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canyouhearthelight · 3 years

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The Miys, Ch. 144

After much demand, Kink Night at the Undine has arrived. This chapter is really fun, was informative to write, but if you need to skip it, you won’t miss out on the overall story. So, trigger warnings on this chapter for:

- Bondage (mentions of)

- Pegging (possible mention of?)

- Impact play (discussed, both done wrongly and demonstrated correctly)

- Topping and bottoming

To be clear: These are all mentioned from the perspective of a non-participant, non-voyeur. I would probably overall rate this chapter appropriate for 14 years and older, but your mileage may vary. However, kink in general can be very healthy if done correctly, and this chapter was double beta-read, not only by @baelpenrose but also by @charlylimph-blog for accuracy of the scene. This actually prevented a PROFOUND mistake from making it to queueing, so I am super grateful for their help.

Once I was released from medical after an unnecessarily long lecture from Noah, I found I had a message waiting from Charly with a date and time to meet at the Undine. Right below that was a message from Sebastian with a uniform-slash-dresscode of sorts.

Aw nuggets. I had forgotten what night it was.

There wasn’t time to grab clothes from my quarters, but my office was on the way to the bar, so I stopped by to change. Socks and shoes were a bit of a challenge, since I generally didn’t wear either, so I had to find a vendor to help me fill in the gaps. Granted, shoes weren’t specified in Sebastian’s list. However, there was exactly a zero percent chance that I was going to lend a hand at a kink party while barefoot. Just… no. Nope. Not happening.

I wiped my palms nervously against my slacks when I arrived, not sure exactly what to expect. Charly and I had talked about it, but none of that knowledge wanted to make its presence known at the moment, apparently. Instead, my mind kept drifting to what in the actual hell she had roped Arthur into doing. The door opened entirely too soon to reveal a smiling Charly, who grabbed my arm and dragged me behind her to the small group already gathered.

All of my nerves were forced from my body by the sputtering laughter I fell victim to when I saw Arthur - I still had no idea what he would be doing, but he looked like someone took a post-apocalyptic movie hero and hit a button labelled ‘make him a villain’ a few too many times. The leather jacket and motorcycle pants were fairly innocuous, since I knew he actually owned both and neither were terribly uncommon on the Ark. Same thing held for the boots - they were just practical in the After and several people held on to that preference with a death grip.

“Cloak’s a nice touch,” I snorted, trying desperately to ignore the campier bits of his outfit.

I was dangerously close to losing it when he scowled and adjusted the laurel crown - I mean, really? - resting on his head. “I knew I shouldn’t have cut my hair this morning,” he muttered. “Damned thing won’t sit right anymore.”

Charly clapped her hands to get everyone’s attention. “Okay, one more run through of what everyone will be doing!”

Sebastian nodded seriously and flicked a towel over his shoulder before handing me an apron. “Sophia has kindly agreed to prep the snacks, while I serve and clean behind people. She’ll clear any dishes in between batches, and one or the other of us will do a lap of the floor every fifteen minutes to ensure everyone is hydrated and there’s no need for medical attention.” He winked at the relief on my face.

Cooking, clearing plates, and momming people into staying hydrated. I could do that.

Arthur brushed off his pauldrons, only forcing me to confront the fact that they were shaped like skulls again, before straightening with aplomb. “I will be Dungeon Master, keeping an eye on everything from there,” he pointed to a scaffold that had been put into place over the bartop, “And intervening as needed if things get out of hand.” Without so much as a twitch of question from me, he explained. “Charly and Coffey can’t be everywhere at once, so I get to perch on high, look ridiculous, and play bouncer if Coffey can’t get there first.”

“Yep,” Charly nodded seriously. For all that she normally seemed built out of chaos and energy, this was Boss Lady Charly. “Let’s keep it safe, sane, and consensual across the board. Speaking of!” She pulled two badges from seemingly nowhere. “Soph, Bash, these are for you.” I took one and immediately grinned when I read it. Staff Only - I Do Not Consent. “If either of you want to play, go for it, but otherwise, probably wear those. Sexy librarian and millionaire CEO are tropes that exist, so ya know - no confusion for anyone. Any questions, concerns, cries for help?” When we all shook our heads, she clapped again. “Okay, off you go! Thanks everyone.”

Sebastian tilted his head toward the kitchen and I followed, wiping my hands on my legs again. “Thank you for agreeing to help with snacks. I know Charly already told you, but I am not the greatest at finger foods that don’t make a mess or won’t be too heavy.”

I hummed for a second before making a few suggestions. “Macaroni and cheese bites, they’re about this big.” I made a circle about an inch and a half across with my fingers. “Just pop and go. Pigs in blankets, the kind with cocktail sausages… meatballs, but probably with lamb instead of beef. Dumplings.” I shrugged. “Charly swears people actually bring food to these, so once that stuff starts coming in, it would just be portioning it and sending it back out. We shouldn’t have too much actual cooking to do.”

He nodded and started grabbing ingredients. “So that leaves drinks, plates, and utensils.” When I reached for a rack of glasses, he stopped me. “No. If one of us drops anything that can break, people can get injured. I’ve been stocking up on fiber-based plates, forks, and spoons. Drinks are going to be in those corn-starch gel pouches.”

“Dude,” I groaned. “Those things get so gummy.”

“Straws are real and do exist.”

“Besides, I can already tell someone is going to find alternative uses for those,” Arthur called from behind us. I swear, I could hear him smirking. “You can’t put humans, sex, and flavored liquid in the same room and not expect that.”

I shook my head with a smile, but he had a point. Once we shooed him away, work on the snacks went pretty quick. Judging by the sounds coming from the main room, it was a good thing, too - furniture being dragged, then Arthur’s voice ringing out to welcome everyone. Soon, Sebastian was swinging out of the kitchen door with the first trays, and true to Charly’s word, he came back carrying a plate of neatly stacked fudge, followed by Arthur carrying a covered container.

“Scratch the meatballs, someone brought an actual mountain of sausage balls,” Arthur grunted as he slammed the container on a flat surface before retreating.

“Not even a joke?” I mused.

“Must be slipping,” Sebastian grinned. “I mean, he said ‘balls’ twice…”

“Low hanging fruit!” a voice called from the main room. It must have seemed entirely out of context to the crowd, but Sebastian and I were laughing as we started plating so he could carry more food out to the spots Charly had designated.

A timer went off, so I took the mac and cheese bites out of the oven, snagged a tray of drink-blobs, shoved a fistful of straws into my apron and took off to do my lap of the event. There were already people taking a break, reaching gratefully for hydration. Several times, someone would reach for one and pour it in a partner’s mouth, and on one occasion, a woman offered it up like a gift to a bound man, both biting into it and drinking greedily.

I almost stepped on someone before I realized there was an actual pile of people on the floor. I diverted my eyes quickly from what I thought was an all-out orgy before my brain registered that I wasn’t hearing sex noises - just whispers. Snapping my eyes back up, it took a moment to figure out that I had nearly stepped on the largest cuddle pile I had seen since my apartment on Insert Winter Holiday. Crouching, I balanced what was left of the drink blobs on one hand while holding out the straws with another. In no time at all, the tray was empty and I was heading back for more.

This time, food on one hand, drinks on the other, I exited the kitchen to see Charly wrapping up her rope-bondage safety lecture before starting to demonstrate different knots on a volunteer, with Charly in the role of the top for this scenario. Watching her calmly contort and restrain another human being while calmly explaining the psychology behind it was… kind of terrifying. I had to constantly remind myself that this person volunteered and that Charly was experienced on both ends of the rope.

One more sweep of the room landed me with only a dozen or so drinks left on top of a pile of empty trays. I backed into the kitchen to sanitize and re-load the trays, only to hear Sebastian swearing. “Who the hell brought chili!?”

“Apparently someone thought it was a good idea,” I shrugged, baffled. I mean, it didn’t seem like a good idea to me, but this wasn’t exactly my area of expertise. “Maybe we put it in bowls, set up a little station in one of the break areas, with toppings? Let people help themselves?”

“Bondage potlucks and chili…” He shook his head. “Trying to remind myself that I’ve seen weirder things, but…”

“I can promise you, they are having fun. And they’re hydrated!” I shook my mostly empty platter of blobs at him.

Sebastian went out to retrieve more food from the people who brought it, and I kept rolling sausages in dough. “More fudge!” he crowed. “I snagged a piece of the first batch, and it was amazing.”

“You clearly do not see the irony,” I muttered where he couldn’t hear me. “Oh, heavens, no chili! But fudge… fudge is fine…”

The next time I was able to break free and take my designated lap, a slight bit more chaos had descended as everyone had gotten more comfortable. Several of the more experienced were examining and complimenting each other on their knots and arrangements of their subs. Ivan and Jokul were doing…. Something… that involved Ivan in a gorgeous evening gown and Jokul with a gag in his mouth. I was almost done with my circuit when a thud reverberated behind me and a black cloak whipped by.

“For the love of…” Arthur growled. I thought he was going to dribble the cowering man he was glaring at like a basketball, but instead he brandished a marker and made two quick X’s on a bare pair of buttocks. “Here and here. Only here and here.” With an irritated flourish, he wrote NOT HERE across the small of the attached back. “This will give someone kidney damage. Specifically you if I catch you doing it again.” Ducking around to the face of the person he had just used as a whiteboard, he shook his finger. “And I’m not even going to apologize, because you have a safeword and you need to use it. First, last, and only warning, you two. If that hit had been any more than a nervous first tap, you wouldn’t even be getting that.” Without a word, he snagged the cane sitting on the table nearby and took it with him. “They aren’t getting anywhere near the cane, fucking idiots. Gotta talk to Charly about those two…” he muttered as he blew back past me, so angry he didn’t even acknowledge that I was standing there.

I almost dropped the stack of empty platters when the Imperial March started playing while Arthur stomped back into his position over the bar. “Attention, Deviants! Courtesy of some poor practices I’ve seen, I would like to invite Sir Coffey and his pet fae Charly to give us a tutorial on safe and proper impact play!” Applause started as he beckoned them forward, Sebastian theatrically adjusting the lights to center in front of the stage.

I ducked back into the kitchen as Coffey’s voice rang out over the crowd, explaining yet again safewords and consent before launching into what toys were used how and where. A little public humiliation never hurt anyone, I joked with myself. At least not for some of the people out there.

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#the miys #found family #humans are weird #science fiction #aliens #apocalypse #humans are space orcs #humans are space fae #earth is space australia #post apocalypse #post post apocalypse #original science fiction #original sci fi #original writing

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johnboothus · 3 years

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Willett Pot Still: The Liquid #BourbonTok Loves to Hate

For more stories on TikTok, check out our whole series here.

“What’s up Bourbon TikTok? … Today I want to tell you about my least favorite bottle in my collection,” says Chad Watson, a Lexington, Ky.-based bourbon enthusiast who goes by @mydailybourbon. Wearing a black tie with a zippered gray jacket, over the next 40 seconds Watson discusses how much he dislikes Willett Pot Still Reserve — “too malty, too earthy, too grassy” — which has become the bourbon that TikTokers most love to hate.

Spend any amount of time on so-called Bourbon TikTok and you can’t help but run across hundreds of reviews for Willett Pot Still Reserve. Some are professional, most are amateur, a few are earnest, many more are comical, bordering on cruel. And they’re nearly all negative, as though slamming this particular whiskey is a rite of passage in becoming a bourbon reviewer on the exceedingly popular platform.

So how did Willett Pot Still Reserve become the most dunked-on bourbon in all of TikTok?

“TikTokers are doing a service that others in the blogging, YouTube, Instagram, and even the podcast space can’t,” believes Kenny Coleman, host of the Bourbon Pursuit podcast. He says that once something like these Willett Pot Still slams take off via TikTok’s algorithm, more are certain to follow. “So now bourbon reviewers on TikTok are getting a message out to people who didn’t necessarily know there even are bourbon reviews,” he says.

@whiskeydizz

Honest and Unbiased Review #willett #potstill #bourbon #fyp #bourbontiktok #whiskey

♬ Blade Runner 2049 – Synthwave Goose

Zero Point Zero

For connoisseurs, Willett holds a hallowed position in the American whiskey pantheon. The company humbly began in 1984 when Even Kulsveen purchased it from his father-in-law, Thompson Willett, and renamed it Kentucky Bourbon Distillers. But Kulsveen wasn’t actually distilling anything, instead sourcing unwanted stock from nearby distilleries like Bernheim, Four Roses, Heaven Hill, Jim Beam, and the vaunted Stitzel-Weller.

As the modern American whiskey boom began to take shape in the early aughts, Kulsveen’s son Drew began releasing their most primo stock as cask-strength, non-chill-filtered single barrels under the umbrella Willett Family Estate. Some of these, with names like Red Hook Rye, Doug’s Green Ink, and Rathskeller Rye, became some of the most acclaimed releases in American whiskey history. Pretty much all Willett Family Estate bottlings released since 2006 now sell for hundreds if not thousands of dollars — and, if you lack knowledge and connections, you really have no chance to ever score any.

“Purple tops, green tops, that’s fun stuff, but when it comes to [Pot Still] … it’s just not for me,” says Watson.

Unfortunately, almost all Willett looks identical — Cognac-style bottles topped with, as Watson mentions, purple foil tops, green foil tops, or white wax. All are slapped with stark white labels featuring the Willett family crest, with the only identifying differences being tiny, handwritten details indicating each bottle’s age, proof, and sometimes an esoteric barrel number. (For a while, the whiskey internet circulated a Google spreadsheet to keep track of these barrel numbers.) All this is what makes the Willett portfolio, if you will, completely inscrutable to newcomers.

“Willett is a very notable brand and people love to chase their limited releases,” says Watson. “So Willett does what most brands would do in that case: creates a product that draws people with their eyes, is priced decently, and is pretty much always available.”

That product, of course, being Willett Pot Still Reserve, the only Willett whiskey ever released into the mainstream. And that’s where I suspect the cognitive dissonance sets in.

Newcomers to the bourbon hobby see the reverent tones Willett is spoken with online, then assume that all Willett is the great Willett that whiskey geeks have been stockpiling for years. The fact that Willett Pot Still Reserve comes in an eye-catching glass decanter — meant to look like a literal copper pot still — solidifies the fact they’ve stumbled upon a good score, which makes the ensuing disappointment once they finally taste it all the worse.

“What’s up guys and gals, this is Kent Davis, wanting to give you an honest bourbon review,” says @kentedavis33, speaking over a still image of the Pot Still bottle. His following nine-second TikTok is a succinct slam:

“Nice bottle, but zero point zero.”

@mattybourbon

Willett Pot Still Reserve Review#bourbon #bourbonreview #whiskey #whiskeyreview

♬ original sound – MATTYBOURBON

Nicest Looking Bottle in My Collection

That “nice” bottle is exactly what leads to so much animus, claims Watson.

“Once people try the juice inside, they realize they have been duped,” says Watson. “For what seems like an amazing art piece, the liquid inside just doesn’t match the standard. It tastes young, earthy, and very green.”

Almost all Pot Still appearances on TikTok begin with the reviewer mentioning how much they like the bottle. In his review, Watson notes that the “bottle shape … is really cool.” “Pretty neat bottle…” says @glennflashwells. “Nicest looking bottle in my collection hands down,” says @mattybourbon. In many cases that will be the last wholly positive thing uttered by the reviewer.

Florida-based Andy Mauldin (@ronbourbondy) chose Willett Pot Still for his first-ever TikTok review earlier this year, claiming he’s never tried it before. Though even that doesn’t stop him from comically coughing after his first sip.

“Whahoooooaa, that is hot!” he exclaims as he struggles to clear his throat. He eventually calls Willett Pot Still Reserve “trash,” noting that the bottle is its “only redeeming quality.” Josh Grundemann (@bassinandbourbon) also coughs, nearly choking after sipping his first-ever Pot Still pour.

“That might be the worst bourbon I’ve ever tasted,” states the Louisiana man.

@bassinandbourbon

Is Willet Pot Still worth it? @60secondbourbonreview and @caseywarr do! Here’s my thoughts! #BourbonTikTok #Bourbon #fyp

♬ original sound – Josh Grundmann

In a way, you could say a TikToker’s first sip of Willett Pot Still is the baptism by firewater that catapults them to the next level of connoisseurship. Maybe they’ll now be ready to get more serious with their bourbon reviewing. Or, maybe they’ll just want to milk the “Pot Still sucks” joke even further — by now it’s started to become a sort of TikTok meme.

Maudlin, for his part, did a follow-up TikTok where he dumps his remaining Pot Still into a fancy crystal decanter, jokingly hoping his wife will now assume it’s the “good stuff,” and thus drink it after running out of her preferred rosé.

If many Pot Still bashers go for the laughs regarding how awful it is compared to the luxe accommodations of the bottle it is housed in, there are a scant few TikTokers who are more earnest in their reviews. Steve Higdon (@60secondbourbonreview) finds Pot Still “pretty mellow” and “easy to drink.” Casey Warr thinks it’s “okay stuff.” While @mattybourbon calls it “not a great bourbon,” though admits it has a nice nose with notes of buttered popcorn, scoring it a decent 5 out of 10.

Those reviews might not elicit laughs or a viral view count, but they’re more accurate in their assessments. Pot Still Reserve is certainly not good — and I would never keep a bottle of it in my house — but it’s not as bad as TikTok would have you believe. Distiller rates it an 88 (out of 100), while Drink Hacker scores it a B+. That feels about right to me. Rumors abound that the spirit has gotten worse over the years, changing from a rye-flavored single-barrel bourbon to a wheated “small batch” blend of undisclosed origins. Whatever the case, it is almost certainly not 100 percent distilled via pot still, which makes the name and bottle design even more amusing.

That’s why the online anger continues to flow, with neophytes thinking they scored the world-famous Willett, seeing the fancy bottle suitable for displaying on the back bar, resting their iPhones facing them in selfie mode, firing up TikTok, taking a big sip, and then realizing (on video) that they just threw 50 bucks down the drain.

And, comical though these may be, maybe Willett should start paying more attention to them.

“Whiskey appeals differently to everyone. So there will be camps that like or dislike a certain whiskey,” says Coleman. “But when a majority of people are consistently giving the same message, the brand should take note and adjust.”

Or maybe not, as there continues to be a seemingly endless stream of fresh-faced TikTokers very excited about their recent Pot Still scores. Like @whiskeymorning, who enters his house clutching two bottles of Pot Still by their necks as he dances to Saweetie’s “My Time.”

We’ll wait for his TikTok review once he finally cracks it. My guess is that it will almost certainly involve coughing.

The article Willett Pot Still: The Liquid #BourbonTok Loves to Hate appeared first on VinePair.

Via https://vinepair.com/articles/86ed-proof-willett-pot-still/

source https://vinology1.weebly.com/blog/willett-pot-still-the-liquid-bourbontok-loves-to-hate

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theblackroseofsatan · 5 years

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Developing a Mobile App is a difficult process, but the end product is fulfilling.

The way toward making a mobile app isn't constrained to coding. It includes numerous stages, including thought portrayal and explanation, correspondence with a product advancement organization, cost estimation, prototyping, structure, back-end and mobile improvement, discharge and showcasing.

Truly, it's perplexing – yet the game is positively worth the flame!

As indicated by GeoMobile, clients go through three hours, 23 minutes per day in apps (contrasted with 50 minutes on mobile web and barely two hours spent on PCs). Regardless of whether you intend to convey a definitive encounter to your mobile clients or assemble an app-based business, you're in good shape.

The Mobile App Development Process: 3 Steps to Success

1. Thought depiction and necessities investigation

Contact a product improvement organization and give a general portrayal of your application. For instance, "I need a sustenance requesting app, as Domino's, with the café menu showed on the home screen."

The product improvement organization will at that point set up a ballpark cost gauge utilizing the app you alluded to as a kind of perspective. The expense of structure an eatery app relies upon different variables. These incorporate the nation you re-appropriate the advancement work to, the size of an improvement organization, stage decision, the estimating model, the extent of work, and so forth. No product improvement organization will give you a precise gauge dependent on your general depiction – and that is the place the prerequisites elicitation procedure starts. Be prepared to meet your Account Manager and tech lead face to face/on Skype to settle on your app's list of capabilities – that is, the rundown of highlights that will enable your clients to pick a supper, put in a request and make a protected installment.

Together with the seller, you'll pick the objective stage. Guideline speaking, it's Android and iOS, so you'll need to fabricate two local apps to guarantee consistent experience on numerous gadgets. Additionally, you have to settle on an estimating model. Building a sustenance requesting app isn't advanced science, so you'll most likely sign a Fixed Price (FP) contract and have the option to design programming improvement costs ahead of time. Contingent upon the unpredictability of your task, the correspondence part may take as long as a little while. At last, in any case, you'll have a nitty gritty specialized vision posting all the practical (what your app ought to do) and non-utilitarian (how the app will do it) necessities for your venture.

In case you're going to adopt the Fixed Price strategy, ensure the tech vision covers every one of the highlights you'd like to empower in your application. On the off chance that you understand you need to add additional highlights to the extension amidst the improvement procedure, you'll need to consent to a beneficial arrangement and pay for those highlights independently. As per your FP contract, you won't almost certainly survey your collaboration until the part of the arrangement procedure.

As another choice, you can sign a Time and Material (T&M) contract and be more involved with the undertaking – that is, organize the app includes on the degree, survey the work toward the part of the arrangement (which normally keep going for two to about a month) and direct eye to eye and telephone gatherings with your group. The T&M model is increasingly reasonable for complex and information concentrated mobile app ventures managing bleeding edge advancements like the Internet of Things, man-made reasoning or enlarged reality. Nonetheless, your cost will be more enthusiastically to foresee.

2. Mobile app plan and advancement

The (UI) some portion of an app is only a glimpse of something larger. The mobile app rationale is empowered by a server, which is worked with web advancement innovations like PHP, .Net, Ruby, and so on.

Here the "app rationale" term alludes to numerous things, including live talk (your clients should message call focus workers or conveyance staff legitimately), social highlights (counting the reconciliation with interpersonal organizations, remarks, appraisals, and so on.), referral/client devotion program components (solicitations, extra focuses and limits) and installments. Additionally, you'll need an online administrator support to refresh menu and valuing data, oversee areas, track arranges and characterize conveyance territory.

An extraordinary mobile app is a lot of modules which can be created and sent autonomously. Returning to the sustenance requesting app model, it will highlight different modules like correspondence, social highlights, installments, conveyance administration and chain the executives.

How would you realize what highlights will demonstrate helpful to your clients? You can just tell once you attempt, so you likely should begin with a Minimum Viable Product (otherwise known as the extremely essential rendition of your app), lead testing and extend its list of capabilities dependent on client input. At long last, there's the plan part. Your plan choices ought to be founded on a through client inquire about; you may even get more specialized about it and make straightforward app wireframes in Balsamiq before you address a mobile app improvement organization to clarify your thought better. Together with a client experience (UX) creator, you'll make sense of how app screens ought to be associated with one another to enable your clients to place arranges in the most helpful manner and ensure the plan meets the App Store and Google Play prerequisites.

3. Mobile app promoting Four to five months after the fact your app will be prepared to dispatch – and here comes the hardest part: app promoting. In spite of the fact that apps now expend more than 90 percent of the all out mobile time, most cell phone proprietors utilize only 30 apps all the time. These incorporate Facebook and Instagram, mobile games, instructive apps and business devices. Advertising the app to clients who go to your physical cafés would one say one is thing; imagine a scenario where you're working an online nourishment conveyance business as it were. Clearly, you have to make some buzz around your undertaking before the app goes live. Make certain to distribute an adequate showcasing spending plan (expect around $30K-in addition to) to do the accompanying:

Think about an app include that will enable you to stand apart from the challenge (something like Domino's Zero Clicks will do).

Fabricate a basic WordPress promotion site with an explainer video and data about your undertaking. At that point start a Google AdWords battle to get some traffic and urge clients to buy in for updates.

Run a blog archiving the app making procedure and offer news via web-based networking media.

Start with a MVP and lead early tests to refine your item.

Plan a delicate dispatch to test your plan of action.

Actually quite difficult, correct? With the normal expense per introduce (CPI) in the USA hitting $ 1.64 (iOS) and $ 1.91 (Android) a year ago, showcasing another app on a strict spending plan is a genuine test. Maybe you can draw motivation from Eat24 – a sustenance conveyance organization that chose to promote their administrations on grown-up sites and won enormous.

#mobile apps #apps #development #mobiledeveloper

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filipeteimuraz · 5 years

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Which Content Marketing Strategies Have the Biggest Impact on Keyword Rankings?

The term “content marketing” is a wide umbrella.

It encompasses a plethora of different strategies and techniques.

But at the end of the day, one of your primary goals is to create content that ranks as highly as possible on search engine results pages (SERPs).

This is important because organic traffic is the number one means of generating traffic for many companies.

A study from The Bright Edge even “found that organic search drives 51 percent of all visitors to B2B and B2C websites trumping all other non-organic channels.”

This means one thing.

You need to figure out the relationship between content marketing strategies and keyword rankings.

This is instrumental in fine-tuning your content marketing campaign and finding the right areas to focus on.

In this post, I analyze data from multiple studies and draw on my own knowledge and experience to give you a clear idea of the content strategies demanding the most attention.

So, let’s see which strategies have the biggest impact on keyword rankings.

Rich content

I won’t waste your time telling you about the importance of creating quality content.

You already know that.

But I’d like to share with you this statistic from an infographic on Quick Sprout:

That’s a lot of links!

And I’m sure you know the integral role links play in SEO.

This graph from Moz illustrates the importance of links and their influence on Google’s algorithm:

Let’s put this information together.

When you create rich content, it gets you more links.

These links improve your overall SEO, which improves your rankings.

So, being diligent about achieving and maintaining rigorous quality standards should be of the utmost concern.

Long-form content

Here’s the deal with long-form content.

It’s hot right now. Scorching hot.

I remember a few years ago when your average blog post was only somewhere around 500 words.

But if you look at the vast majority of content that ranks on page one of Google SERPs today, it’s rare that you’ll find anything under 1,000 words.

To prove just how important long-form has become, I would like to show you a couple of graphs.

The first is from a fairly old (September 2012) article I wrote on Quick Sprout.

I got the data from research performed by SerpIQ:

As you can see, every single piece of content that ranked on the first page had at least 2,000 words.

More specifically,

The first result typically has 2,416 words and the 10th result has 2,032 words.

Newer research (September 2016) from Brian Dean of Backlinko shows a similar pattern:

According to his research,

The average word count of a Google first page result is 1,890.

That’s over 500 words fewer than the original research from SerpIQ indicated back in 2012…526 to be exact.

But it still shows us long-form content is a key element in achieving solid rankings.

Why is this so?

The way I look at it, there are two main reasons for this phenomenon.

First, people have a tendency to scan through content these days.

Few actually sit down and read a 2,000-word piece word for word in its entirety.

Instead, they scan through and look at the sub-headers that grab their attention and may read little snippets of text from there.

Long-form content facilitates this new method of reading.

Second, a longer word count tends to translate into more links.

And this makes sense.

The more content you provide, the more opportunities for it to be linked to.

Put all this together, and you can see that long-form content means higher rankings.

Who knows, the whole “long-form content bubble” may pop in a few years.

But it’s stronger than ever at the moment.

However, it appears that the ideal word count has been reduced considerably, and you should aim for just south of 2,000 words.

How do you create 2,000-word content?

Decide on a specific and narrow topic.

Create a compelling title.

Discuss the issue from every angle.

Provide as much detail as possible.

If possible, provide step-by-step instructions on how to do something.

You should never stuff your articles with words just for the sake of hitting a word count.

But you should strive for detail, depth, clarity, and mastery of a subject matter.

Here’s what I’ve discovered about long-form content. When you truly make an effort to provide value in your content, it expands in length.

That’s not to say that you can’t provide value with a 400-word article.

But the level of value created in a 2,000-word article is usually much greater.

Content with “topical relevance”

But the plot thickens.

The same Backlinko article also points out that

content rated as “topically relevant” significantly outperformed content that didn’t cover a topic in-depth. Therefore, publishing focused content that covers a single topic may help with rankings.

Topical relevance basically combines my first two points of creating rich content and long-form content.

It simply means that Google values content that’s comprehensive and that thoroughly covers a topic.

This means it’s best to focus on a single topic for each piece of content you create.

Rather than bouncing around from subject to subject, you’re better off going all in on a single topic and leaving no stone unturned.

Does this mean you can’t discuss other topics?

No. In fact, you should touch on as many relevant topics as possible! But your focus should be on a single topic.

If you feel you need to cover a topic you weren’t able to get around to in the post, create a separate piece of content and cover it in-depth as well.

Using long-tail keywords

This strategy has been in existence seemingly since the dawn of SEO—back when SEO was in its primordial soup stage.

One of the main ways small-scale marketers have been competing with the big dogs is by using long-tail keywords.

And why wouldn’t they? It freaking works.

In fact, I’ve been using this strategy for years.

I even used it to grow my search traffic by 51% in just three months!

And guess what? It still works brilliantly.

An infographic from Adept states that “pages optimized for long-tail keywords move up 11 positions on average, compared to just 5 positions for head keywords.”

It’s really not rocket science.

Using long-tail keywords means less competition, which means a greater likelihood of achieving a favorable ranking.

The awesome thing is that long-tail searches account for roughly 70 percent of searches:

This means there’s plenty of opportunity out there.

Of course, you won’t get the same volume of traffic that you would for a head keyword or broad keyword, but you can still generate some sizable traffic if you do your keyword research and choose a phrase that receives a reasonable number of searches.

Check out this post from NeilPatel.com for a step-by-step walkthrough of integrating long-tail keywords into your blog posts.

The process is fairly straightforward:

Do your typical keyword research (using Google AdWords Keyword Planner or your preferred tool)

Select the long-tail keywords from the list (3 words or more)

Use these keywords in your content.

Image-rich content

If you haven’t heard, people respond positively to images.

It’s true.

And although I think the whole visual-centric discussion has been done to death, I would like to reference one more point from the Backlinko article I mentioned earlier.

According to Brian Dean,

Industry studies have found that image-rich pages tend to generate more total views and social shares.

But here’s the interesting thing.

Using at least one image is much better than not using any images at all.

However, they couldn’t find a correlation between the total number of images and rankings.

That means there’s no proof that using a lot of images will improve your rankings any further.

In other words, using just one image would in theory have the same effect as using 10 or more images.

The key takeaway is this:

Using a single image is clearly better than zero images. Including lots of images doesn’t seem to have an impact on search engine rankings.

When it comes to my posts, this information isn’t going to stop me from sprinkling plenty of images throughout my content.

In fact, you probably know that many of my posts are jam-packed with images.

I think my audience enjoys the “eye candy,” and graphs in particular are excellent for explaining fairly complex concepts.

But keep this in mind when creating your next piece of content: going nuts with images probably isn’t necessary.

Direct answers

If you’re not sure what I mean by “direct answers,” it’s simple.

Google is now starting to show direct answers when you use a “how to,” “what is,” “who is,” etc. type of search.

Here’s an example:

The first thing that pops up at the top of the page is a clip from the top ranking site.

It’s a way to streamline the process and offer searchers direct information without them having to actually click on the link.

Of course, oftentimes they’ll still click on the link to find more in-depth information.

I know I often do.

So, here’s the deal.

Providing a direct answer can be beneficial and a viable strategy for killing it on SERPs.

If you can provide a quick, logical, and direct answer, especially for a long-tail keyword phrase, there’s a good chance you can get your content featured at the top.

Just be sure your direct answer transitions smoothly into the rest of your content.

Here’s how I typically use this strategy:

Identify a question marketers are asking.

Create an article answering this question.

Provide a step-by-step solution to the issue.

When I follow this three-step process, the articles I write on those topics usually rank on page one for the associated keyword within five days or less.

This is the primary technique I’m currently using on NeilPatel.com, and it’s earned me over 800,000 unique monthly visitors.

Conclusion

I value objectivity when determining the approach of my content marketing strategy.

I find that examining the cold hard facts clears most biases and preconceived notions I might have.

This is important because this gives me the clearest path to achieving my goals.

While there are countless factors that contribute to keyword rankings, the ones I listed here appear to have the biggest impact pound-for-pound.

Putting your attention on these key areas should ensure that your content marketing is heading in the right direction while giving you the best chance of climbing in the SERPs.

https://www.quicksprout.com/2019/03/27/which-content-marketing-strategies-have-the-biggest-impact-on-keyword-rankings/ Read more here - http://review-and-bonuss.blogspot.com/2019/03/which-content-marketing-strategies-have.html

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siliconwebx · 5 years

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How to Read for Personal and Professional Growth

People are notoriously bad readers, especially when it comes to online content. We scan and skim to pull out the chunks of information that are most appealing to us. Digest small bits at a time, never finishing an entire article. Make comments, sometimes harsh ones, that clearly show we don’t understand how to read.

You don’t wanna be that type of reader. You’re better than that.

This article isn’t about learning how to read – we assume you’ve already mastered that. It’s also not about figuring out how to read more. A person who has read a lot is not necessarily well read.

Instead, this article is about how to squeeze information, knowledge, insight and wisdom from the articles and books you thoughtfully choose to read – and how to glean some of that good stuff from the books you read not-so-deeply.

Set a Reading Goal

Assuming you need to jump head first into a topic and come out dripping in wisdom, it’s going to be difficult to do that without a reading goal. We want to loosely adhere to the SMART system of goal-setting here. SMART = specific, measurable, attainable, relevant, time-bound.

I recently wrote about how blockchain is influencing other industries. Completely new territory for me. I had to research a lot before I could get started writing. Here’s how I broke down my goal:

Specific: I would discover what blockchain is and what it’s used for, plus three non-cryptocurrency industries that are adapting blockchain technology.

Attainable: I knew zero and the article I was writing was for a beginner audience, so I had to go just one level up in my understanding.

Relevant: I only sourced articles that were published within the past year.

You’ll notice that I skipped “measurable” and “time-bound” – I didn’t feel they mattered for this specific goal. Also, the whole reading process I’m going to lay out is the measurable part.

If you want to tackle a topic that’s two or three levels above your familiarity, that’s fine, even worthwhile. You’ll just want to start with basic, background knowledge first so you can build upon it.

Open Up to the Unknown

Remembering and recalling information is closer to memorization than true learning. A baby can learn how to say certain words and even associate those words with items, but does that mean they have an actual understanding of what the word means or why they’re saying it?

The best way to truly learn about a topic is to read content about that topic that you don’t understand at first. If you read information you easily grasp, you’re not really learning anything new. By reading fresh, complex information, though, you start to build a bridge between what you currently know and what the writer – the expert – knows.

Learning how to read is a lot like learning how to learn. And how do we learn best? By actively discovering something that’s foreign to us. As you’re reading, pause and research the sub-topics and phrases that you don’t understand or mark them for later.

Spoiler alert: at the end of the article or book, you still won’t understand everything you read. That’s kind of the point.

So you’re at the end and you’ve only grasped 60% of what you read. Now re-read it or find an alternative source. You’ll be armed with that 60% of new knowledge and chances are you’ll make some progress on that still-unknown 40 percent.

Embrace the 4 Stages of Reading

How to Read a Book: The Classic Guide to Intelligent Reading by Mortimer J. Adler and Charles Van Doren outlines four stages of reading, with each stage leading to the next.

Elementary: This is the type of reading you learn in, you guessed it, elementary school.

Inspectional: This is the type of reading most people do online (more on that in a bit). It can be either skimming, which is when you quickly look through the content to see if you want to read part of it, or superficial, which is when you read everything written but don’t get too deep (what you do with a thriller or beach read).

Analytical: You’re absorbing and engaging with what you’re reading. You understand the terms the writer is using, you get what the main argument is and you can determine whether or not those arguments are resolved. You may also decide the writer’s wrong about some points or that certain thoughts are illogical.

Syntopical: Not only are you reading analytically, but you’re developing your knowledge based on what you’ve read, your own experiences and how you feel about it all. The book is simply one of the tools you use to create your own outlook and understanding. You’ve made what you learned your own.

Become a Master Reader

If you want to flex your syntopical reading muscle, pick up the newspaper (let’s get real – bring it up online).

First, read it as you usually do. Skim the headlines for something that interests you and superficially read part of the article. Done. You’ve learned enough to hold a (short) conversation over dinner tonight.

We’re going to do things differently this time.

Pick an article that’s out of your comfort zone, a topic you don’t understand much about. Read it carefully. When you don’t understand a term that’s used, look it up. If you don’t get a reference to another news story, find it and read it. Round out the information so you actually, fully understand what the writer is saying.

Next, look up four more articles on the same topic. Try to find different sources – if you get all of your articles from the same newspaper, facts and perspectives will be repeated. Read those four articles analytically, too.

Sub-steps of the greater syntopical step.

You don’t have to read every single thing. Start by skimming to discover the sections that will be most important to your goal.

Different authors will use different terms for the same thing. Start to create your own terms and language to streamline the information you take in.

Define the questions you want answered, which may differ from the questions the writer is trying to answer.

Pay attention to every side of an issue. Gather information from all perspectives in order to form your own informed and intelligent answers.

You understand what you’ve read – and you’ve read a lot. You get what each writer is saying, the points they’re making, the knowledge they’ve brought to the table.

Say it out loud, whether that’s through a conversation with a friend, your blog or a private Word document. Your challenge is to form your own opinion. Talk about where you match up with the writer’s opinion, where you wholeheartedly disagree and where you fall into a gray area that wasn’t covered in anything you read.

Congratulations. You’ve just become a syntopic reader.

Choose the Right Reading Method

Thorough reading takes a lot of focus and brainpower, and it doesn’t always have its place. I can read Stephen King superficially and get exactly as much out of the experience as I want, no more and no less. If part of my personal growth includes having conversations with my friend who’s also a Stephen King fan, then I’ve done my job.

If I were to analytically read Stephen King novels, I’d (a) take time classifying the book as horror, thriller or suspense, (b) try to understand why he always, always over-describes technology we’ve all used forever and (c) probably turn myself off to Stephen King for life because this is just too much work.

You don’t have to turn what you’re reading into a job if that’s not the goal. There’s a lot to be said for skimming or reading superficially, or reading part of a book analytically and then superficially reading the parts that don’t impact you (my favorite tip for getting through a self-improvement book). When you purposely read less analytically, you also have the option to stop reading cold turkey if you’re not enjoying the book or you’re not getting out of it what you want to.

If you’re an avid reader, knowing why you’re reading and adapting your reading style to that goal is a way to save energy for the times you do need or want to be analytical or syntopic.

Making All This Work in Real Life

In a perfect world, you’d have a clear idea of what topics you want to dive further into, easily gather the necessary content for that deep dive, have the time to analytically and syntopically explore each of them, then magically find the one person who can have an intelligent conversation about the topic you just became a quasi-expert on.

I live in the real world, though, and most nights my book hits the bridge of my nose as I start to nod off after getting just half a chapter along. Here are my tips for real world reading when life gets in the way. These aren’t a replacement for purposeful reading, but they make great alternatives when you have to negotiate with yourself.

Read out loud. This is a trick I use when I fall into that trap of re-reading the same paragraph multiple times without paying attention. Apparently it’s a real psychological trick, too.

Jot down questions as you read. You may not know all the ways you want to explore the topic when you’re getting started, but questions will arise as you read, which will lead you to other sources.

Use the impress, associate and repeat method. Picture the scenario in your head, associate it with something you already know and then repeat the material by highlighting it and going back to it later.

Pay attention to the connections. It’s not an accident when something you just read relates to something you read last week or last year or even last decade. Your brain is building bridges.

When launching into a conversation with someone, make your first talking point that thing you just read. You may uncover more of your own views as you talk about it out loud.

Getting more out of what you read lets you approach a topic, and conversations about it, in a more educated manner. Not only is this helpful in your personal life to develop skills and have better conversations with people, but it’s especially useful in business. If part of your job is explaining a topic to an audience, you’ll want to do it in a way that’s completely new.

Ready to advance and enhance your knowledge? We have a must-read list just for you web designers out there.

The post How to Read for Personal and Professional Growth appeared first on Elegant Themes Blog.

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unlovedaddict · 6 years

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This Year Will Be The Year of SEO 2019

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Regarding successful team management and inter-client cooperation, online editors really are usually a must, especially those which usually detect and highlight critical SEARCH ENGINE OPTIMIZATION errors, non-unique, text, and key word stuffing. By the end of this particular module, you should be capable to define Search Engine Search engine optimization and explain the basics associated with SEO as being a business (as properly as how SEO shapes the particular Internet itself. ) You'll furthermore be able to explain the particular differences between three main SEARCH ENGINE OPTIMIZATION job types, and be ready to choose a career that will best suits your current objectives. A highly effective research marketing campaign, will encompass each search engine optimisation (SEO) plus pay per click advertising (PPC). One of our favorite on the internet toolkits is SEMrush, which consists of a variety of tools with regard to SEO, content marketing, and internet marketing. An SEO Content Writer is usually somebody who writes content for the particular purpose of having it display up on search engines plus gain website visitors. Internet marketing perfect for the platform of SEARCH ENGINE OPTIMIZATION or Seo. With voice search arrives two areas of interest in order to SEO folks wishing to link with consumers: intent and framework. SocialSEO is proud to help future experts in the globe of business and marketing along with the annual SocialSEO Digital Advertising and SEO Scholarship. Finally SEO Wise links enables you to arranged nofollow attribute and open hyperlinks in new window. An extensive dental marketing plus dental SEO campaign can end up being attained by the enterprise just if the web address associated with a dental practice contains in to all the promotional materials with regard to the business. This shows the importance of focussing voice search engine results within order to grow your company, marketing, and Search Engine Optimization(SEO) strategies. They accomplish this by increasing their web site rank through a method known as SEO or even search engine optimization. Just like just about all other SEO approaches, be certain your links are appropriate, plus be careful to not cross the particular line into excessive linking : you don't want your site visitors to obtain annoyed. Bryan Yeager, Research Director at Gartner, can share 9 Key Insights through Gartner's Marketing Technology Survey in order to Help You Prepare for 2019 and Beyond. SEO is a combination associated with digital marketing efforts all operating together to increase a website's value to users and presence in search. On-page SEO (also identified as "on-site" SEO) could be the action of optimizing different parts associated with your site that affect your own search engine rankings. In 2019, we will have to optimize voice research answers with CTAs that Google's algorithms don't pick up upon, but humans do. Dan Mallette, Lead SEO Strategist at each InVue Digital & HearstDMS, forecasts that SEOs will need in order to optimize for voice search and discover new avenues as SERP real-estate shrinks. Obviously, a social networking site that has more interaction will probably bring bigger SEO benefits to be able to some business than one the fact that has less interaction, but simply having a social presence will be a good start.

0 notes

webanalytics · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “Conversions” Are Flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “Top” Traffic Sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

One of the biggest publishers in the world. One of the most respected. Who gets paid based on the number of visitors and page views they get. Has no idea how a quarter of their traffic is getting to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the Funnel Performance = Results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

Or use the Kissmetrics’ Customer Engagement Automation tool to analyze what people are actually doing on your site and with your products. Then, you can interact with behavior-based messaging to keep them around longer. Or keep them coming back for more.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “Wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

Instead, it allows you to compare different page variations to see which ‘bigger’ changes result in improvements. Maybe this works a little better because it adds an extra letter– it’s an A/B/N test.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

That credit card field you took away? It was a huge indicator for which of your customers will eventually buy. 50% of people who put in their credit card will end up converting. While only 15% will of those who don’t enter a credit card will.

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your Channel Source Attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

For example, if you’re spending a ton on ads, you might want to see how the First Interaction looks. Especially when using social ads that often bring people into your ecosystem for the very first time.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Remember that conversion results aren’t always spot on. Direct traffic data might not be correct. Vanity metrics aren’t everything. A/B results can fire off false positives. And last touch isn’t everything.

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

About the Author: Brad Smith is the founder of Codeless, a B2B content creation company. Frequent contributor to Kissmetrics, Unbounce, WordStream, AdEspresso, Search Engine Journal, Autopilot, and more.

from Search Results for “analytics” – The Kissmetrics Marketing Blog http://ift.tt/2wkTx6Q #Digital #Analytics #Website

#Analytics #Search Results for “analytics” – The Kissmetrics Marketing Blog

0 notes

samiam03x · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “Conversions” Are Flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “Top” Traffic Sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the Funnel Performance = Results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “Wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your Channel Source Attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game-changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

http://ift.tt/2eSlhd1 from MarketingRSS http://ift.tt/2xW6h58 via Youtube

#MarketingRSS

0 notes

marie85marketing · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “Conversions” Are Flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “Top” Traffic Sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the Funnel Performance = Results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “Wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your Channel Source Attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game-changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

0 notes

alissaselezneva · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “conversions” are flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “top” traffic sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the funnel performance = results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your channel source attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

from WordPress https://reviewandbonuss.wordpress.com/2017/09/11/5-lies-you-tell-yourself-about-your-analytics-and-how-to-fix-it/

#New Post

0 notes

seo78580 · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “conversions” are flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “top” traffic sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the funnel performance = results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your channel source attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

from DIYS http://ift.tt/2wkTx6Q

#DIYS

0 notes

reviewandbonuss · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “conversions” are flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “top” traffic sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the funnel performance = results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your channel source attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

0 notes

filipeteimuraz · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “conversions” are flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “top” traffic sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the funnel performance = results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your channel source attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

Read more here - http://review-and-bonuss.blogspot.com/2017/09/5-lies-you-tell-yourself-about-your.html

0 notes

ericsburden-blog · 7 years

Text

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

Consulting data is good.

But being a slave to data, is not.

There is such a thing as being too data-obsessed. Confirmation bias pops up. And you miss the good, albeit, intangible stuff that comes along with your efforts.

The solution is to uncover those biases and misunderstandings that lead you astray.

It’s not easy. Or even intuitive. But it’s the only way to avoid these five analytics blinders.

Here’s how it strikes when you least expect it.

Here’s why you fall for it.

And here’s how to avoid it by bringing in other types of feedback and analysis.

Lie #1. Your “conversions” are flawless

You’ve got three AdWords campaigns.

The first brings in zero leads on $78 bucks spent.

The second brings in one at a cost of $135.31.

The third brings in two at $143.28 per lead.

Nine times out of ten, the campaign with more “conversions” is declared the winner.

But what do you really, truly, know about this scenario?

Which campaign is actually performing the best? Which is putting the most money back into your pocket?

There’s simply no way to tell at this point.

First and foremost, these “conversions” are leads — not closed customers.

Second, they might be for different products or services. So different average order values or LTVs come into play.

Third, this is nowhere close to statistical significance. For example, the third campaign has the most leads because you’ve spent the most money on it.

Not because it’s “better.”

What if you simply spend the same amount on the first two? What if you let them both get to around the same ~$150/per mark?

See what I mean?

Too many “what ifs” for my taste.

Yet this is exactly what happens inside any marketing department. The same end result pops up after each client or superior meeting.

Everyone points to the third campaign. It gets the adulation. It gets the increased budget. It gets the additional staff and resources.

So it becomes a self-fulfilling prophecy.

One solution to figure all this out is closed loop analysis.

Ideally, your goal is to match up the customer’s information (name, email, phone, credit card) to the lead data you’re seeing inside Google Analytics.

Haha — just kidding.

That would mean you were gathering Personally Identifiable Information, which is a big no-no in Google Analytics.

Do it and they’ll delete your account right away.

The simplest alternative is to just use a tool that gives you this power, without jeopardizing your data. Hint, hint.

Lie #2. Your “top” traffic sources

What are your top sources of traffic?

A quick glance inside Google Analytics usually tells you (1) organic search and (2) direct. Maybe a little (3) referrals thrown in for good measure if you got some press last month.

Here’s the problem.

Two of those three are legit. The other is not.

The problem is that your direct traffic isn’t, in reality, all that “direct.”

Technically, this should be the number of people typing in your website URL to the address bar and hitting “Enter.”

Instead, it’s a healthy mix of email, social media, and good ol’ organic search.

The bigger the site, the bigger this problem usually is.

For example, The Atlantic couldn’t account for or explain how 25% of their visitors came to their site.

That ain’t good.

But how can you really tell where people are coming from, if most analytics programs can’t tell you with any degree of accuracy?

For instance, let’s say your new, fantastic-looking email campaign is about to go out.

It’s been given the green light. “Legal” gives you the A-OK.

But wait! You didn’t tag the promo links correctly.

Now, you’ve spent all that time on a campaign that won’t have anything to show for it, because the traffic you get will now end up in the dumpster pile officially known as “Direct traffic.”

This isn’t just an email. It affects each and every social message, press mention, and blog post referral, too.

It can even affect your organic search traffic.

Groupon found this out the hard way. Literally. By completely de-indexing themselves for a few hours.

What did those crazy couponers find? That nearly 60% of their direct traffic was actually coming from organic search.

Sixty-freaking-percent.

But don’t freak out just yet. There are solutions here.

First, you can use Google’s UTM builder to make sure you are properly tagging your links. This means any and everything you have control over.

Manually tag them before they head out the door, or copy & paste into a lightweight app like Terminus.

If you’ve got long, cumbersome URL, you can be pretty sure that any traffic to that page didn’t come from Direct traffic.

People aren’t going to remember it. Which means they aren’t going to just spontaneously type it in.

Instead, these peeps probably came from another place, like an organic search or email.

However, in the same breath, you can probably consider homepage traffic to be legitimate Direct.

So create a segment based on these URLs and traffic sources to pinpoint “Dark Traffic” in its tracks. And prevent it from ruining your data in the future.

Lie #3. Top of the funnel performance = results

Yes, we want traffic.

Yes, we want pageviews.

They make us feel all warm and fuzzy and proud. Like our hard work isn’t going unnoticed.

But they should not be the end-all, be-all.

Use them to see how you’re doing over last month. But don’t misunderstand numbers to be the Holy Grail, either.

Like this, for instance:

Looking at only this, you walk away feeling like a boss for all the numbers you’ve racked up. Seriously, I can’t even count that high.

But what about when you consider the bounce and exit rates for each of those pages? Are people staying? No? Color you embarrassed.

Are you still so excited by your thousands of pageviews if most of them left immediately?

Bounce rates are real. And you’ve gotta consider them when you are looking at your metrics.

They mean that people haven’t had the chance to interact with your soft micro conversions. They haven’t had a chance to activate.

So take a look at the big picture.

Are your blog posts and site pulling people in, but not making them stay?

This isn’t a horrible problem to have, because it’s a problem you can pinpoint.

The traffic is there. They just don’t really like what they are seeing once they get to your site. Which you can fix.

First, set up some events to get a better idea of what’s happening on your pages. Then, make sure you have actionable goals that will allow for movement you can track.

That way, you can increase conversions, engagement, and retention without the guesswork.

Just always remember that numbers don’t tell the whole story. Use them with a grain of salt and a little bit of context.

Lie #4. Deceptive A/B “wins”

I’m just going to be honest with you. Those A/B testing “wins” you just got? Don’t always have the best track record.

I’m sorry to be so harsh right off the bat. Sometimes the truth hurts.

What’s even more worrisome? Oftentimes, tests will look like they have succeeded. But that’s not always the case (or at least, not the whole picture).

Start with Google Analytics content experiments, instead.

You can use it to contrast your varying pages to see if there are any sizeable adjustments that cause positive changes.

The problem with this test is when you get a little too grab-happy.

You can quickly and easily remove fields to get better results, for instance. A simple reduction of three fields will increase your conversions by 11%.

Or, you can take away specific conversion-busters like the need to add a credit card for a non-paying trial. Sure, this will up your “conversions.”

But remember how far that got you a few lies ago?

And we’re talkin’, conversions-conversions here. Like, bottom-of-the-funnel, paying customer conversions.

Context is key when you are looking at analytics.

Don’t test landing pages or simple changes to fields while only evaluating the top of the funnel. Make sure you dig in to see how the changes affect the rest of the customer experience and journey.

To do that, use the Funnel Report so you can see exactly how top-of-the-funnel changes are impacting bottom-of-the-funnel sales.

Lie #5. Your channel source attribution

A Forrester Research study years ago found that 33% of all transactions of all transactions happened after new customers had gone through more than one touchpoint.

That number jumps to 48% when considering repeat customers.

The same report showed that paid search is the highest source of conversions.

Is it, though?

Or is it just the last point most commonly used before a sale?

Just because it’s the last one, doesn’t mean it’s the only one.

What other marketing tactics are working to increase growth? Forrester went on to declare that while email works for repeat conversions, social media brings in less than 1% of sales.

Ok. Then how do you explain SpearmintLOVE?

You know, the freaking baby blog that boosted their revenue by 991% in year using Facebook and Instagram.

The only reason I know about them? Because my wife has bought clothes from them. After discovering them on Facebook and Instagram.

One, simple Google graph puts this myth to bed. Fast.

If you look at the left side, or “assist interactions,” you’ll see that social channels will put new products in front of people.

As you move toward the middle, customers get more information about products and options using search. At the end, they’re on their way to the website.

Notice all the possible interaction options here. It’s not just the last-touch that brought the customer to the website. They can take many steps to get there.

Google Analytics has a few different attribution options built-in to help you change how conversions are assigned.

Image Source

These include:

Last Non-Direct Click: This will overlook Direct clicks and go to the channel used right before.

First Interaction: This uses the social or advertisement that got them to the website.

Linear: Here, each channel that a customer used before purchasing will get equal attribution.

Time Decay: This will consider the channel that was used immediately before conversion, rather than channels used in the past day/week/month.

Position: This model gives priority to the first and last channel used before conversion. Anything in the middle gets less attribution.

The depressing part, though?

There’s no right answer here. The attribution model you pick largely depends on your sales cycle, your customers, and even what specific objective you’re trying to figure out.

In other cases? It would be a terrible choice.

The trick is to know what you’re solving for, first. Then working backwards.

Conclusion

Data is important. It’s huge.

YOOGE.

But, be careful.

Google Analytics is a marvelous, cost effective, game changing tool.

However, it’s been known to lie a little from time-to-time. (Yes, we’re still talking about Google Analytics here.)

Uncovering biases is never fun.

But it’s the key to creating campaigns that actually achieve results.

Without just blowing a lot of hot air.

5 Lies You Tell Yourself About Your Analytics (And How to Fix It)

0 notes