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chloedecker0 · 3 months

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Maximizing Retail Profits: Harnessing B2B Price Optimization Software

In the ever-evolving world of retail and e-commerce, businesses are constantly seeking ways to gain a competitive edge. Among the many strategies employed, B2B Price Optimization and Management Software stands out as a game-changer. Price optimisation and management (PO&M) software solutions enable businesses to oversee and optimize the prices of their goods and services. These services also provide a growing range of sales intelligence advice, such as best-next-action suggestions and customer churn warnings. In the industry, vendors either focus on back-office price management and product management roles, or they focus on providing real-time sales intelligence to sales representatives and B2B digital commerce websites, or both. Quadrant Knowledge Solutions, a leading global advisory and consulting firm, has recognized the significance of this technology in their report, “B2B Price Optimization and Management Applications, 2023”. Quadrant Knowledge Solutions focuses on helping clients in achieving business transformation goals with Strategic Business, and Growth Advisory Services.

Download the sample report of Market Share: B2B Price Optimization and Management Software

Understanding the Retail and E-commerce Landscape

The retail and e-commerce industry is a highly dynamic and competitive space. Companies within this domain face the continuous challenge of pricing their products right to maximize profitability while staying attractive to their customers. In this context, pricing becomes a critical element of their strategy. Let's delve into some of these challenges:

Rapidly Changing Market Dynamics: Retail and e-commerce markets are highly volatile, with ever-shifting consumer preferences and market trends. Adapting to these changes in real-time is essential to stay competitive. Without the right tools, businesses risk making pricing decisions that are out of sync with market realities.

Intense Competition: In retail and e-commerce, competition is fierce. With numerous players offering similar products or services, pricing becomes a key differentiator. Setting prices too high can drive customers away, while pricing too low can erode profit margins.

Complex Supply Chain and Cost Structures: The retail and e-commerce sector often deals with complex supply chain operations and cost structures. Understanding the true costs associated with a product or service is essential for setting optimal prices. Traditional methods of cost calculation can be time-consuming and error-prone.

Customer Behaviour and Expectations: Today's consumers are more informed and price-sensitive than ever before. Their buying behaviour can change rapidly in response to various factors, including promotions, discounts, and market trends. Retailers must be agile in responding to these changes.

Competitor Pricing Strategies: Keeping a constant eye on competitor pricing is crucial. Businesses need to respond promptly to pricing moves made by competitors to remain competitive. Manual tracking and analysis of competitor pricing are arduous and inefficient processes.

Download the sample report of Market Forecast: B2B Price Optimization and Management Software

B2B Price Optimization and Management Software: A Necessity

B2B Price Optimization and Management Software is the solution to these challenges. This technology leverages advanced algorithms, data analytics, and real-time market insights to help businesses make data-driven pricing decisions. It empowers retail and e-commerce companies to optimize their prices efficiently while taking into account factors like demand fluctuations, competitor pricing, and customer behaviour.

Talk To Analyst: https://quadrant-solutions.com/talk-to-analyst

#In the ever-evolving world of retail and e-commerce #businesses are constantly seeking ways to gain a competitive edge. Among the many strategies employed #B2B Price Optimization and Management Software stands out as a game-changer. Price optimisation and management (PO&M) software solutions en #such as best-next-action suggestions and customer churn warnings. In the industry #vendors either focus on back-office price management and product management roles #or they focus on providing real-time sales intelligence to sales representatives and B2B digital commerce websites #or both. Quadrant Knowledge Solutions #a leading global advisory and consulting firm #has recognized the significance of this technology in their report #“B2B Price Optimization and Management Applications #2023”. Quadrant Knowledge Solutions focuses on helping clients in achieving business transformation goals with Strategic Business #and Growth Advisory Services.#Download the sample report of Market Share: B2B Price Optimization and Management Software #Understanding the Retail and E-commerce Landscape #The retail and e-commerce industry is a highly dynamic and competitive space. Companies within this domain face the continuous challenge of #pricing becomes a critical element of their strategy. Let's delve into some of these challenges:#Rapidly Changing Market Dynamics: Retail and e-commerce markets are highly volatile #with ever-shifting consumer preferences and market trends. Adapting to these changes in real-time is essential to stay competitive. Without #businesses risk making pricing decisions that are out of sync with market realities.#Intense Competition: In retail and e-commerce #competition is fierce. With numerous players offering similar products or services #pricing becomes a key differentiator. Setting prices too high can drive customers away #while pricing too low can erode profit margins.#Complex Supply Chain and Cost Structures: The retail and e-commerce sector often deals with complex supply chain operations and cost struct #Customer Behaviour and Expectations: Today's consumers are more informed and price-sensitive than ever before. Their buying behaviour can c #including promotions #discounts #and market trends. Retailers must be agile in responding to these changes.#Competitor Pricing Strategies: Keeping a constant eye on competitor pricing is crucial. Businesses need to respond promptly to pricing move #Download the sample report of Market Forecast: B2B Price Optimization and Management Software

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bestoftheweb2021 · 3 years

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How to optimise facebook ads ?

There are several articles available on Facebook ad optimization.

The majority of them, on the other hand, are full of simple tips like “Install a Facebook Pixel” or “Build a Facebook audience.”

Isn’t that not really helpful?

In this post, we’ll show you one of the best ways to save time and improve the ROI of your online ads, allowing you to concentrate on the big picture.

As a result of optimization, the campaign’s results will increase. It distinguishes the winning unicorn ad campaigns from the rest.

You must optimize your campaigns both before and after they are published on Facebook if you want to meet all of your target audience members and outperform your competition.

The good news is that it will be well worth your time and effort.

Using a free online optimization platform for Facebook, Google, and Microsoft advertising is the answer.

This tool is Adzooma, Adzooma is an AI-powered, intelligent platform for managing, optimizing, and automating online ads. You can make progress in just a few clicks by analyzing over 240 indicators from your Google, Facebook, and Microsoft campaigns. It’s a useful piece of software because it has everything you’ll need to stay on top of your campaigns while still pushing them forward.

Why use Adzooma ?

Adzooma’s program is designed to help you gain a competitive advantage by allowing you to:

Adopting best practices will help you save money.

Automate time-consuming tasks to save time.

Personalized optimizations will help you improve your results.

With white-label, one-click reports, you can prioritize important data.

This means you’ll have more time to focus on strategy and research, which is something we’d like to cross off our to-do list. It’s not particularly satisfying to keep churning out the same reports, especially when a computer can do it for you. However, with all of the debate about artificial intelligence in the press, it can be difficult to realize its full potential on a smaller scale.

Why Your Facebook Ads Aren’t Working ?

Most people believe that Facebook advertising functions similarly to other forms of advertising: you have a product or service, you place an ad, and sales result.

However, that isn’t how Facebook advertising operate.

Facebook is first and foremost a social media website. As a result, people are less likely to use the website in search of advertising. They could use Facebook Marketplace to look for a product if they wanted to.

This normally results in three forms of Facebook ad issues:

You don’t know who you’re trying to reach.

Your perfect customers are still being discovered by Facebook.

Your advertisements aren’t engaging enough to stand out.

When your ads aren’t performing as well as you’d like, one of the three reasons mentioned above is typically to blame.

Let’s get this party started.

How to optimise facebook ads with Adzooma ?

First, create your free account in Adzooma :

after you link your Adzooma account with your Facebook or Google or Microsft ads account :

Now from the top menubar click on =>Opportunities

Adzooma’s ‘Opportunity Engine’ analyzes the data in your ad accounts and suggests ways to boost results.

The recommendations include items like “Pause Underperforming Keywords” and “Generated Shared Negative Keyword List,” which are based on an analysis of over 240 metrics. The engine also tests the tiniest data, such as spelling and grammar errors, which you won’t find in Google.

Opportunities are one-click optimizations that help you boost and protect your campaigns.

ou will check all of your Opportunities right here. If you’re not sure, you can uninstall the Opportunity by clicking the’remove’ button. Once you’re satisfied, click the bottom right-hand ‘Apply All’ button to get all queued Opportunities added to your account.

That’s all there is to it; the improvements have been made. Now you can go about your business as usual, and come back here as new opportunities arise.

This method is also to optimize google and Microsoft ads.

Optimize your ad placement ?

When it comes to Facebook advertisements, the positioning of your ads has a significant effect on the cost of your campaign.

So much so that, according to AdEspresso results, the CPC can vary by as much as 550 percent depending on ad placement.

Sign in to Facebook Ads Manager and use the Breakdown menu to break down your campaigns by Placement to find your best-performing ad placements.

After you’ve identified your best-performing ad placements, refine your campaigns as follows:

Increase the bids on the ad placements that are doing well.

Simply delete an ad placement from your ad set if it fails to meet your standards.

How to Scale Paid Ads Faster With Automation ?

Taking the right behavior at the right time is the secret to growing paid ads on every network. Adzooma ensures this 24 hours a day, 7 days a week by reviewing all of your accounts every 30 minutes and making adjustments based on the rules you’ve developed.

Low CTR rates, a fixed number of clicks or budget spend, low-converting advertising, and more are examples of these cases. Set the law, tell Adzooma what action you want to take, and start the process.

Automatically change budgets to put the top performers first.

Identify growth opportunities without spending hours analyzing data

With personalized warnings, you can take action at the perfect time.

Turn the low-performers into high-performers.

Are you unsure where to begin with automated rules? Adzooma has you covered with a range of ready-to-use Google, Facebook, and Microsoft Ads models.

Industry experts hand-picked each of these models as their go-to rules for setting up and optimizing their campaigns. They’re laws that have stood the test of time and have shown to be effective in campaign optimization.

Furthermore, these rules can be customized. Use these models as a starting point, then customize them to suit your specific needs and campaigns. It’s easy.

On your Google, Facebook, or Microsoft campaigns, Adzooma Automation rules can be run every 30 minutes.

It’s the quickest and most powerful free automation tool available, giving you precise accuracy and control. (You can only run an automatic rule once a day in Google Ads.)

Instead, would you like us to run the rule at a particular time? It’s no problem.

You have a complete influence on how and when rules are executed.

Do you want to be notified every Tuesday morning about your poor performers? It’s not a problem.

Want to make sure your money is put to the best possible use during your busiest periods? You figured it out.

Need to start a campaign at 5 a.m. on the 21st? It’s all set.

Account ‘admin’ is not a good use of your time. That’s why we designed Adzooma to be as simple and user-friendly as possible. So, the next time you need to build a rule, just follow the easy step-by-step setup method to get it up and running in a matter of seconds.

A Single Screen For All Your Campaign Management

One a of the most inconvenient aspects of handling PPC campaigns, in my opinion, is having to switch between different channels. If I have a client who has Google, Facebook, and Microsoft ads going, I have to recall three different logins in order to make three different sets of changes — and that’s before I know which one is on fire and which I should tackle first.

The Adzooma management screen is one of my favorites because it allows me to see it all at once. It’s useful to be able to see a complete rundown of the campaigns and dig down into individual advertising and keywords. You can pause campaigns, adjust budgets, and see all in one place from here. This bird’s-eye view gives you a strong sense of control over all of your campaigns.

#facebook ads optimization 2020 #how to optimise facebook ads 2020 #facebook ads optimization tool #conversion adsfacebook #facebook ads man

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simplemlmsponsoring · 5 years

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New Post has been published on http://simplemlmsponsoring.com/attraction-marketing-formula/internet-marketing/data-science-for-marketers-part-3-predictive-vs-prescriptive-analytics/

Data Science for Marketers (Part 3): Predictive vs Prescriptive Analytics

How much would you like to know what your customers are up to and what kind of nudge they need to convert?

Your past data holds answers to likely future outcomes, and predictive intelligence helps you unlock those. While the concept of advanced forecasting isn’t new – the airline industry has been analysing their flight data for years to minimise late arrivals and optimise routes – it is now starting to reach its full potential in the marketing industry.

So far in this series, we’ve looked at how to get your data ready and descriptive v diagnostic analytics. In this third and final chapter, we explain what exactly you can achieve with a mature big data analytics setup.

What is predictive analytics in marketing?

Predictive analytics transforms all the scattered knowledge you have relating to how and why something happened into models, suggesting future actions. By integrating various techniques including data mining, modeling, machine learning (ML) and artificial intelligence (AI), predictive analytics tools transform the data at hand into focused marketing action.

While descriptive analytics helps us learn more about the past, predictive analytics looks into the future, answering the “What will happen if…” questions.

In marketing, that translates to:

Anticipating consumer behaviors before they happen Optimizing your marketing campaigns around specific factors that are proven to impact sales

Finding the most valuable leads in your CRM and pitching them with offers that will generate the highest conversions

Predictive algorithms tell you about the likelihood of a future outcome with scientific accuracy. Big data is a collection of moving parts that can be smartly mixed and matched to model hundreds of different outcomes (negative and positive) that will guide your decision making.

Use cases of predictive analytics in marketing

Predictive intelligence can be applied to back up all sorts of marketing decisions, depending on your targeted area for improvements.

Higher email marketing ROI

Econsultancy’s 2018 Email Census indicates that 58% of marketers were either using or considering using predictive techniques to improve the content of their emails. Specifically, behavior-based personalization has become the key area where predictive analytics is making the most impact. Intelligent email marketing campaigns tend to generate the highest influenced revenue – $5,1 million.

Source: Predictive Intelligence Benchmark Report by Salesforce

Predictive analytics allows you to build an intimate rapport with individual customers, rather than large segments. By analysing customers’ historic purchases, demographics and behaviour data, algorithms can suggest when to send follow-up and reactivation emails, what content to include, how to re-engage your customers at the most effective cost and what product recommendations and promo offers to dispatch.

Identify lookalike customer audiences

Predictive analytics adds a scientific dimension to determining similar groups of customers and similar segments in new markets. Your sales teams can pinpoint valuable prospects earlier in buyers’ journeys, prioritise the most valuable accounts for expansion and uncover new prospects that most closely resemble existing customers.

Focused content distribution

Determine what types of content generate the most impact for certain leads and prospects. Predictive analytics allows you to optimise and personalise your content distribution so that each prospect receives the optimal message at the right time. Instead of second-guessing what to send to new prospects, the algorithms will indicate how certain copy will impact customers of certain demographics or behavioural backgrounds, and programmatically distribute relevant content to them, leading to higher conversions.

Predict and optimise customer lifetime value

Estimate the likely lifetime value of new customers by benchmarking them against similar prospects in your system. Similarly, you can predict the likelihood of churn for certain customers. Once your system registers the warning signs, your sales team receives a notification and can take proactive action. Or you can programmatically plug the dangling customer into a personalised churn-prevention campaign.

Comprehensive marketing campaign optimisation

Fine-tuned predictive analytics systems can programmatically streamline all your marketing activities; prioritising the best course of action, launching, pausing and adjusting campaigns depending on their performance, continuously optimising your content distribution and directing you towards untapped opportunities. All your decisions will be backed by data and science, not assumptions and guesswork, diminishing the risks and increasing the ROI of all your actions.

Moving forward: prescriptive analytics

Prescriptive analytics is an emerging area of analysis that leverages both existing data and action/feedback data to guide the decision maker towards a desired outcome. Prescriptive analytics is also predictive in nature since it tries to estimate multiple futures based on your actions and advise on the outcomes before you actually make a decision.

Apart from answering the “what will happen if…?” question, prescriptive analytics also tackles the “what should we do to reach the desired outcome?” component. For instance, “What new keywords should we target this month to grow our search traffic by 30% in 3 months?”

The best example of prescriptive analytics in action is Google’s self-driving cars. The algorithms powering them make millions of predictions during each trip, deciding when, how and how fast the car should move to reach the destination – the same way a human driver does.

Advances in AI, computational modeling, machine learning and reinforcement learning (a sub-division of ML) are bringing prescriptive analytics into the marketing realm. Most businesses, however, are yet to embrace prescriptive analytics solutions (or one of their components such as AI) to guide their daily operations.

Image Source

You are more than encouraged to join the progressive AI party as well. The use cases and benefits of prescriptive analytics for marketing will only expand over the next few years.

For sales, prescriptive analytics can help determine the optimal product configurations (premium, high-end, medium and low price offers) by dynamically optimizing service prices depending on customers’ tolerances, preferences and other external factors (e.g. availability, demand). Your teams can know exactly what prospects to call to meet sales targets and what kind of offer to pitch to them.

For marketers, prescriptive analytics can provide a wide-angle view of all marketing activities, help determine the performance of planned campaigns/content type and estimate how different external/internal factors will impact their planned strategies.

Machine learning alone is already experiencing transformational momentum in the marketing realm. And if you want to know where AI and ML are headed in the future and how these technologies can give you a competitive edge today, download our guide for marketers.

What it takes to become a data science-driven organisation

Predictive intelligence generates a 40.38% influence in revenue after 36 months of implementation on average. However, such results assume having a mature predictive analytics culture:

Source: RedEye

Your transformations should start with accumulating and assessing your current data. How much data are we we talking about? Typically, a few thousand records showing both positive and negative outcomes should be sufficient to create marketing, sales or product prediction models.

All of your data sets will have to be stitched together in one major data lake. Additionally, you will want to connect some external data streams to it, if your goal is to deploy advanced marketing campaigns based on seasonality, weather, location and so on.

Finally, once you have a well-organised dataset, you can either:

Plug your data to a predictive analytics tool and fine-tune the models yourself.

In both cases, the quality of your data will be crucial for success. Investment in big data and data analytics can seem steep, but making data-driven decisions makes strong commercial sense as we have illustrated over the course of this three part series.