A Guide to Point of Sale (POS) Analytics for CPG Brands

If you're not actively collecting and analyzing data from your retail touchpoints, you're missing out on a huge opportunity to capitalize on customer behavior.

POS (Point-of-Sale) systems collect a boatload of information on product inventory, sales efforts, customer demographics, and staff performance — all of which is just waiting to be collected by you from your retail partners.

But it's not enough just to collect all that data. You also need the proper tools to process and analyze it without the manual overhead. AI/BI tools can help you do just that if you know how to use them.

In this guide to POS analytics for CPG brands, we'll cover everything you need to know to properly collect, store, process, and analyze data from point-of-sale machines and retail storefronts. Let's go!

What Is POS Analytics?

POS analytics is the process of collecting, organizing and interpreting data coming from point-of-sale systems. This data can provide insight into sales patterns, customer behavior, product availability, and staff performance.

Why Is POS Data Important?

POS data is incredibly valuable for CPG brands because it offers deep insights into customer behavior, allowing you to see what products are selling, how much inventory is needed, which promotions are driving sales, and more. Here are a few ways you could be leveraging POS data for your CPG company:

• Strategically Positioning Products: POS data can be used to identify which products need more promotion or shelf space and which products are not performing as well as expected.
• Determining Promotional Effectiveness: Leveraging POS data helps brands measure the effectiveness of promotions, coupons, and loyalty programs so they know which ones are working and which ones should be discontinued.
• Identifying New Opportunities: By analyzing POS data, brands can identify new growth opportunities, such as expanding into new markets or creating new partnerships.
• Creating Targeted Marketing Campaigns: POS data also helps brands understand who their customers are and what they want. This can help them create more targeted and personalized marketing strategies.

Who Owns POS Data?

Generally, POS data is owned by the retailers, since they are the ones who are responsible for collecting and storing it.

However, the brand can access this data if they have a data-sharing agreement with the retailer. This is a standard part of any retail agreement, so chances are that you already have the right to access the data if you so choose. But if it's not, you can easily reach out to your retail partner to institute a proper data-sharing agreement.

How to Collect POS Data from Retailers

Most retailers use off-the-shelf POS solutions like Square, Revel, and Clover. These systems typically come with a cloud-based portal as well as a data export feature — so that brands can easily retrieve the data they need.

Apart from direct retail, CPG brands also have access to syndicate data aggregated by providers like SPINS, IRI, and Nielsen — these portals collect data from a variety of touchpoints to paint a big picture of the entire industry.

If you're looking for a unified portal to collect, store, and analyze point-of-sale data, Vividly offers seamless integration with the most popular data syndicators (SPINS, Nielsen, etc.) as well as retail-specific solutions like Walmart and Target.

How to Analyze POS Data

Once you have the data you need, analyze it to extract valuable insights.

Start by cleaning and organizing the data. If you're aggregating your data from different sources, normalize it to make sure it is all in a consistent format.

Next, create visuals to better understand the data. Charts, graphs, heatmaps, and other visuals can help you spot patterns, outliers, and trends in the data.

Then, utilizing statistical analysis techniques such as mean, median, correlation, and regression analysis, can help you understand the relationships between different pieces of data and predict future trends.

Finally, look for actionable insights. For example, you might ask yourself: “Which customers are buying a certain product?” or “Which stores are selling the most of a certain product?”

Of course, when dealing with large amounts of point-of-sale data from a variety of sources, it doesn't make sense to go through it all manually. Instead, you can automate the process with the right tools and use data science to gain more insights by digging deep into patterns and correlations. That is what we specialize in at Vividly, but more on that later!

Things to Look for When Analyzing POS Data

POS data usually falls into one of five main categories: inventory data, sales data, product data, customer data, and staff data. There's an unending list of stats and metrics to keep track of, but most businesses should focus on a select few. Here are the 10 most common KPIs that you should look for when analyzing CPG point-of-sale data:

1. Sales Volume: Measures the number of products sold, and can give you an indication of how well your products are performing.
2. Product Mix: Measures the ratio of different products sold, giving you an indication of what products are selling more than others.
3. Customer Demographics: Measures the age, gender, and location of your customers, which can help you tailor your marketing efforts to the most profitable demographic.
4. New Customer Acquisition: Measures the number of new customers acquired over a certain period of time.
5. Average Sale Value: Measures the average amount of money each customer spends during a single transaction.
6. Average Order Value: Metric measures the average amount of money each customer spends during a single order, which can be useful for determining how to optimize product pricing and marketing efforts.
7. Conversion Rate: Measures the number of customers who go from store to checkout, giving you an indication of how successful your sales process is.
8. Staff Performance: Measures the productivity and efficiency of your staff, which can help you optimize staffing and incentive plans.
9. Inventory Levels: Measures the amount of stock on hand at a specific point in time, which can help you adjust orders to meet customer demand.
10. Customer Retention Rate: Measures the rate at which customers come back and make repeat purchases from each retailer. Knowing this can help you optimize loyalty programs and ensure customer satisfaction.

Using Data Science to Improve POS Analysis

POS data is not meant to be used as-is. Today, CPG brands have access to a host of machine learning and artificial intelligence tools to identify patterns and extract insights from point-of-sale data sets. Whether or not you choose to leverage these technologies will define the effectiveness of your trade promotion campaigns.

• Here are a few ways top brands are using POS data to anticipate customer behavior and forecast promotional effectiveness in the CPG space:
• Utilizing predictive analytics to anticipate customer behavior and plan promotions according to seasonal trends.
• Using AI/ML algorithms to generate demand forecasting models to anticipate customer demand and adjust inventory accordingly.
• Using natural language processing (NLP) to uncover customer insights from POS reviews.
• Utilizing customer segmentation to create accurate customer profiles and behavioral insights.
• Using sentiment analysis to gauge customer satisfaction and loyalty.
• Implementing recommendations algorithms to create personalized product recommendations for each customer.
• Utilizing deep learning models to optimize product pricing based on customer demand and availability.
• Analyzing product correlations to identify which products are purchased together and create new product combinations.

How Vividly Integrates With POS Systems to Automatically Pull and Analyze Valuable Data

At Vividly, we understand how difficult it can be to make strategic decisions about trade without the right tools and data to power your decision-making. That's why we built a platform that pulls granular point-of-sale data from different sources, including data syndicators and retail platforms, to create a single source of truth for all your trade efforts.

With Vividly, you now have real-time analytics relating to all aspects of your trade effort. Once you have enough data, you can visualize it, analyze it, and use it to create detailed forecasts for future initiatives — all from a single unified dashboard.

Want to learn more about the trade promotion management platform that's been called a "no-brainer" and a "home run" by brands like Perfect Snacks, Bulletproof, and Lesser Evil? Request a demo today!