POS Data Analysis for CPGs

POS data analysis is an integral tool for CPGs that sell their products in retail, offering invaluable insights into the performance of their products, customers' buying habits, and competitor activities. 

In this blog post, we'll cover everything you need to know about POS data analysis, including its definition, types, and use cases. With this information, you'll be well-equipped to use this powerful tool to grow your business and make more informed decisions to optimize your retail strategy.

POS data analysis for CPGs

POS data refers to Point-of-Sale data, which tracks product sales at check-out of a retail or e-commerce store. Retailers will aggregate their POS data across store locations, then share it with their suppliers to give them a better understanding of how their products are performing. By tracking and analyzing this information, brands can make more informed decisions on how to allocate resources and increase sales.

For CPGs, POS data provides valuable insights into product' performance by product, store location, and time period. This information allows companies to make informed decisions about which products to stock in stores, which stores and retailers are the best fit for their products, and how much advertising should be allocated for each product. Additionally, POS data allows CPGs to identify trends in sales over a period of time and understand how promotions, discounts, and other trade spend affects performance. Ultimately, by leveraging POS data, CPG brands can increase sales success and grow their market share in the competitive environment of retail and e-commerce.

Types of POS data 

There are three main categories of POS data: sales and product, inventory, and e-commerce data. Each type offers unique advantages that can be used to inform your business decisions and strategies. 

1. Sales and product data

Sales data provides a record of what items have been purchased at the retail register and when, including item, quantity, and price. Product data includes information on an item's pricing, promotions, and size. This information can be used to track the sales performance of individual products, analyze customer purchase behavior, identify buying trends, and understand category performance. For example, a CPG brand could use sales data to determine which SKUs are popular with certain demographics and adjust their offerings accordingly, or understand how seasonality, holidays, and other events impact sales trends for a particular product.

2. Inventory data

Inventory data gives brands an overview of their stock levels for each item. CPGs can use inventory data to monitor supply chain performance, ensure all retail locations are adequately supplied, spot excess or aging inventory, and adjust product distribution as needed.

3. E-commerce data

E-commerce data is generated from online sales platforms and provides a record of online purchases. This information includes details such as delivery times, payment methods, and returns. E-commerce data can be used to measure channel performance, track customer loyalty, and monitor consumer sentiment. It can also help brands identify areas for improvement.

A CPG brand could use sales data to determine which SKUs are popular with certain demographics and adjust their offerings accordingly, or understand how seasonality, holidays, and other events impact sales trends for a particular product.

Challenges associated with POS data analysis for CPGs 

Consumer goods companies face several challenges when it comes to analyzing point-of-sale (POS) data. To unlock the full value of this data, CPGs need to first understand these challenges and how to best address them.

Inconsistencies in retailer data

The most common challenge is a lack of consistency in the data provided from retailer to retailer. CPGs often supply products to multiple retailers, and each has its own method of data collection and storage, different reporting periods, units, definitions, and more. This can lead to discrepancies in the data being collected and analyzed, making it challenging to identify high-level trends or draw meaningful insights. 

Inaccuracy of POS Data

Another issue CPGs may encounter is the inaccuracy of the POS data. POS data is only as good as the information that is collected at the time of purchase, which means CPGs rely on retailers to accurately capture customer information and product details. If this data is not accurate, then any analysis of the data will be unreliable. 

Data quality and reliability

CPGs need their POS data to be comprehensive, timely, and reliable — and when it isn’t, it impacts their ability to make informed decisions. One challenge is getting a holistic picture across retailers, given that data is spread out across individual retailer portals, which can be time-consuming and manual to extract data from. Vendor portals also undergo outages or version updates that can disrupt a brand’s ability to access their data. And finally, reporting from retailers needs to be frequent enough to help suppliers refine their operations in near-real time, but reporting cadence varies by retailer.

Chargebacks and void transactions

CPGs must also carefully track chargebacks and deductions in their POS data. The many types of chargebacks and deductions can be difficult to understand and categorize, and often come in via PDF reports. CPGs need to pay close attention in order to avoid overspending or financial losses due to erroneous charges.

Making the data actionable

Finally, it's crucial for CPGs to have processes in place that make POS data actionable. This means they must take steps to turn the insights gained from their analysis into tangible solutions that can help improve sales and profits. By identifying key trends, CPGs can make informed decisions about pricing, product placement, marketing, and more. 

With the right tools and processes in place, POS data can be a powerful asset for CPGs looking to get ahead in today's competitive retail landscape.

Making POS data actionable: Tips and best practices

In order to make use of POS data and extract meaningful insights, CPG brands need to take certain steps to make their data as useful and actionable as possible. 

Getting access to the right data

The first step is getting access to the POS data you need. Most commonly, CPGs will need to access retail portals, built and maintained by each retailer, to get this data. The reports will vary in data granularity and frequency depending on the retailer, and sometimes require a paid subscription.

Once access to the POS data is obtained, CPGs have to export and consolidate the data. This can be done manually or through automation. 

Normalization and harmonization

The next step is to make the data clean, reliable, and usable for analysis. This is done by normalizing and harmonizing data into a standard format, which makes it easier to query and analyze. 

Analyzing of the POS Data

Once your data is correctly formatted, the next step is to create dashboards or analyses depending on the business needs. This could include inventory forecasting, customer segmentation, or sales trend analysis. All of these help brands identify patterns and get a better understanding of how their products are performing in the market. 

As a best practice, brands should look for ways to analyze their data as close to real-time as possible. This allows them to gain valuable insights quickly so they can respond to changes in the market and adjust their strategies accordingly. 

With the right analytics tools and strategies in place, brands can easily extract insights from their data and make informed decisions about their business.

Real-world applications of POS data analysis

The use cases of POS data analysis for CPGs are vast, ranging from sales analysis to promotion evaluation. Here are some of the most common use cases:

1. Sales analysis: As mentioned above, CPGs can use POS data to gain deeper insights into their customers' shopping behavior and identify trends in product performance in the market. This helps brands optimize their pricing, product placement, merchandising strategies, inventory allocation, and more.

2. Distribution growth and retention: POS data can also be used to monitor the growth in distribution of products across regions and retailers. They can also monitor the health of those accounts, and be proactive in driving performance or prompting re-orders for specific store locations.

3. Sales and demand planning: With POS data, CPGs can capture a clear picture of sales trends, enabling them to conduct forecasting and demand planning. Through this process, CPGs can project future growth and align sales and operational teams around a shared vision to ensure they’ll be able to meet consumer demand.

4. Line review: POS data analysis can also be used to prepare for a line review, which involves analyzing the performance of your products and presenting those insights in an annual buyer meeting. This helps brands succeed in line reviews, which can lead to increased orders, product expansion, or improved placement with retailers.

5. Chargebacks and deductions: CPGs can use POS data to better track and understand deductions and chargebacks, whether those are for trade spend, penalties, or other fees. This helps brands manage costs, optimize trade spend, and protect profitability.

6. Retailer and distributor void detection: By analyzing POS data, CPGs can detect when voids have occurred, making sure to resolve any out-of-stocks or other in-store issues and get products back on the shelf. 

7. Promotion evaluation: POS data can also be used to track the effectiveness of promotions, including whether customers are engaging with discounts or sales incentives. This helps brands optimize their promotional strategies to drive customer loyalty and increase sales.

8. Product innovation: CPGs can use POS data to understand the performance of their existing products and services, and in some cases competitor or category-level performance. This helps brands identify areas to innovate and offer new products or flavors.

Final thoughts

POS data analysis is an invaluable tool for CPGs, helping them gain valuable insights into their customers' shopping behavior to inform every aspect of their business. With the right analytics tools and strategies, CPGs can get the most out of their POS data and set themselves up for success.

Crisp is dedicated to helping brands make the most of their POS data. Crisp’s open-data platform automatically ingests, harmonizes, and analyzes data from 40+ retailers and distributors to help brands access business-critical insights.