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Mastering POS Data and Analysis: A Guide for CPG Brands | Retail Velocity

Mastering POS Data and Analysis: A Guide for Brands and Retailers

Consumer packaged goods (CPG) suppliers and manufacturers—whether large, small, or in between—are constantly seeking ways to gain an edge over competitors, better understand consumer behavior, and optimize operations. One indispensable tool in achieving these goals is retail point of sale (POS) data.

Each swipe of a credit or debit card or entry of a cash transaction is a treasure trove of data. This data, when collected efficiently and analyzed effectively, can reveal patterns and insights into shopper behavior, sales trends, inventory management, and even employee performance.

Despite its importance, many CPG personnel may find the concept of POS data daunting. In this guide, we'll break down the fundamentals of retail POS data, its significance, and how CPGs can transform raw transaction data into actionable insights and harness its power to drive success.

 

What is POS Data?

Every POS system collects large volumes of raw transactional data after the customer has paid. However, this data is not only payment data—i.e., it includes more than the transaction amount and time of purchase. At its core, POS data refers to the information collected during a customer sales transaction, whether that purchase is at a physical or brick-and-mortar retail location, online, or on a mobile application.

This data encompasses a wide range of information and provides richer detail that CPGs and retailers can leverage to drive better decision-making related to trade promotions, new product launches, pricing, product assortments, supply chain, retail execution, and much more.

 

Types of POS Data

Because POS data provides a comprehensive view of numerous business areas, it serves as a cornerstone for understanding not only what your consumers and shoppers want and buy but also how they shop and what drives their purchasing decisions.

To gain these valuable insights, CPGs and retailers collect and analyze several types of POS data.

Sales Data (Transaction Data, Basket Data)

Transaction data forms the core of POS data. This includes information about individual transactions, such as the items purchased, their prices, quantities, discounts applied, payment type, and the total amount paid.

Why Is Sales Data Useful?

Sales data can help you run a more profitable, efficient business that keeps both consumers and retailers happy. Possessing and understanding comprehensive transactional data helps you know which items are flying off the shelves and which ones are languishing on the shelves or in a warehouse that might need to be put on promotion. Tracking sales trends over time, you can identify and, more importantly, understand peak sales periods or seasonal patterns, top-performing and underperforming products, and the effectiveness of your marketing campaigns and in-store execution efforts.

By analyzing transaction data, manufacturers can identify popular products, trends, and demand patterns, enabling them to adjust production levels, develop new products, or modify existing ones to better meet consumer needs. Sales data can also improve your inventory management, enabling you to replenish top-selling items before they are out of stock and avoid overstocking products that aren’t selling well.

Sales data can also provide insights into purchase intent. For example, was the product purchased part of a larger order of multiple items, or was it a single purchase? It also provides visibility into whether an item is typically purchased using cash or a card.

Product Data

Product data, as you may have guessed, includes information about each product sold during a transaction. This information includes product names, descriptions, SKUs, categories, and possibly attributes like size, color, or style.

Why Is Product Data Useful?

Product data allows manufacturers to understand the performance of their products in the market. By analyzing product data, manufacturers can discover what products customers buy, how much of the product shoppers typically purchase at one time, how much they spend on the product, and what products are bought together. This information can inform decisions about product development (new products, improvements, or modifications), marketing strategies, and inventory management.

Also, armed with this product information and combining it with cost information, CPG sales and finance teams can understand how successful a product is over time, which ones have the highest profit margins, and how much revenue each product generates.

Inventory Data

Inventory data provides details about the retail stock levels of each product, including current quantities on hand, which products you need to replenish, reorder points, and any stock movements (e.g., sales, restocks, returns, or exchanges) and where the product is located.

Why Is Inventory Data Useful?

Inventory is the backbone of retail and helps CPG manufacturers manage their supply chain effectively. By monitoring inventory levels and movements, and by receiving alerts for low inventory, manufacturers can ensure they have sufficient stock to meet consumer demand without overstocking or understocking. This helps optimize production schedules, minimize storage costs, and reduce the risk of stockouts or excess inventory.

For retailers, if they are selling online and through a physical store, it is even more critical they ensure inventory levels are accurate so they can make informed decisions about ordering and stock management.

Customer Data

Simply put, customer data includes information about who is buying your products. This may include customer information, such as names, email addresses, phone numbers, loyalty program IDs, demographic information, or detailed purchasing histories. Some businesses may collect this data to personalize marketing or track customer behavior.

Why Is Customer Data Useful?

With individual customer data in hand, you can learn how long someone has been a customer, what products they bought, how much they bought, how often they bought your product (and from which retailers), how much they have spent, where their brand loyalty lies, typical basket size, time of purchase, purchase type, and more.

This level of detail, when analyzed properly, is useful for creating targeting marketing campaigns and promotions, personalizing shopping experiences, and fostering customer loyalty and brand loyalty.

Payment Data

Payment data includes information about the payment method used in each transaction, such as credit/debit card, cash, or digital wallet. This data may also include details like card type, last four digits of the card number, and authorization codes.

Why Is Payment Data Useful?

Because payment data provides visibility into how customers prefer to pay, it can help track sales performance and payment trends. Understanding payment trends can help optimize checkout processes, reduce transaction times, and enhance customer satisfaction. Also, by analyzing payment data, you can identify popular payment methods and detect fraud or payment issues.

Time and Date Data

Time and date data equates to timestamps indicating when a purchase was made.

Why Are Time and Date Data Useful?

Time and date data provides a historical record that you can refer to year-over-year and it can be useful for analyzing sales patterns and seasonality trends, identifying peak hours, and scheduling staffing accordingly. By understanding when and how sales fluctuate over time, manufacturers can adjust production schedules, plan trade promotions, and allocate resources more effectively. This can help optimize inventory levels, reduce wastage, and maximize sales opportunities.

Location Data

Location data tells you where a purchase was made. You can view this data at a country level, but you can also view purchases by region, city, zip code, and individual retail store. You can even obtain location data by individual POS terminals to see what purchases were made at an employee-manned checkout or a self-service checkout, or which department the purchase was made.

Why Is Location Data Useful?

Location data helps manufacturers understand how your sales perform by location and it helps them understand regional variations in sales and consumer preferences. By analyzing location data, manufacturers can identify geographic markets with high demand, tailor their marketing strategies to local preferences, and optimize distribution channels. This can lead to increased market penetration, improved customer satisfaction, and higher sales.

At a customer-store level, you can also use this data to target marketing efforts for areas of the store that customers might not usually visit or to promote products in a certain area of the store.

Promotion Data

This data includes information about any promotions or discounts applied to transactions, including the type of promotion, its duration, and its impact on sales.

Why Is Promotion Data Useful?

Promotion data helps manufacturers evaluate the effectiveness of marketing campaigns and promotional activities in-store or online. It provides insight into whether a customer is using a promotion and which one(s) they have used. By analyzing promotion data, brands can measure the impact of discounts, coupons, or special offers on sales, customer acquisition, and brand awareness. This can inform future marketing strategies, optimize promotional budgets, and maximize return on investment.

Returns, Exchanges, and Refunds Data

This includes information about product returns, exchanges, and refunds, including reasons for return, refund amounts, and any associated fees.

Tracking returns and refunds data is paramount as it unveils valuable insights into customer preferences and product performance. By analyzing these activities, CPGs can identify trends such as common reasons for returns, product dissatisfaction, or quality issues.

Why Are Returns, Exchanges, and Refunds Data Useful?

Returns and refunds data provides insights into product performance, product quality, customer preferences and satisfaction, and potential issues with products. By analyzing returns, exchanges, and refunds data, manufacturers can identify product defects, customer complaints, or areas for improvement. This can help enhance product quality, reduce returns, and increase brand loyalty, and it leads to strategic decisions such as removing certain products from shelves or online stores or adjusting marketing and promotional strategies.

 

WHY SHOULD you ANALYZE POS DATA?

Today’s point of sale systems collect enormous amounts of data, data that can help CPG companies better understand their products, consumers, and even their retailer partners.

With key data such as sales transactions, inventory levels, customer behavior and interactions, and payment details, brands can extract meaning from every purchase and gain valuable insights into various aspects of their business’s operations—that is, if they can collect it, analyze it, and interpret it efficiently and effectively.

Through a modern retail data platform such as Retail Velocity’s VELOCITY® solution, which can automatically ingest, clean, and harmonize daily store- and item-level POS and inventory data and other data from any retailer or retail data source (in any format), CPGs can transform large volumes of disparate data into a wealth of actionable insights that eliminate guesswork and intuition-based decision-making and instead drive strategic, data-driven business decisions.

Here are several reason why comprehensive, trustworthy POS data and precise, reliable POS analytics are crucial to facilitating profitable growth for CPGs and their retailer partners:

1. Understanding Customer and Consumer Behavior and Personalizing the Customer Experience

POS data plays a pivotal role in improving customer experiences and increasing brand loyalty and sales. By analyzing customer buying patterns, trends, behaviors, and preferences, companies can personalize the shopping experience and tailor product offerings and marketing strategies to meet the specific needs and desires of consumers through new products, product modifications, and targeted promotions and discounts.

2. Optimizing Inventory Management

POS data provides real-time visibility into inventory levels and sales performance. With this information as to which products are in demand and which are not, businesses can streamline their inventory management processes, reduce stockouts, minimize excess inventory, and improve overall efficiency.

By monitoring stock levels, CPGs and retailers can identify fast-moving items and optimize store replenishment practices to reduce waste, ensure products are consistently available on the shelf, and maximize sales opportunities.

3. Enhancing Decision-Making

Data-driven decision-making based on solid, actionable data is key to success in today's competitive retail landscape. Reliable POS and inventory data empowers businesses to make informed decisions regarding pricing strategies, trade promotions, marketing campaigns, product assortment, product placement, and resource allocation.

Overall, reliable POS analytics allow CPGs to plan, execute, and measure with confidence, knowing their decisions are backed by accurate data and real, trustworthy insights. When a CPG company can identify broader buying trends and patterns, understand shifts in the market and changes in consumer behavior, and identify which marketing efforts are yielding positive results, they can adapt more quickly and appropriately, seize new sales and growth opportunities, and gain and maintain a competitive edge.

 

Best Practices for Effective POS Data Collection and Analysis

Achieving effective POS data analysis and insights generation involves employing best practices related to efficient retail data collection and management and the utilization of the right solutions, processes, and industry and data expertise.

Centralized Data

Unifying and centralizing data from retailers and disparate data sources is a key element for CPGs, but that data also needs to be easily accessible and shareable. If necessary, the data also needs to be seamlessly fed into a manufacturer's data warehouse(s), data lakes, or other applications or systems such as trade promotions, demand planning, and logistics, as numerous departments depend on that data to make strategic decisions that impact sales, marketing, supply chain operations, revenue, and profitability. This unified approach and process allows for more cohesive, comprehensive, and accurate retail data analysis for individual retailers and across retailers.

Automated Solutions

Implementing and utilizing intuitive software solutions and tools should also be part of your best practices. It’s essential for brands to employ an automated retail data collection and analytics platform, such as VELOCITY®, that is cloud-based, user-friendly, and enables quick and easy access to reports, interactive dashboards, data visualizations, and meaningful insights. This holds the most significance for non-technical business users who need the right information at the right time and who don’t want or need to spend countless hours wrangling data or getting trained in data analysis. The software should also be able to collect, cleanse, and harmonize data from any data source whether it be internal or external.  

Daily POS and Inventory Data

Acquiring and processing daily POS and inventory data at an SKU and store level is critical for generating and leveraging timely and reliable insights. The VELOCITY® platform can provide yesterday’s data today, enabling both CPG companies and retailer partners to gain the granular visibility they need to adapt quickly to changes in consumer demand and market conditions, recognize and maximize sales opportunities, and streamline supply chain and business operations.

 

let data be your guide

Point of sale data is a powerful tool that, when analyzed and interpreted effectively with the right software solution, can help brands identify trends, patterns, and correlations that may not be immediately apparent. This enhanced visibility provides invaluable insights that can drive success for brands of all types and sizes. And the more efficient your retail POS and inventory data collection and the more comprehensive and accurate your retail data, the richer those insights will be.

The retail landscape is constantly evolving, and so should your sales, marketing, and supply chain strategies. With deeper insights, CPG companies will be able to better inform their business strategies and collaborate decision-making processes internally and with their retailer partners. Also, by understanding the fundamentals of POS data, its significance, and how to effectively harness its power, companies can gain a competitive edge, enhance customer experiences, and propel sustainable growth.

Embrace POS data as a strategic asset, and whether it's for adjusting pricing strategies, launching targeted marketing campaigns, or optimizing inventory levels, let that data be your guide.

 

Helping brands easily acquire and transform POS data into a valuable asset is nothing new to Retail Velocity—we've been doing it for 30 years. If you'd like to learn more about how we can help you leverage that data to drive profitable growth through proven, automated solutions, schedule a consultation.

 

 

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