Last Updated On October 15, 2020 / Written By Chloe Henderson

6 Types of Point of Sale Data and How to Use Them

Point-of-sale data monitors transactions and shopper activity to generate reports on performance and revenue. This allows retailers to customize their services around customer preferences.

Retailers are continuously trying to find new ways to appeal to customers to drive traffic and interest. This can be difficult without a tool to facilitate data tracking, requiring management to rely on manual calculations and data collection.

With point-of-sale data, businesses can view metrics on transactions and customer interactions to monitor the performance of employees and campaigns. Through extensive data collection, retailers can also track various internal operations, such as inventory management, refunds, and trends.

What is Point-of-Sale Data?

Point-of-sale (POS) data comes in four primary forms, each defined by their source and objective.

  • Retailer direct data is the simplest form of POS data, derived from a single retailer chain.
  • Retailer direct shopper data is information collected from customers, such as payment methods, via loyalty programs at the POS terminals.
  • Syndicated store data provides broader information on an entire market, such as sales metrics from multiple retailers.
  • Syndicated shopper data looks at customer behavior across multiple brands through household panel data, a source for retailers to monitor shopping trends and preferences.

POS data gives companies insight into market trends and consumer behavior, enabling them to make data-based decisions on advertisements, product launches, and other tasks.

Businesses looking to measure the performance of items or targeted marketing promotions should focus on store-level data, including syndicated or retailer direct data, since campaigns are specific to each location. However, management can monitor shopper trends to determine the effect of larger promotions, such as social media ads.

6 Types of Point-of-Sale Data

While there are four main sources of POS data, there are several other sources retailers can collect information from. Depending on the company's area of focus, they can gather information on-

1. Inventory

Advanced POS software can integrate with back-end inventory software to accurately track stock levels with every transaction, regardless if a purchase is made in-store or online. This functionality updates each integrated system with every automated cycle count, reorder, and data input, ensuring retailers stop selling products that are out of stock.

With inventory control, businesses can use POS data to pull information on a product's location, variance, sales, and profit margin. With quick access to this data, retailers can answer shoppers' questions, place orders, and locate items, providing enhanced customer service.

For example, if a customer wants a particular clothing item in a different size, an employee can use the POS system to determine if the product is available or needs to be shipped from another site.

2. Customer Profiles

With every transaction, the POS system collects valuable customer information to add to their profile. Whether the purchase is made in-person or through the online store, the shopper's name, address, phone number, payment method, and purchase history are gathered and stored. Customer data is optimized when consumers enroll in a rewards program, allowing the system to track their preferences.

Customer information enables retailers to launch email marketing campaigns to promote product lines, give personalized item recommendations, and offer exclusive discounts. This offers shoppers customized experiences and provides business owners with the opportunity to capitalize on demand trends.

3. Purchase History

By tracking purchase histories, management can reference specific customers and timeframes to determine pricing, shopper information, and product demand. Modern POS systems can generate detailed reports on these datasets, allowing management to view the information by date, product, and customer to detect various patterns.

Information on purchase histories takes the guesswork out of developing impactful marketing strategies and target promotions. With proper utilization, businesses can use this data to improve product turnover rates, increase sales, generate more revenue, and personalize the customer experience.

4. Staff Sales

Most POS solutions require employees to sign in using a unique login to access data or complete a transaction. This feature allows management to monitor each staff member's activity, such as average sales, customer interactions, and which products they are best at selling.

Monitoring each employee's productivity and performance allows management to provide extra training, incentives, and bonus where appropriate to boost sales and reward top-performers.

5. Sales Trends

A POS system's main priority is to finalize and track sales throughout a retailer's sales channels. This basic function alone generates valuable metrics on product performance, payment processing, demand, and revenue.

Continuously reviewing sales reports enables retailers to detect emerging trends. By identifying these patterns, companies can optimize their operations to improve performance.

For example, a retailer can extend their hours during their busy seasons to capitalize on the increased customer demand, then limit hours once traffic slows to save on operational costs.

6. Returns, Refunds, and Exchanges

Although product returns are not ideal for businesses, every retailer experiences returns, refunds, and exchanges at some point, especially following holidays. However, POS data uncovers the reasons for an increase in returns or refunds, enabling management to promptly implement a solution.

For example, if reports show a particular product line is receiving an influx of returns, management could find the items to be defective. Businesses can decide if the product should be dropped or contact the provider to determine if there is a recall.

The POS system also notes how customers want to receive their refunds, whether in cash or for store credit. This makes it easier to detect returner fraud and view how returns are affecting the bottom line.

Companies that utilize their POS data gain insights into several internal operations, enabling them to enhance their overall performance.