What is POS Data?
Point-of-sale (POS) data is a collection of data points gathered from customers during transactions. Every time a consumer makes a purchase, businesses can review their history to determine spending habits, areas of interest, and dislikes. This enables companies to improve their marketing strategies and product development.
When the POS system collects information during transactions, it is called passive data, because the customer doesn't initiate it. In other words, the system is gathering the information, not the shopper. However, online retailers can gather active data, where users actively share their information to engage in a promotion. Either way, businesses can use customer data to improve overall decision-making.
Companies can also look at POS data on a micro and macro scale. On the smaller end of the spectrum, retailers collect POS data at the payment terminal. Depending on the business's hardware, employees can also collect POS data via scanners, portable payment devices, and other transaction points. On the macro side, companies can gather information from groups of retailers and even city-wide data. Combining POS data from multiple channels, from in-store to online, enables companies to broaden the scope of their insights.
Why is POS Data Important?
POS data is very important as it is the initial point where businesses can collect information. While it is the origin of data gathering, POS data doesn't only impact front-end services. POS data greatly impacts inventory management behind the scenes and enables companies to optimize their stock levels. This makes sense, as retailers can't improve their inventory if they don't understand what customers are buying.
In addition to inventory, POS data provides the key to customer service and impactful marketing. Based on customer information, stores can determine how they can attract new shoppers to increase foot traffic and word-of-mouth advertisement. It is up to each business to properly gather and capitalize on this wealth of information.
6 Ways to Utilize POS Data to Boost Sales
While the power of POS data is virtually unlimited, most businesses use it to optimize various front and back-end operations.
Important-: Businesses can compile all sales information to define trends for each product, store, customer profile, and employee.
1. Optimize Inventory
Unfortunately, many small businesses do not track their inventory, resulting in costly discrepancies. A 2017 study found that inventory shrinkage cost companies approximately $100 billion worldwide. However, retailers can avoid these unnecessary expenses by utilizing their POS data.
Advanced POS software updates stock levels with each transaction so inventory managers can place reorders appropriately. Otherwise, companies risk under and overordering products, which can significantly impact profits. Not ordering enough items can result in stockouts, forcing customers to shop elsewhere.
On the other hand, overordering products increases the likelihood of deadstock, which takes up valuable storage space. By utilizing POS data, companies can actively monitor inventory counts to optimize levels, transfer products, manage returns, and automate reorders.
2. Gain Customer Insights
There is so much to learn from customers that could help business improve their marketing, product development, and sales strategies.
- Product Affinity refers to the pattern in which customers buy items together. This metric enables businesses to successfully bundle and recommend different products.
- Order History enables companies to monitor customer preferences to improve product recommendations and customized offers.
- Product Sales identify sales by each product line so retailers can further analyze trends.
- Returns, Refunds, and Exchanges often point to a product malfunction, inefficiency, or deformity. Retailers that track this metric can investigate highly returned items.
3. Improve Employee Staffing
POS systems typically require employees to login in with their verified username and password so they can track their activity. This not only improves employee accountability but also allows managers to track employee performance. Supervisors can determine their top and bottom performers based on sales and customer feedback. This way, top performers can receive recognition or rewards, and lagging employees can get more training.
Employee performance also helps improve staff scheduling during slow and busy seasons. Retailers often experience inflated staffing costs when they overstaff certain hours. However, understaffing can result in unsatisfied customers from lack of support. Therefore, businesses should use POS data to optimize their staff schedules.
4. Create Customer Profiles
Whether a customer makes a purchase online or in-store, the business has the opportunity to extract critical information, including-
- Phone number
- Email address
- Purchase history
- Store location
Companies can combine this information to find common variables and build customer profiles. These profiles, also known as buyer personas, enables marketers to launch different targeted promotions to each customer group.
5. Forecast Sales Trends
The primary information that POS data tracks is sales. Businesses can compile all sales information to define trends for each product, store, customer profile, and employee. This enables retailers to forecast future market trends based on historical information to optimize various operations, including.
- Stock levels
- Employee management
- Product placement
Sales trends also outline a store's slow and peak hours, days, months, and seasons. Owners can use this information to optimize their hours of operation to drive sales.
6. Manage Returns, Refunds, and Exchanges
While this is not ideal, every business experiences product returns, refunds, and exchanges. This information provides critical insight into customer satisfaction and product functionality. Collecting return data allows retailers to discover the most common returned item and investigate it further.
If a company experiences inflated refunds, they should note the preferred refund method. If customers commonly ask for cash, this could be a sign of return fraud, which can significantly impact profits. Companies may also find that customers exchange for another product, in which case, product developers can note the preferred features.