Even the most “bare bones” point of sale (POS) system can tell you a lot about your grocery business. The POS captures checkout activity, like which lanes are the busiest and how many transactions are going through your self-checkout lanes versus non-self-checkout lanes. It can also capture which cashiers are ringing up the most transactions, the most per department, or the highest dollar amount per ring. And, of course, there is product information, departmental and total sales figures, your top 100 items, and so forth. That’s a lot of data.
Want better data about your grocery store? TRUNO’s Point of Sale solutions will help you get the information you need.
But while a modern POS is expected to capture all this data, it’s not necessarily easy for retailers to see, digest, and leverage in their day-to-day operations. That’s where POS analytics come in. With a proper set of analytics and business intelligence tools, you can make data-driven decisions that can improve margins in your store.
Pinpointing store-level growth opportunities
POS analytics can provide insights into your promotions and promotion management. Which promotions have been successful, and in which departments? By analyzing the overall performance of different sales categories, you can identify opportunities for sales growth. If you’re thinking about adding new categories—especially labor-intensive ones like fresh prepared goods—the analytics can help with future staffing and planning for product preparation.
You already have a good handle on what products you sell today, but analytics can help you determine what you want to sell more of—or less of. Use the data to help pinpoint opportunities at the individual store level, even if you’re operating more than one store. By analyzing categories, you can find opportunities where you’re not doing much business today but could expand your sales tomorrow, like paper products. You can also determine if you want to grow sales of seasonal items, like products that sell mostly at Christmas or New Year’s.
Planning ahead in your store
You can also use analytics to anticipate staffing needs. Predictive planning can help you determine the number of cashiers needed during busy hours or the staff required to unload next week’s delivery trucks. Being able to move staff from one department to another as needed improves operational efficiency and customer service.
In addition, POS analytics can help you analyze customer traffic patterns in the store, allowing you to optimize placement of high (or low) selling items. Managers can test different layouts to determine which configurations maximize sales while keeping the customers moving and satisfied with their in-store experience.
Identifying potential fraud at the checkout stands
Your POS system is about more than the products you sell. It also contains a wealth of information about the activities of individual cashiers. By recording all transactions during every shift, it documents each time a cashier overrides an amount or quantity, manually ring up an item, hits a “no sale,” or enter a weight that’s different from what registers on the scale.
Most cashiers are honest, but the checkout stand is one place where fraud can take place. When you have a picture of every sale in your store, it becomes easier to identify patterns that are out of the ordinary. So, when analytics tell you that one checkout lane has significantly different activity from the other lanes, it’s worth taking a look. There might be a perfectly good explanation for the difference, or you might be looking at fraud.
The future role of POS analytics
Looking ahead, use of POS analytics is expected to grow beyond predictive to prescriptive. Not only will grocers be able to predict sales, staffing, product movement, they’ll also be able to automate more operational decisions. For instance, the POS system could automatically shift cashiers to other lanes during busy times without a manager. It could also suggest placing an order for holiday stock ahead of the rush and have the manager approve it with one click. These are but two examples of how application of POS analytics could save time for management by eliminating multiple steps they perform manually today.
Today POS systems record what’s happening in the store at the lanes, but in the future, they will also track mobile checkouts and online checkout activity. Some systems can already analyze where people are in the store by using mobile scanners, helping managers analyze traffic and optimize product placement.
These types of prescriptive, data-driven operations will roll out over the next decade. As they become do, it’s important to work with a trusted technology partner to keep your POS systems up to date and ready to integrate with new technology as it emerges. The more you integrate your systems, and the more you’re pulling data from multiple sources and analyzing it together, the more valuable the data becomes.
With TRUNO’s Point of Sale solutions, you can gain insights to increase efficiency and improve your margins.