Why right data matters in retail analytics?


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The world of retail business involves being in direct proximity to the customers. Selling goods and services to the customers directly can appear to be a piece of cake, but it is usually not the case. Taking a shot in the dark while predicting a business decision’s success can only take the retailer so far. This is where analytics plays a crucial role. Retail analytics provides insightful data about sales, inventory, customers, business trends, patterns, and performance in the retail industry. It is not always the Data that determines profits, but the right kind of data.

Here are some factors that retailers need to consider while identifying the right data sets:

The Nature of Your Business

This is a very crucial point to consider while defining the correct data. For instance, for a travel agent, data about the ticket sales for a particular destination vs. the customer’s economic background will determine the destinations and packages they must offer. Similarly, for a restaurant chain, data around the days when youngsters flock the joint and the average sales on that day will help them come up with exciting offers.

Pricing of the Product that You are Selling

The pricing of a product determines the data required to drive its sales. What will be ideal data for a luxury good will not be perfect for predicting the sales for an economic product. If we look at the product placements in a jewelry shop, we can categorically make out the strategy behind the placements. For diamonds in the store, the average sale price per unit sold in a day is relevant data, whereas, for gold/silver, the volume of purchase in a day will be considered key.

Format of the Retail Store

A store can exist in various formats. A shopping mall, for instance, is different from a standalone 7-eleven store. A shopping mall is interested in knowing the number of high-income spenders that visited them in a month. This can be achieved through a collaborative effort with a premium store in the mall. Special promotions by the mall can be ideated based on the total number of footfalls on specific days. Staffing and leaves of the employees working in the mall can be worked out based on this Data.

Whereas, a convenience store like 7-eleven can be interested in knowing the products in each category that sells quick. The store that is flocked by middle-income customers can be further classified into age groups. This can help determine decisions like the success rate of a mobile application when launched or the promotions/ product placement that the store needs to work upon.

Data analytics is not just limited to a product or a store. A business can improve their understanding by analyzing individual behavior and summing up a collective trend. Data helps to adjust and flourish according to the market’s needs. Any business is about meeting the market need.

The importance of a data-driven approach in the retail sector cannot be undermined. If at all, a business must only invest in improving its retail analytics. Retail analytics solutions offered by ‘Denave’ provides real-time actionable insights that can identify growth drivers. Powered by AI and data sciences, it focuses on solving a specific problem. With a user-friendly visualization that presents KPI dashboards, infographics, ops insights, trackers, etc. in easy to understand format, there is a power of simplicity.

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