Become Data Driven to Optimize Seasonal Merchandising

What can we say about data? To quote the legendary country music star Tim McGraw, I like it, I love it, I want some more of it,” and I know I’m not the only one that feels this way. 

The fact of the matter is we all have access to a lot of data. Data is being collected and compiled from Wi-Fi, Bluetooth, video-based business intelligence tools, and programs we constantly use. But, with all this data the challenge is the difficult and time-consuming task of sifting through and organizing the mountains of information. The beauty of this? It gives a ton of insight and, if used properly, provides the edge you need to keep customers coming back to your store. The key is to become data-driven. Understand and accept what the data is telling you and use it to your advantage.

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Summer is right around the corner so let’s consider seasonal merchandising as an example. For consistency, I will refer to merchandising as the planning and promotion of sales by presenting a product to the right market at the proper time, by carrying out organized, skillful advertising, using attractive displays, etc.” You can bet there is a lot of data out there driving the decisions of where product is being placed, which products are purchased together, and how people navigate stores. This list goes on and on.

A retailer working with RetailNext, an in-store analytics company, realized a 19% increase in sales after testing the removal of floor displays that prevented customers from effortlessly browsing merchandise in the store” - Analyze This: Web Style Analytics Enters The Retail Store

So for seasonal merchandising, or any merchandising, Forrester suggests retailers be effective in using retail store analytics to transform the operations of a physical store. Retailers must marry retail store analytics data with traditional data by combining data such as inventory position, staffing levels, customer lifetime value, and online browsing behavior with other historical behavior that may live within an enterprise data warehouse.

By using the data correctly, retailers can achieve optimized store layouts and merchandising based on season and the customer’s behavior, providing a more personalized in-store experience. Additionally, it provides a more effective way to plan for future merchandising. Transactional data can show what items are typically purchased in pairs, allowing retailers to promote products together and make it easy for customers to get what they want, or upsell to customers who didn’t necessarily come in to buy both items.

Along with streamlining the operations of the physical store, retail store analytics also offer retailers the opportunity to personalize a customer’s experience. In many ways, the operations of a retail store analytics platform closely resemble that of traditional eCommerce analytics systems” - Analyze This: Web Style Analytics Enters The Retail Store

Getting setup to use this data isn’t necessarily easy. As I mentioned earlier, there is a lot of data out there, so retailers need to be strategic in how they use it. The trick is implementing a solution that gives you all the data you need to make informed decisions about your merchandising and other strategic plans and allows you to present the data in a way that can be easily read and acted upon. Luckily there are solutions out there that will help you do that.

Keep up to date on every aspect of your business with RQ’s advanced reporting. Metrics are collected in real time, analyzed, and presented with clarity on store, executive, and productivity dashboards. RQ also provides product forecasting and order suggestions based on sales trends.