Smart merchandising and data analytics to optimize sales

GRADUS introduces innovative approaches to merchandising using data analytics, which allows not only to more accurately forecast consumer demand, but also to quickly respond to market changes. Using its unique tool — GRADUS Retail Index (GRI) — the company evaluates up to 80% of the market volume for key SKUs. This allows for a quick response to changes in demand and accurate forecasts, ensuring that sales strategies are adapted to market needs.

The strategy is based on the availability of granular data collected at the level of retail chains and individual retail outlets. These data allow us to evaluate the potential of each retail outlet (RI) based on sales by category and identify lost sales.
As part of the implementation of the smart merchandising approach, the company clustered retail outlets by unique product range and sales volume. Evaluation of equipment operation during and outside of promotional periods, as well as testing various variations of product display, make it possible to optimize merchandising and identify the most effective ways of placing goods.

Identifying the key contribution of merchandisers to sales efficiency allowed us to review the frequency of their visits and update routes, as well as adapt the targeted program for placing DMPs, which reduced costs and increased turnover. The introduction of a tool for signaling problems with sales of one SKU helps to promptly identify a decrease in demand and adjust the strategy at the network level, allowing merchandisers to respond to changes in a timely manner and minimize losses from incorrect placement of goods or incorrect price tags.

Thus, data analytics helps make informed decisions, increasing the efficiency of product display, improving the operation of equipment and adapting sales strategies to changing consumer preferences.

In his speech, Vladimir Vasyutkin explained in detail that the Perfect Store concept includes several key elements that contribute to achieving maximum efficiency in retail. The key components of the perfect store are:

· Data: Deep analysis of sales by SKU and outlets allows you to forecast demand and optimize product display.

· Pricing: Monitoring prices for your own products and competitors' goods helps evaluate the effectiveness of promotions and sales, as well as adjust the pricing strategy.

· Assortment work: Analysis of sales and customer preferences allows you to flexibly manage the assortment, promptly introduce or withdraw items, and adapt product lines to changes in demand and market trends.

Vladimir emphasized that the correct use of analytical data and standardization of product display not only increases the effectiveness of promotions, but also helps optimize the use of retail equipment, which contributes to increased conversion and increased sales. Thanks to accurate analytical sales data, you can accurately measure the efficiency of equipment use and the result of the attractiveness of goods on the shelf.

Perfect Store is not only a space for selling goods, but also a set of strategies aimed at maximizing the convenience of purchase for the client and efficiency for the business.

In order to not only successfully sell, but also beautifully and effectively place products on the shelf, the professionalism of the merchandiser is important. The merchandiser plays a key role in achieving pictures of success on the shelf, helping to attract the attention of buyers and stimulate demand. It is the competent display and placement of goods, supported by analytics, that become important aspects in the effective operation of retail outlets.

Thus, Vladimir Vasyutkin at PRODEXPO 2025 emphasized the importance of integrating data analytics into merchandising processes and managing product range presentation in the sales area and on the shelf. Implementing tools such as GRADUS Retail Index helps to promptly adapt your sales strategies, increase their efficiency and minimize losses from incorrect product placement.

To successfully work in modern retail, it is not enough to simply place a product on the shelf. The most important factor is an accurate understanding of where, how and when the product will be in demand by the buyer.