If you are in retail, you don’t have to Saint Lucia Email List for a certain technology to act thanks to data. You surely already have data on hand that will allow you to find new levers to activate. I will present you 9 ideas. They may already be within your reach because the data is in your systems. You can operate them on your own or with the help of a firm. We made with Armel Gilibert a selection of data use cases that would be relevant for a retail player. They relate, for example, to the analysis of the sales area, the optimization of prices or the personalization of the customer experience.

Study the phenomenon of range extension and omnichannel through data Use sales and web research in a geographic area to enrich the offerings of stores in that area. This work will allow you to understand what motivates consumers to buy online rather than going to the store. Today retail is also done online. Improving loyalty programs and making targeted recommendations to customers online is possible. For this, it is necessary to analyze the tastes of the customers by their past purchases, even the history of consultations and the demographics of the customers. Data to identify the pain points of retail customers

Personalize the online customer experience

Use video feeds to identify items or departments that interest customers but that do not generate purchases. Identify areas where customers spend little time reworking the layout or adjusting the associated offer. Use sales history, even consultation history and customer demographics to make targeted recommendations to identified customers. For example, asking the customer if they have a loyalty card to scan or an account. An in-store customer advisor can then access the profile of the person in front of them and inquire about customer satisfaction for their past purchases. He can also offer advice or recommend products that may be of interest to him.


Analyze purchasing habits by crossing them with geographic and demographic data in order to optimize prices according to the profile of the store’s customers. Stores can display different prices and therefore influence the purchasing power of their local customers. Identify the determining factors that influence the customer experience in retail Exploit comments left on social networks or search engines for your brand or your competitors. This makes it possible to deduce action plans for continuous improvement. Forecasting sales by product family or by product allows you to optimize inventory levels to better meet customer demand and limit unused inventory and purchasing costs.

Data to identify the pain points of retail customers

The data can also be used to supply its pedestrian drives reliably. Knowing the purchasing statistics of its customers in a given geographical area makes it possible to anticipate demand. In a simplified way: If the probability of having a demand greater than P packets of M brand toilet paper rolls is high (> 95%), we supply at least P brand M packets locally in our pedestrian drive We send the rest in a few hours depending on statistical fluctuations. But overall we save trips that might have carried M. Analyze the criteria to determine where to open stores and their typology.

For example, you can analyze the geographic and demographic characteristics of consumers to understand which type of store customers in a specific location would be most sensitive to. This approach is certainly already carried out in an artisanal way, you can think about systematizing it. Identify the companies and communities likely to call on your services and the turnover potential according to the activity, their geographical position, the type of premises, etc. You already have a gold mine in your data: sales history, user behavior on the web, demographics of your customers, inventories, etc. You can supplement it with open data (characteristics of the territories, SIREN database etc.)

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