Predictive Models Applied to the Retail Sector
The use of big data and predictive models has become one of the greatest successes for the sector, thanks to these, it has been possible to take proactive measures based on real-time data and predict future trends.
Using the right models and calculating historical data, it is possible to predict customer behavior, sales growth, changing consumer behaviors and/or market trends; helping retailers to stay ahead of the curve in order to compete effectively and gain considerable market share. It also enables leaders to set precise goals for their business.
What are the uses of these predictive models?
Personalize customers by understanding their behavior and combining it with consumer demographics in order to create customized offers to customers at a detailed level.
Segment customers to detect and satisfy their needs and priorities by indicating the percentage of customers that are gained or lost over time, as well as the potential revenue or loss they leave behind.
Inventory and supply chain management answers questions such as what to stock, when to stock, and what and when to discard.
Retailers can link data on customer behavior with demographic data, with the aim of scoring each customer according to how likely they are to buy certain products at different points of sale.
You may be interested in: “Geospatial data applied to the retail sector.”
In marketing campaign management, they are used to strategize future campaigns. The more you know about your customers, the more targeted your message can be.
Contact us for more information about our Business Intelligence solutions with predictive models in the retail sector.