Recommendation Engine: Right recommendation equals higher profit

Retail_how-recommendation-engine

A retail business survives on its customers. To keep customers interested in their brands, retailers have to constantly come up with schemes that can lure the customers, which can result in better sales for them. But, how to engage the customer so that he can be converted into a better sale at the end of the day, this is something every retailer is thinking about and putting his money on. Also, a major roadblock for the retailers is to enable a phygital retail experience by linking the customer's digital journey into their stores in a frictionless and contextualized fashion. So how can a retailer come up with recommendations that can keep the customer engagement up and running?

How retailers can recommend a better option to the customer?

In this digital age, the market is governed by data. With precise analysis of the data, a retailer can recommend the best option to customers to boost the store’s sales. Better and precise recommendations can be made to the customer with the help of data-driven recommendation engine which allows the retailer to engage the customer both online and in-store.

With Softweb Intelligence and Analytics platform (SIA), a retailer can help a customer to have multiple relevant options to choose from to complement their requirements. SIA can also help the customer to avail the loyalty points which helps the retailer to retain the customer and keep him engaged. With the help of technologies like machine learning and data science, SIA can process massive amounts of data for the retailers. It can record, cleanse, normalize, and aggregate data from a variety of data sources which can result in an extensive inventory of actionable recommendations for the customers.

SIA recommending success tips

  • Anticipate demand and drive sales with individualized recommendations for the customers
  • Categorize customers on the basis of their preferences and previous purchases
  • Suggest complementary products for current purchase
  • Recognize when a consumer might need a past product again and provide more context-aware choices to them
Talk to us about your data complexities and let SIA address them