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Recommendation Blocks and Dynamic Personalization
Awareness is the key. Knowing the needs of each customer in eCommerce is essential for sales growth and brand loyalty. eSputnik implements this principle by realization:
- customer website behavior tracking,
- behavior analysis using AI algorithms,
- multichannel interaction with the client by creating messages and arranging the logic in the scripts.
This functionality is used, for example, to generate product recommendations for the customer, based on data on user activity from three sources:
- messages - clicks in messages (emails, sms, web push, IM)
- website - collecting data about the behavior of users on the site
- CRM - information about offline customer behavior (calls to the call-center, offline purchases).
Product recommendations increase the average check by offering products that are similar to what the customer has already scanned or added to their shopping cart.
The goods selected by a particular customer can be sent either by email, push notification, Viber or SMS.
The implementation of this feature is highly effective due to simple integration, the usage of real-time AI technologies and an affordable price. it is easy to use, although it is driven by the impressive methodology of AI and Big Data.
Personalization technology improves customer experience, increases conversion rate and average receipt, increasing total sales to 20%.