How ML/AI can help influence buyer behavior through Real-Time Offers to Boost Conversions in Retail?
In the real world of brick-and-mortar shops, a keen salesperson would observe buyer behavior and use their experience to engage the customer and influence them to become a buyer.
A great salesman has the luxury of interacting with the customer and also takes cues from the customer’s body language.
How do we get that salesman-like influence in an online store? Here is where we used machine learning to analyze past data and train models that allowed us to predict buyer behavior.
It was a long process that required analysis of the past purchase history of users.
- Comprehensive research activity was done to identify the right features that affect buyer behavior in the client’s retail domain.
- Almost 1 Million user sessions across 6 months of data were analyzed.
- We tried multiple features, models, and variants before we found some success
- In the end, we achieved an increase in non-purchase-to-purchase conversion by almost 15%
- We were also able to Identify up to 12 unique user personas through ML-assisted segmentation and clustering exercises that helped the marketing team in retargeting campaigns and improving our models further.
Next Step
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