Automatic and accurate product recommendations are key to increasing cross-selling and up-selling. DigitalFMCG uses behavioral and transactional data to suggest products to consumers that will genuinely increase their basket value and satisfaction.
How It Works
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Behavioral Analysis: The system studies purchase history (online and offline), browsed products, campaign engagement, and loyalty status.
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Predictive Algorithms: Utilizing advanced algorithms to suggest subsequent products (e.g., "Customers who buy X often buy Y" or "Complementary products").
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Multi-Channel Targeting: Delivering personalized recommendations across various touchpoints: via email, SMS messages, push notifications, on activation landing pages, and within loyalty portals.
Concrete Benefits
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Increased Basket Value: Effectively encouraging the purchase of related products or more expensive alternatives.
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Improved Customer Experience: Ensuring the user feels that the brand knows and understands their needs.
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NPD Teaser Optimization: Using recommendations to more quickly promote new products (NPDs) among the segments most likely to purchase.
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Abandoned Cart Recovery: Automatically recommending complementary products to customers who have not recently made a purchase.
