E-Commerce

Most e-commerce teams do not struggle with traffic anymore. They struggle with conversion, basket size, and repeat purchases. That is where recommendation engines quietly make — or break — revenue. Done right, recommendations do not feel like “AI.” They feel like the store understands the customer. Why Generic Recommendations Fall Short Many platforms offer built-in recommendation features. They usually work on simple logic: similar products, popular items, or past purchases. That is fine at a basic level. But in real businesses, it breaks down quickly. At that point, recommendations stop helping and start getting ignored. What “Custom” Actually Means in Practice A custom recommendation engine is built around how your business sells, not around generic engagement metrics. For example: The model is not just predicting what a user might like. It is helping the business decide what it should recommend right now. Real-World Use Cases That Drive Revenue Personalized HomepagesReturning customers see products aligned with their browsing habits and price sensitivity. New visitors see curated, fast-moving items instead of a random catalogue dump. Product Page RecommendationsOn a smartphone page, accessories and protection plans convert better than “similar phones.” A custom engine understands that context. Checkout UpsellWell-timed recommendations at checkout — chargers, refills, subscriptions — add revenue without slowing down the purchase. Post-Purchase Follow-upsAfter a purchase, recommendations shift toward replenishment, accessories, or upgrades instead of repeating the same product. Where the ROI Actually Comes From The real impact shows up in: In mature e-commerce businesses, recommendations often influence a significant share of total revenue, even though customers barely notice them. That is usually a sign they are working. Why Custom Beats Plug-and-Play AI Off-the-shelf tools are built to work for everyone. Custom engines are built to work for you. They can account for: More importantly, they can evolve as the business evolves. Final Thought Good recommendations do not feel like marketing. They feel helpful. Custom AI recommendation engines give e-commerce teams control over what gets shown, when, and why — turning personalization into a measurable revenue lever, not just another feature.