Recommendations and chatbots
Posted: Wed Jan 22, 2025 9:07 am
The only way to know what works and what doesn’t is to collect accurate data by testing variations. In doing so, AI won’t just test different versions of a site or marketing messages on it, but will also determine malta telegram database which ones work best for different audience segments.
Even such minor functionality as the optimal schedule and channel settings for sending client mailings, made on the basis of ML, can seriously increase conversion. A similar case was implemented by a company producing construction sets for children and adults, and the response to a personalized mailing was 210% higher.
ML-based recommendations will help increase the amount of purchases, repeat sales, and even win customer loyalty: people value time and are happy if they are helped to choose what they like faster. The best effect is achieved by combining different types of such models: product ranking feeds, product-to-product recommendations, and personal selections.
For example, VkusVill, using a new ML-based system, prepared recommendations for discounted products for regular customers. All customers from Moscow and the Moscow region received notifications about products at reduced prices. As a result, the average bill increased by 8% in a month.
Even such minor functionality as the optimal schedule and channel settings for sending client mailings, made on the basis of ML, can seriously increase conversion. A similar case was implemented by a company producing construction sets for children and adults, and the response to a personalized mailing was 210% higher.
ML-based recommendations will help increase the amount of purchases, repeat sales, and even win customer loyalty: people value time and are happy if they are helped to choose what they like faster. The best effect is achieved by combining different types of such models: product ranking feeds, product-to-product recommendations, and personal selections.
For example, VkusVill, using a new ML-based system, prepared recommendations for discounted products for regular customers. All customers from Moscow and the Moscow region received notifications about products at reduced prices. As a result, the average bill increased by 8% in a month.