We use cookies for a better Customer Experience. Please see our Terms and Conditions for more information.

SALESmanago Live Product Demo

Wednesday, 10:00 am CEST

SALESmanago Live Product Demo

Wednesday, 10:00 am CEST

REGISTER

Machine Learning & AI recommendations

Analyze website traffic, transactions and user profiles to build connections between them, predict shopping behavior and create personalized product recommendations. Recommend products based on the behavior of other customers with a similar profile.

Machine Learning & AI recommendations

The use of the Machine Learning engine to create product recommendations is aimed at:

increasing sales conversion through product recommendations with the best chance of purchase,

personalizing the website also for anonymous visitors,

shortening the purchase path, by providing recommendations that may that may interest the user the most and shorten the search time for the perfect product,

increase in the effectiveness of retargeting campaigns, thanks to the use of AI recommendations in advertising networks.

How does this work?

Machine Learning & AI recommendations

Based on the analysis of data on visits and transactions, SALESmanago calculates the probability of other products occurring after a visit or purchase of a specific product and recommends those giving the greatest chance for customer interest.

SALESmanago Copernicus operates on the basis of five types of recommendations:

  • collaborative filtering - offering products based on the similarity of users and concurrence of various products
  • most frequently bought after visit other
  • most frequently visited together
  • most frequently bought together
  • mixed statistics with weight

Generated recommendations can be used in communication channels: e-mail, website, web push, social media, advertising networks.
Machine Learning eliminates expert restrictions such as custom user behavior and unique preferences, matching recommendations to changing customer behavior in real time or price sensitivity.

Use Cases

Adjust the page to the client's profile

Website personalization

Recommendation frame on the cart page, with products selected according to the type of recommendation: collaborative filtering for cross selling purposes.

Increasing cart value

Recommendation frame on the product page with the products most often bought along with the viewed product

Recommend products real-time while Live Chat conversation

Personalization of Live Chat conversations

Product recommendations generated based on AI & Machine Learning in Live Chat.

Convert leads into customers

Product retargeting

Send an email after an abandoned cart with 1-to-1 product recommendations and generated based on AI & Machine Learning.
The use of advertising networks to target ads containing AI product recommendations to users who have not made a purchase after a few page views of the product.

Effectively regain interest

Retargeting

Sending win-back campaigns with AI product recommendations encouraging to return to the website.
Maximize eCommerce revenue growth… the lean way