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Module
Recommendation Engine
A recommendation engine that recommends products to customers based on their past product interactions or that of other customers with similar interests. XStak’s recommendation engine is a cloud-based recommender system that offers a self-service workflow so that you are up and running in no time.
Your time is valuable, save it with our recommendation engine
1.
Personalized Recommendations In Real-Time
2.
Increased Average Order Value (AOV)
3.
Drive More Sales
Why XStak's Recommendation Engine?
Give your customers recommendations that they will love, right when they need it! With our recommendation engine, you can take advantage of real-time data and advanced algorithms to deliver tailored recommendations for your customers.
Personalized Recommendations
Our product recommendation engine is a self-service tool that provides personalized recommendations based on customers’ past purchases. You can start using it in your company today.
Increase Conversions and Revenues
With better recommendations based on past behavior and owing to smart recommendations, you can see increased conversions on your store and drive more revenues per customer visits to your store.
Improved Customer Experience
Customers find what they would potentially like very quickly and recommendations reduce customers' time to look for similar products and products that have been bought together in the past by other customers with similar preferences.
How it works
Collaborative Filtering: Based on similarity of customer(their browsing or purchase behavior)
Content Filtering: Based on similarity of the product
Features
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Collaborative filtering is a strategy for predicting or classifying future behavior. We use this to suggest products for purchase. The prediction is based on past likes/actions and not on features of the product itself.
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This feature allows you to recommend products that have similar tags/attributes to those products that are currently being viewed/added to the cart by a visitor.
Hot-selling products
These products are being added to cart or viewed by other visitors and you might want to pick them up.
Case Studies
Case Study
Improving Conversion rates and ROI
Several fashion retailers, including Bonanza, Alkaram Studio and Meme , were facing difficulties in increasing their conversion rates and achieving higher revenue and higher average order value. To tackle this problem, XStak proposed a solution to these retailers that focused on enhancing customer engagement, increasing the average order value (AOV) per customer, and improving conversion rates.
XStak's Product Recommendation Engine was identified as a key tool to achieve these goals. After implementing the recommendation engine, these fashion retailers observed a significant improvement in ROI and customer engagement, leading to an overall increase in profitability per customer visit. The retailers were thrilled with the results and recognized the value of XStak's solution in driving business growth.
The Results
261x ROI
Bonanza
94x ROI
Alkaram Studio
41x ROI
MEME
Boost Your Ecommerce Conversion Rates