"People also buy" widget
Recommendations based on the actual buying patterns of customers
Inspiration from other customers
Key tags: Collaborative filtering, Buying patterns, Carts
The widget analyzes actual orders and identifies products that customers frequently buy together. This is one of the most effective forms of recommendation, since it's based on real buying behavior.
How it works
Cart analysis
The system analyzes thousands of orders and looks for patterns of products bought together.
Time-based associations
It also takes into account products purchased shortly after one another (e.g. accessories later).
Association strength
The more often products are bought together, the higher their priority.
Customer segmentation
Recommendations adapt to customers similar to the current visitor.
Data freshness
More recent purchases carry more weight to track current trends.
Statistical significance
We only recommend combinations with a sufficient number of occurrences.
Examples of buying patterns
Electronics online store: iPhone → People also buy: Case, screen protector, charger, AirPods
Clothing online store: Men's shirt → People also buy: Tie, belt, cufflinks
Fitness online store: Running shoes → People also buy: Running socks, sports watch, water bottle
Benefits for your online store
- High conversion rate thanks to recommendations based on actual purchases
- Higher average order value
- Automatic learning with no manual configuration required
- Relevance even for new products thanks to category similarity
- Leveraging the collective intelligence of all customers
- Continuous updates based on new orders
