Recommendations – whether from friends, reviews or other encounters – are one of the principal motivators when it comes to making a purchase decision.
Custobar calculates product recommendations for use
- in any campaigns
- on your site (API)
- on Store Dashboard for salespeople
These are based on a number of factors, and, importantly, are calculated using all recorded purchases, not just those made online.
Our system calculates recommendations based upon customers’ sales and browsing data, as well as discerning those products that certain groups of individuals buy. This is based upon the best-performing personal recommendation algorithm we have tested.
Some example product recommendations
- A recommended product specifically for an individual customer
- Content-based recommendations, such as ‘Similar products’
- ‘Customers who bought this also bought…’ – item-based collaborative filtering based on sales data
- ‘Customers who viewed this also viewed…’ - item-based collaborative filtering based on browsing data
Custobar product recommendation API
Product based recommendations
Format of the API request:
This parameter can have 4 different values: similar, bought, viewed or all. All will return all types.
ids_only=1 API returns only IDs of the recommended products. Otherwise it will return all product data in Custobar of the recommended products as JSON.
count=x you can specify the number of products you want to receive.
boost=1 -boosts similar products (brand, category, type etc.) higher. Boosted fields can be configured from company settings. Used in bought & viewed products.
category | type | brand can be used for filtering results
Other customers bought also these products (in these examples: Product ID = 0375704027):
Filter recommendations with product type:
Other customers viewed also these products:
Most sold products (returns product ID and count)
Most viewed products (returns product ID and count)
Like the most sold products.
You can also include count, i.e:
Personalized product recommendations for customer