Optimize your marketing campaigns, improve your offline or online navigation and sell more by understanding what product are frequently bought together.
In a matter of hours any developer or even non-technical analysts can integrate the transactional data from your eCommerce with our no-code advanced analytics solution to infer multiple association rules.
Optimize Email Promotions Campaigns
Acquiring new customers is extremely expensive. Get ideas of which products tend to sell well together. Then segment these campaigns to the right customers to increase recurrence or to sell out products with too much stock.
Optimize In-Store Product Placement
Understand which are the real product categories that emerge from your customers' purchases and behaviour to improve the navigation, discoverability and engagement of your eCommerce website or physical store.
Sell more by adding "Frequently Bought Together"
Increase the average ticket by implementing product recommendation algorithms in your shopping cart without the need to hire a team of data scientists like Amazon. Any developer can create and maintain product recommendations in a matter of hours with our no-code and guided data science platform.
Integrate with your Transactional Data
We have integrations with all major modern datawarehouses and databases. You can easily send data from your Shopify, Magento, SAP... with any ETL solution like Fivetran or Airbyte
How It Works
Control and share access to your projects with your teamVIEW CASE STUDY
Discover more in Docs
Precisely understanding the behaviour of your customers is a realm where details count.GO TO DOCS
Clustering Supermarket Transaction
Clustering is a machine learning technique used to group data points based on similarity.
Market Basket Analysis
Retailers use market basket analysis to uncover the associations between products.
Scraping with Tractor
Tractor is a tool to scrape data from popular platforms. Use it to bluid datasets from information on Google, Twitter and facebooks Ads.
This guide is intended to walk you through the process of analyzing customer reviews with Graphext.