Each wine has several characteristics that are processed and stored in a GraphDB.
Wines are connected based on similarities such as grapes, structure and food pairing.
Wines can now be quickly clustered and searched based on similarities.
Add upselling recommendations based on sales data. Increase sales by adding a real-time recommendation engine based on user cart items.
Show the most interesting content to your users based on what they see, play, like or read. Understand their behaviour and suggest things that they would like.
35% of what consumers purchase on Amazon come from product recommendations.[Source]
75% of what people watch on Netflix comes from the recommendation algorithm.[Source]
+20% conversion on personalised landing pages compared to non-personalised pages.[Source]
66% of consumers would stop making a purchase if they did not see personalised content.[Source]
Yes, the engine provides recommendations that can be used anywhere on your website, product pages, homepage, cart etc…
From when we receive your data we would build a working demo in 1 week and a production ready service in 2 weeks.
No, you won't pay any monthly fee for a proprietary product or service. We will build your recommendation engine with open source technologies.
No, we won't need access to your source code. We will build a separate service that can be integrated with your code via API.
No, not if you don't want to. The recommendation engine can be hosted in the cloud or into your own infrastructure as well.
Yes, if you want. We can offer a maintenance service after the release. Otherwise the recommendation engine will be based on open source code accessible to any developer in your team.
Because we can offer bespoke solutions with a strong background in web-based applications that collect, process and show data.