Featrix Customer Journeys

Uncover insights from your eCommerce or retail sales for B2C.

What are your customer cohorts? Who buys what when? Do some products often get bought together? Are there hidden relationships across orders from customers? Can you identify what messages or offers to present to customers at the right time?

Customer Journeys is a new solution in beta with Featrix. We'd love to hear from you what you need in a solution like this. We are working with multiple retailers to hone this solution.

How Featrix Haystack works

Focus on the leads that AI finds  promising for your business.

When it comes to prioritizing contacts, things can be difficult. When you’re buying data from the big vendors, you might have SIC codes, NAICS codes, headcount, and annual revenue. These data items are often wrong, missing, or conflated among each other. Further, while your sales and marketing teams interacts with these contacts, the company is a hidden layer behind all the contacts. So we need a two layer solution that models both companies and contacts.

You can extract three sets from your CRM, and load them into Featrix: the universe of contacts available to us, the list of “good” outcomes, and the list of “unwanted” outcomes. Featrix Haystack takes in your lists, adds additional data enrichment, and ranks and sorts your universe of what’s possible.

From the scored list, you can build tailored campaigns to test new business hypotheses and optimize existing campaigns. Featrix Haystack can continuously learn and improve its ranking from your new activity going forward.

Discovery and Naming of Groupings

Featrix enriches your business data with information available on the internet, creates embedding representations, and applies proprietary clustering techniques to discover and label meaningful groups. To take the process a step further, Featrix Haystack automatically generates descriptions of the groups, which yields candidate names for the identified groups that are contextually appropriate, depending on the types of companies in your data.

It almost sounds like magic — but it's working in production at multiple customers today.