London-based digital experience provider Qubit has built a machine-learning engine aimed to help marketers better target customers by revenue opportunities.

Announced today, the Qubit ML engine leverages predictive analytics and machine learning. 

In an interview with CMSWire, Bud Goswami, lead data scientist for Qubit, said the platform gives companies the ability to go "opportunity mining.” 

Personalized, Targeted Messages

With the machine learning engine, Qubit users can surface and rank segments of customers and then send them personalized messages.

"It helps marketers understand and influence their customers," Goswami told CMSWire. 

Qubit ML provides a range of programmatic experiences for those targeted customers rather than offering experiences without context, he added.

"There are obviously a million ways to slice and dice data," Goswami said. "But a lot of it has been isolated from business relevance. OK, so you have this information. What are you going to do next?"

Not knowing that answer can "lead to inefficiencies," he added.

Qubit Uses Behavioral Data

Bud Goswami
Bud Goswami

Qubit's digital experience management platform collects a range of first-party behavioral data for visitors across all digital channels. 

Its data pipeline validates the data and then makes it available for consumption, Goswami told CMSWire.

The machine-learning engine layer will help marketers understand missing revenue opportunities. 

  • Why are they not converting? 
  • Do they need better product recommendations or a better-targeted email?

"You can communicate directly with them on the Qubit app," Goswami said.

Learning Opportunities

Qubit machine learning
Qubit machine learning

Goswami said customer discovery, experiences and the measurement of those experiences sit on top of data collection and a data service pipeline, explaining:

"This closed feedback loop of end-to-end data collection and machine-learning measurement is a strength of Qubit's as opposed to the rest of the marketplace. We really don't like to say, 'Do business with us because of machine learning.' Machine learning works better as a tool for marketers by allowing them to ask the next question." 

Design Workflows

Qubit, through a new experience design workflow, also allows users to define rules for digital experiences and bring in developers to deploy.

Qubit officials said they A/B tested more than 2,000 e-commerce experiments and found abandonment recovery, social proof messaging and product recommendations as great tools for revenue growth. 

Qubit also announced today increased support for seasonal or time-sensitive customer segments, like Halloween- or Christmas-driven businesses. This update follows the spring release that included Qubit Live Tap, which gives companies access to all customer data in Qubit Visitor Cloud. 

Qubit closed a $40 million Series C funding round led by Goldman Sachs earlier this year. To date, Qubit has received more than $76 million from Goldman Sachs, Accel, Sapphire Ventures, Balderton Capital and Salesforce Ventures. 

“We’re seeing continued change in how consumers interact with brands," Graham Cooke, CEO and founder of Qubit, said in a statement. "The need to build a more complete customer understanding, and to have a robust and agile technology platform that helps deliver the right experiences, is imperative."

All enhancements are expected to be available in November.