Businesses need to grasp cause and effect: Someone did X, and it elevated sales, or they did Y, and it hurt sales. That’s why a lot of them make use of analytics — however, Bilal Mahmood, co-founder, and CEO of ClearBrain mentioned existing analytics platforms couldn’t answer that question precisely.
“Each analytics platform today continues to be based on an elementary correlation model,” Mahmood stated. It’s the classic correlation-versus-causation problem — one can use the data to suggest that action and a result are linked; however, companies can’t draw a direct cause-and-effect relationship.
That’s the issue that ClearBrain is attempting to solve with its new “causal analytics” software. As the corporate put it in a blog post, “Our aim was to automate this process and construct the first large-scale causal inference engine to allow growth groups to scale the causal effect of each action.”
The idea is to use this alongside A/B testing — prospects look at the information to prioritize what to test further and to make estimates concerning the impact of things that can’t be examined. Otherwise, Mahmood stated, “In case you wanted to measure the actual effect of each variable on your site and your app — the actual impact it has on dialog — it could take you years.”
The causal analytics software is currently available to early access prospects, with roadmaps for a full launch in October. Mahmood said there should be several pricing tiers; however, they’ll be structured to make the product free for many startups.
Along with launching the analytics tool in early access, ClearBrain additionally declared this week that it’d raised a further $2 million in funding from Harrison Metal and Menlo Ventures.