This afternoon at the Disrupt SF Startup Battlefield, PatternEQ launched into private beta with an aim to help software as a service (SaaS) companies attack on of their chief foes: churn.
Call it data science for the common man. PatternEQ takes in data from a startup’s various sources — MixPanel, for example — weaving the information into its own algorithmic tools to help a company make actionable sense of its data. PatternEQ has built a number of algorithms that it quickly checks against a company’s data. It then selects the one that is most astute, and applies it to the collected information.
The company has bigger goals for its software, but it’s starting with a focus on SaaS churn. That’s a reasonable selection, given that the SaaS market segment is quickly growing and has cash to spend given the current fundraising landscape.
PatternEQ is predicated on the point that hiring a data scientist for your firm is expensive and slow. If you need results on your data quickly, you can’t afford to wait for a service that you might not be able to afford. PatternEQ will cost about $1,000 per month, a sum that should be in the price of companies with enough subscribers to desire a deep look into their churn.
The company went through Data Elite Ventures and is looking to raise more capital to hire additional engineers.
Founder Uzma Barlaskar told me that the product can accept any data set from a user and run its algorithms against the information. Barlaskar also indicated that the company is building a number of templates that will help the less technical user better parse their results. Those templates will be ready in the fourth quarter of this year.
In short, PatternEQ wants to become the nexus for all your company’s disparate information sources, bringing them together and spitting out insights that were previously obscured from sight. If PatternEQ can pull off its vision, it will be cheap at 10 times the price.
Data science has almost joined big data and cloud in the pantheon of terms that are so overused that they lose all meaning. But in the case of PatternEQ, its premise — helping SaaS companies cut churn — is constrained enough that its effort to democratize data science is a reasonable use of the phrase.
When PatternEQ releases its templates product, we’ll check back in with the company to see how quickly it is growing.
What is the secret sauce?
Automation, the user doesn’t have to pick what sort of algorithm that they need to analyze their data.
What is the target market?
Small businesses, others can use it, but we are focusing on small businesses. Don’t think that people will graduate out of the product.
Are you selling a service, or a technology, or both?
It’s data science as a service. We don’t want you to do other services on top.
What have you learned that might surprise us from your data users?
The hardest part is getting the data into the same place. People have a hard time getting a unified view of their data. Other thing is that people are still learning about predictive analytics.
How do you compare with a Tableau, or other firm that is targeting more advanced companies?
Tableau is not predictive. Domo is a BI tool, and so they don’t provide predictive analytics either.
Am I trusting you with my data, or do I run it locally?
It’s a SaaS service. The target market is not going to set up a Hadoop cluster, so we do that for them. We decide the best technologies, and you just focus on what you do.
Where does the data live?
You can upload files, or you can connect to our APIs, so it comes into our servers. You can choose which events you want to pull into the platform.