Retaining customers is a major priority for tech-based businesses, and until recently it was a daunting task to identify which customers may not stick around. The effort often required hiring data scientists or entrusting private customer information to third-party analysts.
Bellwethr, a customer risk prediction and prevention startup, is changing all that. Its software uses machine learning to automate business processes, which removes the need for a staff of data scientists and helps keep data from being passed to multiple parties.
Midway through last year, the company was accepted into the 2018 class of the three-month Techstars Kansas City incubator program. We caught up with Bellwethr founder and president, Matt Moody, to learn a little more about how Bellwethr helps tech companies stay on track with growth and customer satisfaction.
Q&A with Bellwethr Founder and President, Matt Moody
Q: What does Bellwethr do and what makes you guys really different?
Matt Moody: We automate business processes with automated machine learning bots. It’s drag-and-drop where you can build a bot that basically learns the patterns in the data and then applies it. You basically just kind of drag and drop in the inputs like city, age, when somebody signed up, when did somebody leave, those sorts of things. You can identify what outputs you want. And now we have some templates that we’re going to roll out that make it simpler, that give a starting point.
Q: Why is automating machine learning super-hot right now?
MM: The opportunity is so big right now because data scientists are hard to find and when you do find them, they are expensive. If we can get by with none, then it’s going to be huge for businesses.
Q: As a business, how do you guys measure success? What metrics and KPIs are you focused on for 2018?
MM: We’re still early stage; we’re trying to find a scale as far as the KPIs go. We’re starting with how many product demos we have every single day. That’s one of the main KPIs. We’re looking at customer feedback all the time to understand how we can make Bellwethr better.We’re also trying to make sure that we’re horizontal in how we function. We’re trying to find different verticals where we can apply what we’re doing.
Q: How are you defining and building the culture at Bellwethr?
MM: We’ve worked together in the past and that makes it really easy because everybody already knows what to expect from everybody. I think the culture is going to be something that’s going to be a growing challenge when we expand beyond the known players. One of our big initiatives is bringing on talent and recruiting; so that’s going to be a challenge. We’re still pretty tight knit.
Q: You just got accepted to Techstars. How does this change the next few months? What are you most excited about, most nervous about?
MM: Going into this, we want to learn from all the Techstars folks with vast experience and get their feedback and really to use that to build the business. The first week was pretty eye-opening, and that’s just the first week.
Q: Where does the name Bellwethr come from?
MM: From sheep herding, actually. In the flock they would tie a bell around one of the animals so when danger came, it was a predictor. So, there’s sort of a predictor of the future for machine learning and prediction. I did learn from my kids that “Bellwether” is the name of the bad lady in the movie Zootopia. I’m like, oh, great. Wonderful. I didn’t know I needed to run the name by my kids before I named it.
Q: Can you talk us through your funding philosophy for Bellwethr?
MM: We obviously went about funding Bellwethr in a different manner than a lot of tech companies do. We didn’t want to try to raise as much money as possible from private investors. We’ve been profitable since day one, which is pretty rare. Basically, we’ve been generating revenue since the very beginning.
We had revenue, then we needed to expand a little bit on the team. So that was the point where we brought on Lighter Capital. And as we learned more and figured out what we really wanted to do, that was the point where we felt that Techstars would be a nice fit.
Q: Besides Techstars, what are you most excited about in the upcoming year?
MM: I think we’re most excited about rolling out a lot of new stuff. I’m excited about seeing where our new development goes. We’re taking a pretty big swing here and are trying to solve a big problem. It’s pretty clear this is going to be really hard, but on the flip side, it should make a significant impact when we succeed.
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