Thursday, June 27, 2019
Interview with Michael Greenberg, Retina
In an age of ever increasing marketing spend to attract customers, how do you make sure you aren't spending more acquiring a company than they are worth? Los Angeles-based Retina is using machine learning and artificial intelligence to figure out customer lifetime value (CLV) for such businesses as Dollar Shave Club. We spoke with Retina's CEO, Michael Greenberg, to learn more. Retina is backed by Comcast Ventures and Crosscut.
What is Retina Go?
Michael Greenberg: Retina is the world's premier company around customer lifetime value scoring and behaviors associated with that.
How do you do that?
Michael Greenberg: My co-founder, Emad Hasan, led the business marketing operations at Facebook. He saw that the cost of acquisition for many, many different businesses were going through the roof, week after week. We saw that they were hitting the inflection point, where they were spending more than they were receiving from customer acquisition. As you may have seen in a recent report, when that happens, it's death for those businesses. To tackle this, we formed Retina in 2017, so that we could help businesses find out the true lifetime value of their customers, not just after they had them for years, but when they just walked in the door. We're arming them with the ability to retain the customers with most value, and attract more customers that look like them.
We see you do that through machine learning and artificial intelligence?
Michael Greenberg: We like to be more of an open book. Machine learning is a bit of a buzzword. Our team comes from two different areas, at UCLA and Stanford, and we have some DNA from the University of Pennsylvania. They are two groups, tackling this through two different ways. What we use, is a form of conversion optimization, which uses a new kind of clustering. We build look-alike audiences for businesses, based on University of Pennsylvania research. We extend those modesl we that we can predict customer lifetime value with 98 percent accuracy, sometimes as soon as a customer comes in the door.
How did you start the company?
Michael Greenberg: My original background was in theoretical physics, at UCLA. That's when I started my first company, ScaleFunder, which we spun out of the UC California system in 2012. We were acquired in 2014 by Summit Partners, and I ended up in private equity, post-acquisition at Summit Partners. That's where I saw the problem we are solving at Retina. Many businesses we were investing in were seeing their acquisition costs increase, and I met Emad, who saw that figuring out CLV was the only way out of this acquisition cost hole. We formed the company in 2017, and our first customer was Dollar Shave Club. We received venture funding from Comcast Ventures and Crosscut.
How was it that Dollar Shave Club became your first customer?
Michael Greenberg: We had friends that were at the BI team there, and they were looking to solve a very thorny problem. They were spending lots more than they would get from their customers. They were selling $1 or $6 items, but were spending $100 to mass market to that customer, hoping they would stick around. We manually went in and scored the data, and found the behaviors of their best customers, which allowed them to predict who those best customers were, and keep them around.
How is it you went from theoretical physics to business?
Michael Greenberg: First of all, it made my mother very, very happy that I went into business instead. I will say, is that private equity was almost like my MBA, in that it taught me how to scale a business efficiently. It showed me that, especially with venture backed startups and e-commerce, a lot of startups are going into an un-tenable space, because they're not paying back their costs. Coming from private equity, it's given me a way to look at this problem from outside the echo chamber.
So where is the product now?
Michael Greenberg: From the day of Dollar Shave Club, we now have dozens of customers. Some of the ones in LA you might know about are Ritual, as well as Madison Reed, a leading women's hair coloring company which is growing by leaps and bounds. They are using our technology not only for marketing, but also for financial forecasting.
What's next for you?
Michael Greenberg: We raised a seed round in September of 2017, and actually, this year, we have been production-alizing all of our models. We also are now offering Retina go, which allows any business do a one time, low class customer lifetime value scoring of their customers, which gives an automated analysis in a little over 24 ours. That shows businesses the power of predictive lifetime value scoring.It can give them a health check, especially if they're uneasy in the age of Amazon. We put this out there to show the power of this technology.
What kind of customers does Retina Go work for?
Michael Greenberg: I like to say, customers who have bigger-than-Excel data. We can work with long tail, B-to-B companies, B-to-C businesses with thousands, not just hundreds of customers. We work with any B-to-C company with over 10,000 customers, such as retailers and e-commerce. In the future, we hope to work in the insurance and fintech area.
Anything that you have learned that you did not expect, that has popped out of your models?
Michael Greenberg: Yes. The most expensive product is not the one that predicts who your best customer is. That's the one I've seen time and time again. People confuse average value with lifetime value. A great example of that, is Dollar Shave Club. We found that a $3 product—their Shave Butter—was way more predictive of lifetime value than what razer their customer bought. Those are the little things that are really interesting, which are counterintuitive, but which are a great use case. I think that the second thing people haven't been using this for yet, but should, is for customer service. We've started working with businesses to help them rank their customer service tickets, based on customer lifetime value. If you think about it, that makes perfect sense. You want to give your best and highest level of service to the people who will spend most in the future.
Finally, given you perspective on the artificial intelligence and machine area, where are we now with the industry?
Michael Greenberg: I think, with new regulations that California will be launching, GDPR, and other efforts, businesses are going to have to rely on their own data, rather than using external data. If you have heard people say that data is the new oil, I like to think that machine learning is the refinery. Businesses are going to have to get more value by refining their own oil. They are sitting on an untapped gold mine. We're now entering a phase, where everyone can have access to machine learning. It's not just the big boys, like Amazon, Facebook, and Netflix. It's now a level playing field, where there is a lot of untapped value, and you'll be able to get much more personalized experiences. That's the phase we're entering right now.
Thanks, and good luck!