Sramana Mitra: What else is interesting strategically in how you’ve navigated the story so far? How many customers do you have now?
Vincent Yang: I think we have four or five dozen customers. The growth rate is actually pretty fast.
Sramana Mitra: What’s the pricing model? What’s the business model?
Vincent Yang: The core of EverString is to provide the predictive model. For every client, if they have multiple products, there will be multiple models running at the same time. For every single model, there is a predictive platform fee. It depends on the scale of the business. For some clients, we charge $30,000 to $100,000.
On top of the model, it really depends on what application you want to use. We have some clients using us for funnel optimization – they use the predictive model to prioritize their inbound. They pay additional fees for this application. Some clients use our model for new lead generation to analyze every single company out there. Based on the volume they want during the year, they pay for that as well.
Sramana Mitra: Back to my question about other strategic moves, what else do you want to share?
Vincent Yang: One of the things that’s very interesting is every single company needs an artificial intelligence brain that analyzes every single data. We’ve made a lot of moves on that part to integrate more and more to the client’s workflow. Initially, we integrated to their CRM. Later on, we made a strategic move to integrate to all of their marketing automation systems. You can imagine a lot of that. You have browsing behavior on the website. They have payment systems. We wanted to sieve through every single data.
On the other side, how do we crawl better? How do we analyze better the global data? We are making more and more development on the natural language processing involvement and scaling up our cloud infrastructure. We are doing more and more partnerships with publishers to analyze more behavioral data. Those are all the strategic moves that we’ve made in the past to make better the connection between your data and the world data.
Going forward, we want to go deeper and deeper into artificial intelligence. Right now, we are able to predict very well who the next customers are. There’s a lot that an AI can help you to predict. When is the best time to engage? How big are the deal sizes? Right now, most of the decisions are made by intuition or made by rules if you look at Marketo. Those are great ideas. How do we use the machines to further optimize the conversion rate and efficiency? You will see more analysis and more and more applications.
Sramana Mitra: What about metrics? Obviously, you are trying to turn the marketing organization into a more metrics-driven organization. What metrics are you coming up with?
Vincent Yang: Very good question. There are a couple of metrics that will make a big difference before and after using EverString. Number one is conversion rate. We are tracking the conversion rate in every single stage before using EverString and also after using EverString to compare the lift. As of today, we have seen a significant lift. The average is about three to five times. That’s number one.
Number two is about days to close. Before you use EverString, the sales and marketing have no idea who’s the best audience. They spend a lot of time talking to bad leads. Now once you’re laser-focused on the best leads, the sales cycle is going to shorten dramatically. We are starting to see a 40% to 50% decrease in the sales cycles. The final one that combines the sales cycle and conversion rate is ROI. What are the revenues that you are generating? Those are the three fundamental metrics we are tracking.
Sramana Mitra: Very interesting. As you can tell, I am deeply interesting in the subject. Thank you for your time.