Maximizing Customer Lifetime Value – Vinod Vasudevan, Flytxt

This is Textron TV. Hey everyone. Welcome welcome to another text on TV segment.

I have a new guest who's ever been on our show before to introduce you to his name is Dr. Vinod vasudevan. And if I mispronounce that I apologize I practiced a whole bunch before but I do the best I can.

Dr. Vassive vasudevan. Thanks for joining us on techstar TV.

Oh, thank you. It's okay. Nice to have you here if it's okay, I'm gonna call you the Newt and renewed.

Why don't we start off with maybe a little bit of your background for our audience? Ellen thanks. That's fine.

Just call me. We know that notes it very easy for everyone including the listeners and the viewers. I have I come from a technology background.

I did my bachelor's Masters and computer and and PhD in neural networks from the Indian Institute of Technology correct board. And then I have progressed in my career from basic research through applied Research into commercial activities and sort of alternated between large corporations and small Enterprises and startups that NTT in Japan the land Communications in India, which are very large corporations worked in a research lab in Singapore did my first startup in the early 2000s in the day area and this is my second startup now where I am not talking to you from perfect. That's that that is a well-rounded resume CV right there.

So that's great. Well, you mentioned you're at your second startup. Now is it in the Bay Area?

I assume it's in the Bay Area or You know, this is based in Netherlands. Oh, okay. Let's start that wasn't the baby.

Yeah, and this one is in in Netherlands. So Japan Singapore India the Bay Area Netherlands. Seen the world the idea.

Yes. I have iconic underneath that I have been around the world. Yes.

com, you know about eight or nine years ago. I get a chance to go around the Rosemary about me will be an Amsterdam in April for the coupon Cloud nativecon. Europe is gonna be an Amsterdam in April and looking forward to it.

It was supposed to be an Amsterdam two or three years ago, right when covid I guess was 20 20, and so they're coming back. anyway, let's Absolutely. Well, we'll be doing video live from the event.

So if you're there come in and we'll sit down and do live stream video, but let's talk about the new startup if you wouldn't mind share with our audience a bit. You know this this this startup, but we call flight test. It's I said several years ago.

And basically the problem hit me or the problem set at rangling me when I was working in my previous job at Reliance Communications. And and then the problem was basically that you saw across many Enterprises. Where the transition from a focus on having large number of customers?

To a focus on getting revenue and profits out of those customers was always a big struggle for the industry. com Industry. We saw that in the Telecom industry in the banking industry and operate we see it in the winter industry.

And it Advanced we had launched a kind of an app store World Garden service. This is in around 2003 and that was for initially was free of charge because we just wanted to acquire customers and usage and very quickly. We reached about a billion transactions per month.

For and this is in India is a huge country. So here you had a lot of people using it too. But the moment we started charging the usage sort of like no it came down like this sure and then we had to study for several years with trial and error to shut up bring it back to assemblance of profitability.

And when you look around there is so much information and data about the customers and maximizing this value or revenue or profits from that. It's basically an optimization problem. So if you have data a lot of variables and an optimization problem, you should be able to have a structured solution.

But it was almost like Black Magic. It was an art form rather than a science to go from customers to revenue and profitability. Those who mastered the art survived and others sort of fell back a lot in this business.

So since then it's been it's been in my mind. You know, my my CPU used to be working with me back then too. And so we were chatting and we had in this mind saying okay sometime we want to create a structured solution to this because both of us have a background in algorithms and Ai and optimization and why can't we create a solution for this?

So that's really where the sort of the aha moment came in to say. Okay fine. We can solve this problem and we should do it sometime.

That's how we we talked about it then about a year and a half later. I had a chance meeting with the for European entrepreneurs turned investors sort of a serial entrepreneurs who became serial investors and you know, sort of birds of the same feather clock together, so we started talking about Business and start up and what next and sort of the idea clicked? What was there in my mind what sort of you know presented with what they wanted to do and we converged on this third process to say.

Okay, let's look at providing a capability for businesses to optimize their customer lifetime value and using analytics. That's the way we crafted then and Within about a year's time, we sort of put together the different pieces and the company was pumped. That's how this this company got started a problem that was there in the industry, which was there in the back of the Mind the chance meeting with investors things resonate and then you Start the business.

You know from such Serendipity businesses are born sometimes right? Yeah, that's true and the beauty I mean, yeah, I mean things happen you have a chance meeting and you had an idea in the back of your mind. They like it the next thing you hear.

We are. I just want to make clear to our audience. The name of the company is flytext.

It's f l y txt. And Tony behind that too very quickly, you know, the the investors who might they had a company which they started in the year 2000 which was called flight test. And they had sold that business, but they like the name so much.

So therefore they retained the name. Then when we wanted to start a new company we said okay fine. Why not use the name you guys like the name you have retained it with you.

So in despite selling the business, so let's use that name. I learned I love it. That was that was the reason I mean I get asked us to probably choose the name and this is how we chose them.

Crazy, oh, right. Yeah, but yeah, it smells as sweet. So.

You know, here's the thing. Like you I've been in business a long time serial entrepreneur. com and then I Started a hosting business in like 96 and rode that through I sold it.

com thing. Down through that cybersecurity after the bubble burst and you know been doing stuff ever since. One of the things in basic business models in the internet.

Anyway internet age. I've seen changes, you know used to be very direct model retail. Let's call it.

I gave you a service. You paid me dollars for that service. That was my Revenue.

I had my cost of goods sold my cost of sales. And it was very it was relatively simple equation. Here's my profitability, right?

Here's my email so forth. in today's age where we have open source business models and there's so much, you know, quote unquote free software and free services that we offer, you know, a lot of people like just like your experience as soon as you start charging the usage goes true right down right down the drain because people People have an expectation that somehow this should be free that the fruits of your you know, you look the fruits of your labor. That you're making available to them should be free yet.

They don't deny. Yeah, you're entitled to make a living. You're entitled to charge.

They just don't charge them. Right because they the expectation is free For too many people on the internet today. And so we need these alternate.

models How do we monetize? That's true. And it sounds like that's kind of where your expertise where where it all comes together here.

Yeah, that's right. So so no, you take a typical a internet business you take a typical internet business. So you take a typical fintech business today or even a no a digital content business.

People wanted to transactions on the fintech platforms. They want to consume the digital businesses content as long as you are given discounts and you are given like, you know low charges and all when you want to Once those service providers those companies start charging you for for a regular cost of business cost in if you want to call it that They need to find inventive ways to be able to balance between keeping their customers and generating or maximizing the value. They generate out of the customers.

And what we do is we provide those companies our software using which they can do this in a structured optimized fashion. So if you take talk about a telecom operators when we work with in large numbers or with some fintex or banking services, They're faced regularly with the questions as to I mean, like they have a lot of customers. So which customers can I look forward to generate more money from or to increase their spend which customers are likely to leave my service.

Who can I retain who should I retain because the ones I retained should be valuable for me. So essentially it continuously answering questions about how can you generate antational value from your customer base by by keeping them for a longer duration with you and for generating? I mean making them spend more on your products and services that is is the problem that we help Enterprises to solve.

So in a sense To retain customers to sell them more upsell and cluster them more and in their process generate higher customer lifetime value. I mean you talked about today's businesses. A lot of businesses traditionally where working on subscriptions and usages and with the subscription economy growing more and more businesses that are coming into that that model I mean and when you talk about a subscription business, you have a ongoing relationship with your customer and the value or the profits that you generate from.

The customer is not about today or this week or this month. It's basically over a whole life time. And how do you maximize that?

How do you optimize this is a complex problem. I mean Speaking from a man from an algorithmic perspective, which will appreciate I mean, it's an intractable problem and the only way you can solve it is to find a very good solution using. Some approximation technique, which is an AI techniques are commonly used to find very good solutions for such complex problems.

And that's what we decided to use as our mechanism for solving this problems. and one of the things that makes us very makes us unique in this basis. That when we started the business we knew we had to develop fundamentally new technology.

But we also knew that we are developing new Ai and AI needs to be trained and trained well on large volumes of data. So in the first eight ten years of the business we focused on developing the IP we focused on working with some of the largest consumer businesses in the world across the world we had access to Consumer insights or insights from more than a billion and a half. Customers across the world literally several trillion real-world data samples, which we used to stay who's insights.

We used to train our AI so we have one of the most well-trained AI in the customer Life Time Value maximization business, and we also developed a process by which the AI learns at different customer sites, but doesn't have to bring the data to the common place is nobody will let you bring their data to your premises. So you learn different locations and the learnings get combined but not the day. so it's like that that's what what the the USB is and that's the USB which delivers value to our customers and partners when we deliver our Solutions.

Sorry, no problem. We're not what are the kinds of things you're learning the what? What are the The insights that the AI or patterns or whatever you want to call it that allow you then to serve customers better better monetize create a better experience Etc.

So let me let me I mean for all we was let me try to give a picture that's a simpler picture of that. For instance you look at you you talk about any Enterprise. I mean you the Enterprise has got a set of products and services that the customers consume over a period of time and then over a period of time.

They're going to generate the value for the Enterprise. So the learning go from very basic one says to at what time of the day does your customer like to consume? What kind of service?

Or what combination of Production Services is this particular customer likely to consume at what price levels would this customer like to do? So these are the kind of things that you try to infer and learn from your data and predict for the future so broadly, I mean you do. I mean if I if I if I am talking about watching Netflix movies or the equivalent of that what genre of movies do you like in the weekends versus what genre do you like on the weekdays?

Because we can see maybe with your kids and you like a certain different kind of movies and be teaching maybe watching alone or with your spouse and then that from kind of I mean, what movies do you like during the holiday season? I went to the extent Netflix doesn't use it. But you even know which parts of the movie you Skip and which parts you probably rewind and watched more than once.

So all this that is an example of that service. Now you talk about a telecom the kind of things is what kind of content do you watch on your mobile phones or what websites you visit there. Do you make long distance calls in the evening?

So during work hours. Do you what kind of usage patterns you have in the weekends? And that would like to lead to what are you likely to spend more on and what are you like to spend less on and how can we give you more encouraging process or how can everyone reaching my product portfolio or how can energy my pricing structure for that?

So it's a totality of decisions that go with. customer intelligence product intelligence and then convert combining these to generate recommendations actions and the predictions that lead to higher customer lifetime when Okay, let me get a little business here. How does one engage with flight text?

How is this offering? Sold are offered to customers. So we Supply this all as a software as a service management model, so we provide the solutions directly to our customers.

we also Supply our technology embedded with oracles products as well as saps products the Oracle and sap are two of the leading customer experience in CRM providers and what I refer to earlier as our unique technology, so that technology is a gap or it feels a gap in their products or the products of similar companies. And therefore that's one channel through which we deliver the project. And and our engagement model with our customers is such that we focus on ensuring that the customer.

Derives the benefit out of it. We even introduced a success fee component into our Revenue model. So that the customer.

And the customer stand as a customer gains more we on a part of that or we can think of its vice versa that customer doesn't pay as a certain part of our compensation unless they they make certain level of gain out of it. So that's the yep. com.

That's correct. Is there a free trial or anything that people can can check out we do offer our end up. This is an Enterprise product.

So the the I mean Executives from an Enterprise for interested to explore our product can come to our website and request a demo for them. Do they get a login to a demo service and they can experience the solution for themselves? And we also do more detailed Pilots for Enterprises in to understand what they could benefit out of this.

Perfect. But not we are out of time. I I try to make sure we hit everything here that anybody out here might want to look to help us get started.

You know the whole AI in trying to help serve better. It's fascinating. a lot of people think it's a little snake oil yet or it's not ready for prime time yet other people are saying hey, it's getting better every day.

We'd love to keep in touch with you and continue to hear how you're improving the process and how you're helping fintex and other Enterprises. Yeah, I mean you I mean you get me talking about AIA and talk forever. So I will not start doing it, but we still got our time up today not to worry.

I'm sure we'll do it again. Yeah fly text FL why txt guys right here comes We're gonna take a break here on Tech struggle. Be back in a minute.