Revolutionizing Personalization with Vara Kumar Namburu

This is Textron tv. Hi everyone. Welcome back here to Techstrong tv.

Our next guest is, it's a new first time guest new company to our show. Let me introduce you to Vara Kumar Naru. Uh, Vara is the co-founder and CTO of a company called What Fix.

Hey, Vara, welcome to Text Drug tv. It's great to have you on. Alan, thank you for invite.

Uh, great to be here. So I'm assuming this is the real background out there. This is in some virtual bay, we figure out in Jellystone Park.

Where, where are you? I'm in San Jose, quite to the San Jose airport. Okay.

It looks beautiful. And I actually, I was just out in San Jose. I was in Santa Clara, uh, yesterday.

I got home late last night here, back on the East Coast and um, was there all week. It was be, the weather was really gorgeous out there. There Go evenings are really good for walk.

It is Not too cold and really Pleasant. No, not humid. We went out for dinner a couple nights and it was, it was beautiful.

Anyway, far as I mentioned, you are the co-founder, CTO of what Thick. We're going to get into what, what, what fixed is in a minute, but let's talk a little bit about who you are and how you came to be the co-founder here. Yeah, yeah.

So the company has started by Karima and me. Uh, both of us worked together, I think, uh, since last 23, 24 years. We worked together in the same team, same product we have been working on.

So 2010 was when we started our startup journey. Uh, and it was a very, altogether a different product, 2010, and then we promoted to what p in, uh, 2014 roughly. So that's when what P started and then, uh, we grew from there.

Got it. Um, and what, what's your background? Yeah, I, I led up a programmer.

So for, uh, I really like, uh, coding, so that's my background being software engineering. Uh, so then, uh, now I, at Bot Fix, I lead our r and d and presales functions. Uh, but by heart it's programmer.

I get it. Alright, so what fix, what is, what FIX do? So, uh, a the idea of what fix is that, uh, what we believe is that, uh, uh, technology has to get user savvy, not the other way.

Uh, and we sure be expecting users to be too much technology savvy today, take any company, whether it is logistics, manufacturing or a delivery, anything that you take, those are all technology companies today. And technology is what is, uh, driving every one of us efficient, uh, and productive at what we do today. So including generative AI is helping us to be a lot more efficient and productive.

So the idea of what fix is that, um, can we make, uh, these technologies more easier for the users to manage and use? So that's a thought process. So the whole, uh, concept of what is to be in law of work for the user and can we help them in the process, uh, uh, helping them, helping them through the software applications and guide them, nudge them to the process in the process.

So that's a thought process of Wap Fix. We call this as something, uh, Tom, we use, uh, it's called Ization. The idea is that can you make all these softwares user I step?

So that's a whole, that's, that's what we do at wap. Uh, today we offer, uh, three products to our customers. So the best product is called Digital Adoption Platforms.

The idea of these platforms is that they come as a layer on the software helping guide, give guidances to the users, be it a new user, be it a current user, can we nudge them to do the right things in the software applications. That's a first set, first product that we offer. Second product that we offer is all around data.

So can we give a lot of data to product owners, our operations teams so that they can really understand how people are actually behaving in the application? Are they able to use the application in a comfortable way? So that's a lot of data points that we give it out.

And the third application is all about, uh, uh, can we give users a, a safe place, uh, to play experiment, uh, the get trained on software applications, so that's called applications simulation area. So these are the three products, uh, that we offered to customers today. Predominantly two use cases that we, two kind of users that we saw.

So the first set of users are, let's say you are a company, be it, let's say you're an insurance company, you have an insurance portal for your, uh, your insurers. So what could be on it, making sure that the users are self out on the software. That's one type of, uh, use cases we address.

And the second type of use cases is you provide a lot of technology to employees. So can we make sure that these technologies are well adopted and used by the employees, be it, let's say a driver, uh, driving to deliver, um, parcels. So they, a lot of technology that they need to use today.

So these are the two kinds of users that we solved there. Excellent, excellent, excellent. Um, if it's okay, let's jump into what was kind of our topic of discussion is you guys are recently, uh, was it, was it a full on patent or pending or Yes, it's a patent approved.

Yeah, Patent approved. Fully approved, yes. You guys were, uh, awarded a patent.

Why don't we first, you know, what, what is the patent on? Yeah, Yeah. So we have a roughly 20 patent file and five approved today.

So broadly all around the same theme that I talked about. So be on the software applications and how do we make sure that people, uh, are held well. So the specific patent that we got approved there, which we wanted to talk about, which is, uh, about personalization.

So in general that the complexity always in the organization is that the same software application is used by many different types of users in the company. And often it is very hard for someone to bucket these users into different group and give them very personalized experiences to them. Because let's say you may have a, let's say a large insurer, you may have underwriters all over, uh, the country, but the underwriter in California may be working slightly different from the underwriter in, uh, um, uh, Colorado, or an underwriter who is doing, uh, automobile may be doing very differently from an underwriter who is handling home insurance.

So generally it is very hard to categorize people in the application, and often user groups and roles doesn't go to that extent of, uh, categorizing them to the granular level. So the idea of this personalization is that by looking at pattern of how they use software applications, can we cohort users into buckets automatically? So if we can cohort the users into buckets automatically, the outcome of this will be that we will be able to personalize the things that they may want in the software.

We can recommend them the right things in the software application. So that's the whole concept of this patent. So can we bucket users in the, uh, in a software application automatically, and then can we help them see content, which is very relevant to them?

So that's the crux of this patent. I know a little bit about patent patent law having gotten to law school and stuff. This wasn't being done before you applied for the patent?

Yeah, so the, what's done in the past is, uh, there is a personalized content. He's been, he's very normal, be it Netflix to, uh, Amazon Prime to, so it's very, very common where you could personalize content, but what is unique in this patent is that you group people automatically into the cohorts by looking at patterns of how they're using software application that is unique. So that is what is special in this patent, uh, but otherwise serving personalized content is it has been there for a, for a long time.

So the uniqueness here is, uh, uh, just being able to look at software usage pattern and be able to cohort users automatically, that's what is unique in this. I got it. And, and what's, you know, what's the advantage in being able to do this?

How does that translate into what, you know, the bottom line as they say? Yeah, so the, the finally how it helps is that, uh, let's think of a scenario like even we were talking about izus. Let's say that, uh, the partner in Florida started to see some surge of, uh, home insurance maybe because of something that is happening naturally.

So what happens, uh, when this algorithm is in effect is that it automatically identifies that this cohort of the users require guidance on this particular kind of things because there is a sudden pattern change in the behavior of these users. So that is what it is able to identify. And by identifying data, it is able to surface right, help contend to the users.

Let's say in this particular example for the Florida underwriters, what will start ing about audio underwrite home in, so in Florida, but some specific nuance nuances, so it is able to bring it up because it is able to, in runtime, it is real time, it is able to understand the pattern changes of usage of that cohort of the users. So the got it out of this will be that the users will be able to, uh, file the, uh, content very easily and be able to take advantage of that with which the application engagement will increase, so with which obviously the company's top line will get better. So there's a, uh, there's a whole set of things that will have an impact.

Got it. Now I, I saw the number being thrown around there in our notes that it increases application engagement rate by 5%. Is this wishful thinking or is this based upon, you know, your observations with this?

Yeah, Yeah. So this was based on the measurements we did with few of the customers. Uh, because it, I mean, every innovation that is done at Twix, we try to go with a few customers first, and then we observe monitor, and then we take it to the broader customer segments.

So usually these are the, the tests done with few of the customers on before to us as after scenarios, and then be able to differentiate and come with this number. So that is the number that you are seeing. Got it.

Um, now how does, how do people engage with Watch Fix? Yeah. Yeah.

So the way people engage with wafi is that as a user, you wouldn't notice that it is wafi, but you're just getting into the software application as usual. Let's say in this case, maybe you are getting into June meeting, then you will see what messages from WAP fix automatically on Zoom itself. So whatever is the application that as a user that you are getting into, you will start seeing what p experiences on it automatically.

And those experiences can be helping new users to get into the software, or it could be nudging power users to do things in a slightly different way, or it could be recommending them the next step so that they can be a lot more efficient. So there variety of things that WAP will show up, uh, on top of those applications. So we could be at an operating system level, means I can just log into my Windows laptop and then you can start seeing WAP directly, or it could be on desktop, mobile, web, any application that we, you will just see wap, uh, on top of those, think of us like a layer.

I'm trying to think. This company I interviewed WalkMe, uh, are you familiar with them at all or? Yes.

Yes, we are. We are roughly in the same space in the one, the product we offer dap. So that's, we are in the same space, uh, for those products.

Got it. All right. So now I, I think I understand it there.

Um, is there any limitations as to like what applications you work with and which ones you don't? Yeah, today, in terms of the applications which are, uh, laptop, desktop based, there are no restrictions we could be on technically on all, uh, applications. We could work on everything.

So mobile and there are some restrictions such as, let's say the mobile AppSec that are provided by third party developers, we will not be able to inject into it today. Mobile OS has restrictions on, on what you can do. So because of the mobiles restrictions, there are some restrictions on what we can do in mobile, but otherwise, uh, otherwise it's technically any application that we can layer on That makes it easy.

Good, good. Uh, you know, we never mentioned the website, Uh, website of website Of what Fixx for people who want to go get more information. com.

So that's the what Fixx, uh, website. W-H-A-T-F-I-X? Yes, that's it.

com. And it, you've been at it for about 10 years now? Yes.

Wex You've been earlier before that. What Fixx? It is already around nine, 10 years already.

And even before that, uh, we have four years, uh, roughly before that, uh, uh, we've been in the startup journey. Got it. Well, congratulations.

Congratulations on the patent as, excuse me as well. Keep doing what you're doing. Right.

I mean, oftentimes we get companies on here and our audience will say, oh, this must be a new company, and overnight, you know, success. I've never heard of them. And then you find out, well, they've been down for 10, 12, 14 years, and yes, nothing gets done without a lot of hard work, and I know that.

Yeah. So congratulations and, and thanks for coming on Text Drunk TV and telling us about this today. Thank you, Ellen.

That's exactly, it is, that's a spin slack. It is just, uh, overnight, but it is actually, it's a, it's a lot of grand, uh, hard work. Uh, that's when it'll show off.

It's, you know what they say that the days long and the years are short. God, It is. All right, RA Kumar Naru Naru, uh, here.

Co-founder CTO With what Fix On Tech Drug tv. We're gonna take a break. We'll be back in a minute.