https://youtu.be/tleD72Lj1r0
Sharehk Shaikh, the founder of CleverX, the audience discovery platform for market and product research teams, and the co-founder of Reflow AI, a company that provides AI agents to build and run your HR tasks and workflows. We discuss about the importance of understanding customer needs and building a complete solution, the Create Familiarity Framework, the MVP fallacy and the vision for Reflow AI.
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Create Customer Familiarity with Sharekh Shaikh
Our guest is Sharekh Shaikh, the founder of CleverX, the audience discovery platform for market and product research teams, and the co-founder of Reflow AI, a company that provides AI agents to build and run your HR tasks and workflows. Sharekh, welcome to the show.
Yeah, it's a pleasure being here, Steve. Thank you for having me.
Well, it's exciting to have you because you are a tech founder, a multiple tech founder, and you've got some really cool technology up your sleeves. So tell us a little bit about your journey. What does it take to become a tech founder? How did that work out for you?
Yeah, it's been quite a long journey. You know, I was born and raised in a very small town back in India. And at that time, I had no idea I was gonna be a tech entrepreneur or build those companies, but was very lucky to have amazing parents who gave us great education. And I was also very lucky that I lived in four countries when I started my career. So I did my computer science engineering back in India from a pretty good school and was lucky to get jobs with some amazing companies across, you know, different continents.
So I worked in Dubai for many years, worked in Singapore as well, and then moved to the U.S. a few years back. But my last job before starting CleverX was working for Gartner Research, which is one of the largest technology research companies in the world, and had the opportunity to work with really smart people there. You know, understood the world of research, understood the world of how, you know, the trends in technology are shaping how we live, work, and do things in general in business. So that was a very, very fascinating experience.
And I think that was a segue for me to get into building my own company because I saw a bunch of problems in that space and we wanted to solve them. And in the last three years of the company, the company has grown like at least tenfold. It's been doing incredibly well. We have some biggest names in the world who use our platform to conduct research. Yeah, so overall it's been a long but a very exciting journey across different places and geographies and meeting hundreds of people along the way.
So it struck me that on LinkedIn the description of the company is not an audience discovery platform but the audience discovery platform. So audience discovery platform. So tell me a little bit about why you feel that this is the platform, how are you different? And what is the problem that you're solving?
Yeah, so for the audiences here on the podcast, right? I think a lot of people don't know the scale at which market research happens, especially in a country like US. So close to 50 or $55 billion is spent on just conducting online surveys, be it business to consumer or business to business. And the problem with that industry is the data is very blinded, which means that when you as a researcher, you're trying to conduct online surveys, especially in the B2B space where you're spending somewhere around $100 to $200 per successful response, you still don't have an idea who your respondent is.
And that is a very, very difficult position to be in for a researcher, be it in an enterprise or an end user or a market research company, because when your customer or your board asks you a question, how confident you are on the insights that you've achieved, the answer usually is not so great, because I really don't know who these 100 or 500 people were who participated in my survey, I'm just going on the fact what my panel provider or my other vendors have told me that this is legitimate data.
Market research isn't just about numbers; it's about understanding the people behind the data.Share on X
But if you look at the industry, 40% of fraud happens in every online survey project because of the data being blind. And that is the problem we're trying to solve. So we are flipping the model completely, where we're making 100% the identity of your respondents 100% transparent, so you have the trust in your insights. And you also have the ability to even connect and message and talk to every single respondent on your survey. That makes it really powerful for multiple reasons for a researcher, because it not just only gives them the confidence, but it also gives them the trust in their own insights.
And that is the reason we are very, very unique player in this space. I don't think there is any other company that does what we are doing at scale and in a self-service model because our platform looks very much like LinkedIn, but it also gives you the tools to conduct research in different ways with a very known senior audience.
Very interesting, interesting. So I've done something similar for my books when I was researching what would be a great cover, I did some A-B tests and as a company called PICFU, which does this kind of research, and they kind of stratify their audience by age. And I think there are some other, you know, some other criteria. I can't remember what it is, but I think it's about consumption of certain products. And I was wondering how accurate that is. And how I could maybe more or less target my research, because I really would have preferred to focus on just my target market, but it was not available, could not be stressed by that much. So I wonder what is it that you guys do differently from companies? And how can you get closer to the identity of your of your audience or responders?
Yeah, that's very interesting. You mentioned that because the problem that you shared just now, Steve, is the exact problem even for large enterprises. And they are struggling to find the right people who have a certain behaviour or buying pattern or influence to buy multimillion dollar products for business purposes. And it's difficult for them to find these people. So you can actually locate these people on LinkedIn. The challenge is trust on LinkedIn is very low because of two major reasons.
One, I don't want to interact with a stranger because I don't know if like how my data is going to be used. The second problem with LinkedIn is a lot of spam. So you get a bunch of these requests, you don't know who to trust. Even if you're serious about like participating in someone's research work, you don't have a monetization mechanism. If I convince you somehow to participate in my online survey and promise you to give $100 for it, and if I do not give you those $100 after you've completed the survey, you have no one to talk to.
Like there is no way to find out like how you're gonna get your money back. Right? So those are the reasons which allow our users to have the trust in our platform, because that's something that we've taken care of really, really well. Going back to the point about how do you know about this audience, our platform is very transparent. So you can actually sign up on the platform and search for people by their location, their areas of expertise, by the companies that they've worked for before. So it very much looks like a LinkedIn sales navigator with all those different filters. And you get identity of that person.
You also get to see their LinkedIn profile too. So you can actually know that this person is who they say they are, but it goes one level beyond that, where you have the ability to connect with everyone or message them and have a chat with them before you even invite them for a research interview. So your expectations are really met well because you might have five specific questions. Let's take an example of your book, right? You might say, I have the five options for my book. This is what my book is going to be about.
And this is what I want my users to get when they look at the cover page of my book. And there could be all of those five questions, three questions the person is like really great at, you know, giving you feedback or insights, but they might say like the other two questions I really don't have knowledge. So you know what you're gonna expect when you get into a conversation with a person like that. And you know that that entity as well.
So you know like their age group, their age, you know who they are, their senior business execs who care about strategy, and they are the right people who might buy a book or recommend your book to other people in their peer network. And I think that makes it really, really valuable for researchers so that transparency is what, you know, we are known for and the quality of people that are there on the platform, yeah.
Transparency breeds trust in our platform, addressing the challenges of trust and data security.Share on X
Okay, that's amazing. So we can talk more, we will talk more about this, but I like to also cover this topic of the business blueprint that this podcast is about. And in our prequel, we talked about one of your favorite frameworks called the Create Familiarity Framework, which may be a good segue from what we're talking about here, about people trusting people that they can familiarize themselves with. So how does your framework, the Create Familiarity Framework work?
I think I remember the first conversation we had even before doing this podcast. It is really, really important for brands or people who have decision-making authority to know a company before they even get into a sales process. What I mean by that is things are not like they were 10 years before when it came to buying or selling a product. People would pick up a phone call, make a call to you in the next 10 minutes,
