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“Working at a startup is like working and learning in dog-years.”

Founder and CEO of Chubby Brain

Interview by Kevin Ohashi of KevinOhashi.com
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Anand Sanwal is the Founder and CEO of ChubbyBrain. Anand’s previous job was managing a 50 million dollar Innovation Fund for American Express. He also worked at one of the most well known bubble startups, Kozmo.com, which received the largest amount of funding in NYC history for a tech startup. He worked with a small team to open up the European market for Kozmo.com. Along with his corporate and startup experience, Anand also has an education from Wharton (University of Pennsylvania) along with a Chemical Engineering Bachelor’s of Science. Anand’s latest venture is ChubbyBrain, part of CB Information Services (the parent company of which he is CEO).

ChubbyBrain has created a tool called the Funding Recommendation Engine (FRE) which is a data driven tool to help entrepreneurs level the funding playing field. ChubbyBrain has a large database of venture capital companies and angel investors along with their investments. FRE takes information from entrepreneurs about their company and matches them with investors who actually match their profile based on past investment history. It gives savvy entrepreneurs the ability to do reverse due-diligence on their potential investors. The FRE is currently in an alpha stage but has already been featured by ReadWriteWeb, Business Insider, Xconomy, TechFlash and others.

For MO.com readers looking for funding, the first 50 who enter invite code “mostartups” (no quotes) at www.chubbybrain.com can give it a try and maybe identify the perfect angel, VC or government grant provider.

MO:
How does the Funding Recommendation Engine work?

Anand:
Investors often talk about “pattern matching” when they talk about assessing investments. The FRE is pattern matching in reverse. The reality is that past investment behavior is the best indicator of future behavior and so the FRE takes inputs about an entrepreneur’s business (industry, funding required, location, stage, experience of entrepreneur, etc) and then algorithmically matches those inputs with investors/funding institutions based on the investors’ actual investment history (not what their website says). The FRE uses data from CB Insights and culls through the investment history of 8000 investors (VCs, angels, gov’t grant programs, family offices, pvt/growth equity, banks, etc) who’ve made at least one investment in a private company in the last 2 years to algorithmically assess fit with an entrepreneur’s venture.

Founder and CEO of Chubby Brain

MO:
What are the primary benefits you hope entrepreneurs get from their use of the Funding Recommendation Engine?

Anand:
• Investor serendipity- Use FRE to uncover investors that entrepreneurs may have never have heard of or discovered. With 8000 investors in our database who’ve made at least one investment in the last 2 years, it’s fair to say that there are many new investors the FRE can uncover for an entrepreneur.
• Reverse due diligence – Arm entrepreneurs with information on investors so they can determine if that investor is suitable for them, i.e. have they invested in a competitor for example? Reducing the information asymmetry which currently exists is good for both entrepreneurs and investors as the right entrepreneurs pitching the right investors is a win for both sides.
• Efficiency – The FRE does the work of identifying investors that would otherwise take days/weeks and does it in 5 minutes

MO:
Tell me about your education, you started off with chemical engineering and quickly transitioned into business. What caused the transition? Has your chemical engineering background served you in unexpected ways since you made the transition?

Anand:
I graduated from a dual-degree program at the University of Pennsylvania called the Management & Technology Program in which I received my degree in Chemical Engineering at the same time that I was working towards a degree from Wharton. So as a result, there wasn’t really a transition. I always knew my interest was on the business side but had an interest in engineering. More generally, engineering equips you with a set of skills on how to attack and dissect problems that is particularly valuable in a business context.

MO:
You’ve spent a lot of time at two of the top business schools in the world (Wharton and Harvard). Can you share some of the knowledge imparted on you during your time spent there? What is the real value of the education from a name brand institution in your mind?

Anand:
Of course, access to great professors who are leaders in their field is a tremendous asset, but academic learning is not the key value in my estimation. The best part of attending the University of Pennsylvania / Wharton is the network. Some of my closest friends are from my time there and they’re folks who are amazingly successful, helpful and inspiring. And there are prominent alumni in most any field and if I reach out and say I’m a fellow Wharton alum, they’ll usually take the call. And of course, being around a group of smart, success-driven people also forces you to raise your own game which is a good thing.

MO:
Could you tell us what it was like working for Kozmo.com during the boom? Kozmo received huge amounts of funding and ended up collapsing after you left. One of your responsibilities was raising money, was this the first time you raised money? Did this experience in any way influence your decision to create ChubbyBrain?

Anand:
Working at a startup is like working and learning in dog-years in that what you do and accomplish at a startup is the equivalent of what people in larger organizations accomplish in much longer times. That’s not a knock against large organizations – it’s just reality. It has more to do with being in a startup where there is, especially in the beginning, a scarcity of resources, skills, time, etc. And so if you’re good, you do a bit of everything as there is nobody else to do it.

Kozmo in particular was an awesome ride. Myself and four guys were sent to London to launch Kozmo Europe – visions of grandeur I suppose. We lived together, worked together and it was a bit frenetic throughout. I was involved in setting up distribution facilities, signing up partners, fundraising – everything. I learned a ton and made some great friends.

As for Kozmo’s failure, it was unfortunately inevitable. You can’t sell something for less than it costs and hope to make it up in volume. It’s a pretty basic economic principle, but in the euphoria of 1999-2000, a bunch of lost our minds – myself included.

In terms of the influence of Kozmo on ChubbyBrain, that was a long time ago so it didn’t impact the development of ChubbyBrain in any direct way. I think what Kozmo solidified for me was the startup/entrepreneurship bug. So even though I had an amazing time at American Express after Kozmo, I always knew that building something along with a team of others was important to me.

The development of ChubbyBrain is much more the result of my time at American Express where I led the company’s $50M Innovation Fund. And in that context, I got to see firsthand that information on private companies and those that invest in them is pretty poor. And so we started building data around private companies and their investors – venture capitalists, angel investors, private equity, etc. And the beauty of data-driven businesses in our view is that you can use the data in all sorts of interesting ways to develop different offerings.

And so ChubbyBrain is one of these offerings. It tries to address what we feel is a severe information asymmetry between investors and entrepreneurs by using data in a way that will help entrepreneurs uncover investors who fit their business based on their actual investment history – not what they say they invest in.

MO:
How are the FRE and CB Insights connected?

Anand:
CB Insights provides the bulk of the data that drives the FRE and both CB and CB Insights are part of the same company. CB Insights is primarily targeted at institutional customers, i.e. private equity, investment bankers, venture capitalists, angel investors, advisors/consultants. The common thread in all of our offerings, today and into the future, is an extreme orientation towards data.

MO:
What is the business model behind ChubbyBrain?

Anand:
We’re fortunate that we have CB Insights as our primary revenue generation vehicle which allows us to be focused in the short-term on developing data-driven tools that will be beneficial to startups and small and medium-sized businesses as part of ChubbyBrain – and not have to focus on monetizing CB. That said, given some of the buzz and great reviews CB has received, we have seen interest from sponsors who want to get their brands and products in front of decision-makers at high-growth small and medium sized businesses. Given this, we will selectively partner with firms who we think have a compelling value proposition for entrepreneurs/businesses. One partnership we’ve already struck which we’re really proud of is with the NYC Accelerator for Clean and Renewable Energy where we are looking to help the city identify promising clean tech companies that can be attracted to NYC. It’s a perfect fit with us given what we do, and given NYC ACRE’s financing and other services, it’s potentially an awesome way for a startup to accelerate their development in one of the greatest cities in the world (if not the greatest).

MO:
Is there any sort of rating or feedback system planned for investors on ChubbyBrain?

Anand:
It’s a good idea. There are other sites out there that do it now so our preference in the short- to medium-term would be to continue to develop offerings which are data-driven. We’ve got many other ideas in the works that keep with our mantra of being data-driven.

MO:
You focus on data, how do you collect your data and what sort of issues have you run into technically as well as legally with regards to data collection?

Anand:
With regards to collecting data, we have built aggregation technology that looks at unstructured (and in some cases structured) sources of public information and parses out the relevant elements we’re after. We look at really anything which will have info on investors and the companies they back including but not limited to:
• press releases
• social media
• company websites
• investor websites
• regulatory filings
We’ve gotten quite good at this and our code or what we like to call “the machine” is able to do the vast majority of this work now although we started doing it manually to understand the patterns that we ultimately codified. The old model that many large lumbering incumbents still use is researchers trolling around doing this by hand. We think that model is going the way of the dinosaur.

Beyond our parsing and aggregation technology, we have investors who directly send us news of their investments. They have a natural interest in ensuring our data is up-to-date because it is their investment activity which drives our FRE algorithm. And so if they want their brand and firm in front of startups, ensuring their data is complete is ultimately beneficial to them. For an investor, the Funding Recommendation Engine is the easiest way to garner deal flow. Also based on the entrepreneurs/startups who’ve gone through the FRE, I can say that we see a very high caliber of entrepreneur/startup in general. While the FRE is not taxing in terms of effort, the fact that it takes 5 minutes and asks some important questions tends to weed out folks who are not serious about their business. This is a good thing for investors and they’re starting to see that. In the last week, we’ve had several prominent venture capital, super angel, angel investor groups and seed accelerators give us data to ensure they’re accurately being considered in the FRE.

We’ve also sent a few promising startups we’ve seen to investors we know and are aware of a couple of meetings that have already occurred. This is powerful for entrepreneurs and investors, and this has all occurred in our private alpha over just a few weeks.

MO:
What are your plans for ChubbyBrain/FRE in the future?

Anand:
In terms of future plans for ChubbyBrain and FRE, we have some ideas on new innovative ways to use data to help entrepreneurs become more successful. But we’re going to test those ideas a bit before we do anything. More importantly, we just launched the FRE just six weeks ago so at this point and before we start thinking about the next thing, we really need to perfect the FRE and ensure it is providing maximum value to companies seeking funding and investors. We’ve gotten a lot of very complimentary and useful feedback and so the short-term goal is actioning those items to improve the FRE.

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