WeFranch

In an upcoming episode of mainstreetmedia, I interviewed Gregory Ugwi

In this memo, I will break down what we discussed

somewhere in lagos

Greg grew up in the largest city in Nigeria

Lagos has a population of more than 16 million - a higher total than the next five cities combined.

Income inequality plagues the metropolis; a stark divide exists between the wealthier areas of Lagos (Ikoyi, Victoria Island) and the inner city (Ajegunle, Makoko).

Greg grew up in the inner city

As a youth, he was a troublemaker, but nonetheless, a great test taker. High test scores landed him a spot at the richest boarding school in the country, located in Abuja, the capital of Nigeria.

He took long trips between his boarding school up north and his home down south.

The distance between home and school was more than physical - Greg felt as if he was moving between two different worlds, jumping from one planet marked by poverty to another accustomed to abundance.

At 16, Greg did very well on his standardized tests and received financial aid to attend Princeton in the United States.

So he went from being surrounded by kids from the richest families in Nigeria to being surrounded by kids from some of the richest families in the world

The question still lingered in his mind

How do you create wealth?

This curiosity carried Greg to his first employer, Goldman Sachs… In the middle of the Great Recession

He was part of the Strats team, a highly quantitative group providing tools and models that helped traders make better decisions. His role was to build better tools with software to help traders make better decisions in capital markets

At one point, he was looking for data on home prices in sandy states (Florida, Arizona) because those prices were behaving differently from other areas in the U.S. His team tried to pay millions to Reuters and Bloomberg, but no one was selling the data. He started scraping the data and got yelled at, because of compliance issues

Greg talked to his friends at hedge funds and they were having the same problem. No one is capturing alternative data to help investors make decisions.

A lightbulb went off, and the seeds for Thinknum Alternative Data were planted.

What was the hardest part of getting Thinknum off the ground?

Greg thought for a few seconds before providing an incredible analogy

Imagine you had to play one-on-one against LeBron, who wins?

Now let’s say you have to play Team USA, 1 v 5, who wins?

That’s what a startup feels like: you versus Team USA.

You are trying to sell data, and you’re going against Bloomberg

They have specialists that are good at hardware, Linux, C++, the best collateral, infinite money for marketing, and you are trying to compete with them.

Occasionally in the universe, the game changes overnight. Imagine if, a day before the game, officials decided that we would be swimming instead of hooping.

Maybe you win, maybe you don’t, but you have a decent shot.

All of the major advantages that Team USA previously had - long limbs, low body fat - might work against them in a swimming competition.

So that’s what happened. Bloomberg was really good at getting data from exchanges and Thinknum could never compete in that field. But now it was about crawling data, getting data from the web, spinning up data models quickly, new technologies. When Greg & co. built that really well and got an emotional reaction from investors, there was an unlock.

Over the course of 10 years, Thinknum found product-market-fit, raised a $11.6M Series A, and then got acquired.

franchise

After the acquisition, Ugwi was exhausted.

He was in Princeton, New Jersey, with his brother. His brother, a therapist, was looking to buy a franchise at the time.

One particular franchise held an expo in the middle of nowhere and the information provided was insufficient to make a significant investment. Greg saw misaligned incentives with franchise brokers making millions by keeping the market opaque.

His exhaustion wore off and WeFranch was born.

The market is enormous:

• The U.S. franchise industry generates $800B+ in economic output annually

• Over 8.5M people in the U.S. are employed by franchises

• 800,000 franchise locations in the U.S.

Another interesting development is searchers - individuals operating search funds - have started turning towards buying franchises.

Searchers engage in entrepreneurship through acquisition, where an individual raises money from investors to buy a single company, improve operations, and eventually sell it to repay investors and collect a nice check.

WeFranch has capitalized on these new developments in the franchising space by hosting events bringing together searchers, franchisors, franchisees, and investors.

From a strategy perspective, the company focuses on providing clean data and tools for franchisees, with the knowledge that franchisors will flock to WeFranch if potential franchisees are there. The business model is to charge franchisors while making the platform free for franchisees.

Keep up with Greg’s journey as he builds the future of franchising at WeFranch:

 Website | LinkedIn | Find a Franchise

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