Entrepreneurs: Ajo and His Startup
by Ajo Fod
After I got my Masters in Computer Science and Optimization from USC, I worked for banks for a while as a quant (people who do quantitative or mathematical stuff such as build complex models to evaluate financial securities, risk and reward).
Contrary to what most people would tell you about working for a bank, I found the work very interesting—not surprising, given my math background.
But much as much as I enjoyed my work, I was bitten by the entrepreneurial bug and wanted to do something original.
I’m an engineer at heart and I like inventing things that makes life better or improve what people are already doing.
Innovation seems to happen overwhelmingly in small to medium companies and then big companies usually buy the promising smaller ones.
Doing my own thing would also gave me the ability to try out new things at an amazing pace that makes the process of discovery a lot faster.
Initially I had the bright idea of trying to beat the banks at what they do best: price securities.
I invented a way of making models that could learn more from purchase data about pricing than conventional models do and put those models to work trying to outguess Wall Street computers.
Eventually, I realized that even though my algorithms were smart, the networks that were affordable to me were too slow to use this information for the strategy I developed.
Even though I could predict prices, I couldn’t get ahead of computers that were closer to the exchange to make the profitable trades.
I had to make a pivot or bet even bigger and buy access to the necessary networks.
I paused to think for a while and it occurred to me that the world is full of things that need to be priced.
So, why stick to the business of securities where so many quants and fast computers were concentrated in solving a problem with a lot of history?
Why not solve a Main Street problem?
I began looking for a niche where there was a significant problem that I could solve.
About that time I heard a story on the NPR money podcast.
Two sets of people were asked to guess the weight of a cow shown in a picture.
They first asked a bunch of experts what the weight might be and each gave a different answer.
They also gathered answers from a crowd of non-experts on a website.
The median value in the crowd of non-experts was much closer to the true weight of the cow than the group of experts!
That led me to think about how the wisdom of crowds could be used to help small companies make better decisions.
Of course, I wanted to monetize the information in the buying decisions that people make.
How about learning the perfect offer to make to shoppers at an online store?
I’d recently built complex pricing models to value financial securities, so I knew I could do this.
I quickly noticed that small businesses were leaving a lot of profit on the table. They were essentially using rules-of-thumb, instead of measuring price sensitivity and making optimal offers for peak profit just like the airlines, Airbnb and Amazon are already doing.
How much of an advantage can optimization bring?
For example, the average retail store runs with a 5% net margin.
What if the store could raise the sale price (after any discounts) of the average item by 1% without affecting demand?
That would raise their margin a staggering 20%!
And that is what happens with just a 1% change.
Imagine what can happen with a larger price change.
In our experiments with stores on Shopify, we noticed that they were so far off the optimal price that they were making less than 70% of what they could be making if they could tune into the crowd.
That is beyond a big deal!
So I began working on an app with the vision of using optimization to create better offer management strategies.
Over the last year I created the company, Quant Price. You can try our first app for free on Shopify.
Join me tomorrow for a closer look at what Quant Price does.
