Entrepreneurs: Ajo and His Startup Quant Price
by Ajo Fod
Yesterday I described how I came to start my company Quant Price. Today is the story of what happened after that decision.
I first did the Founder Institute program that helps entrepreneurs create companies. They introduced many concepts that are hard for first time founders to grasp. Things of HUGE importance ranging from talking to potential customers to validate the idea to seeing how buying decisions are made.
There are many things that can make a startup fail. Each of these factors are risks. A successful startup has avoided each of these pitfalls in succession.
There is a step by step process to developing the idea and de-risking it. The founder Institute program helped me think through them.
One shortfall of the program was that it has a cookie cutter view to creating startups. It requires that everyone fit into a mold. This may not serve every startup well. I’d probably have taken it to completion if I were not “terminated” for having a hard time getting a sufficient number of video interviews.
Though to be rational, I’ve to admit that it’s also possible that I just have a very bad idea or am not really cut out for this. I may only know very late because “I’m drinking my own Kool-Aid”.
The risks are huge. There are a lot of things that matter to a startup being a success. There has to be value in the product. There has to be a way to reach a big chunk of the market. There has to be a way to convert all those gains into money. People have to believe in the dream and be willing to contribute for free for the duration that the cash flow doesn’t exist. It takes a lot to keep a startup together.
It was very hard to find my first customer. I didn’t even have my marketing material when I went to interview Katherine Krug the founder of Getbetterback.
Partially because I didn’t realize that I was supposed to bullshit my way through such meetings and, frankly, partially because I didn’t know how to bullshit about it if I had to.
Fortunately, Katherine is one of those people who tests things like prices. I think she was lucky to not have a mentor who had a strong opinion about pricing. (I still can’t believe that people don’t test their prices.)
Katherine first did a price test with Optimizely. Unfortunately, Optimizely is not really geared to do price tests. Additionally, putting Optimizely code on your web page makes it load a lot slower for the end consumer. That itself reduces conversion rates.
It made me wonder if people don’t know or just don’t care about the impact this has on the browsing experience.
Optimizely targets conversion rates, so once Katherine was done with the test it told her how many people had converted to buy at different prices. Obviously at the higher price, fewer people converted.
But the real question was which price lead to better margins?
And was the test significant?
That is when she realized she needed Quant Price.
I salvaged the Optimizely results to guess what the next prices for the next test should be.
We used our pricing engine and did an A/B test. It turned out that seemingly identical prices $49 and $59 were over 26% different from a revenue perspective.
We also realized that changes to the web design and the holiday season could change the optimal price. So much so that at some point $69 was 22% better than $59 because of the Christmas buying spree.
Hidrate, my second client, was easier to find after we put up a video interview with Katherine.
With Hidrate, we seemed to run into some bad luck. The $59 price for them was identical to $49 from a profit perspective. But as luck would have it, they were running out of inventory. Now, at the $49 price they were burning through 45% more inventories to make the same amount of money as at $59.
Once we told them about it, they raise their price to $59 to save inventory. They kept their customers happier for longer AND made money to buy more inventories without losing the company to investors.
Here are details from our first two clients,
We did all this by using technology developed for finance. Quants in the financial industry are usually tasked with pricing securities worth trillions of dollars based on market data. There are multiple factors that affect the “fair” price of a security.
I learned how this valuable task of pricing can be automated incorporating available data.
Many companies now quote prices and sell exclusively online. Computers can be used to make pricing decisions based on price sensitivity of individual customers, business specific parameters, such as inventory availability and market conditions and the current season.
Airlines and Amazon already do this on a massive scale and are very profitable as a result.
SaaS companies and large-to-medium scale retail operations could be next in line.
Fortunately, our market is easily defined. We are looking to help companies with more than 300 distinct customers. This is desirable because with more data we can get statistical significance on more complex models.
We are looking to help SaaS companies that want better pricing models. For them, we have a solution that reduces churn and increases revenue at the same time !
To justify building a company-specific solution, we need to be able to service a pool of revenue of over 10M$/year.
Quant Price’s free app Qbot is available to smaller companies in the Shopify app store.
In order to make our technology more accessible we packaged it into APIs and apps, that help us expose this functionality to more companies.
Two final points.
- I’m happy to pay a bounty for referrals. Contact me at info@quantprice.com for details.
- We are looking for talented people who can participate in the development of our product.
And if you have any questions or comments you can respond here or use the email address above.
