We started off wanting to build a new kind of search engine – a search engine for numbers.
But somewhere along the way we got fascinated by prices. Prices of everyday products, electronics, automobiles, shoes, jewelry, healthcare services, financial products, real estate, ball bearings, sugar, coffee, and so on. Even prices for you and me – our wages and salaries.
Everything on the planet has a price – every product, every service, every person, every thing. What if we built the world’s largest database of prices? A really really big database of prices for everything?
What could we learn from it? The more we thought about it, the more we were fascinated.
We realized that prices are a high quality signal of what’s going on around us and what’s happening in the world. Almost every event we experience, from holidays to hurricanes, is reflected in prices. Even our preferences, what we like and what we value, are reflected in prices.
Could prices be used as a signal to help people make assumptions and predictions of what might happen in their lives? And could businesses make bets and decisions based on looking at prices of everything? We know they already do that based on the price of money, stocks and bonds and commodities. But how about based on the price of shampoo, groceries, healthcare, and steel rods?
It already happens to some extent. Whether as a consumer, a business, or a government, prices affect many of the decisions we make. But the world of prices is still largely opaque – it’s hard to get data that is both comprehensive and accurate, and even where it’s available, it’s often already old.
Part of the difficulty of making decisions based on prices comes from the fact that prices are not transparent. There are varying levels of availability and transparency to prices for different goods and services. We believe that collecting, organizing and analyzing prices of everything has value to consumers, businesses and government.
Take something as fundamental as inflation – crucial decisions (consumer & business spending, government policy) hinge on an accurate view of inflation. But it’s difficult to estimate with underlying data that’s neither comprehensive nor real-time. Why not take the guesswork and politics out of inflation? The Billion Prices Project at MIT is one that has already started on the path towards a real-time handle on inflation.
The internet has changed much of what we used to think about prices. There is more transparency and more dynamic pricing, and that’s with only 10-12% of consumer commerce online. Whole swathes of the economy are not on the internet today.
As more of the economy moves online, there will be more goods and services on offer, and real-time, dynamic prices will become a reality for everything. It’s already the case in some industries like air travel – prices change based on availability, demand, time of year, and so on. But that’s now happening for everything from cameras to shoes. Who hasn’t heard of stories of products on Amazon changing prices multiple times a day (link).
We believe that as more of the economy moves online, the transparency, the dynamics, the assortment and real-timeness of prices is going to accelerate – and trading in goods and services will become increasingly like the stock market.
This transition will not be without interesting side effects such as the case of the $23 million book, resulting from two stores having an algorithm for changing their price based on the other (link).
What can prices, the change in prices, and even the rate of change in prices across different industries tell us? Could we extract meaning from these changes? What can we learn from the way prices of different goods and services are connected? Could we eventually explain the world, in some small way, using prices?
All of this brings up questions of how businesses operate in a world where prices and the products and services they’re associated with are changing all the time. How do they plan? Or if they’re setting prices, how do they make sure they’re appropriate and fair? Will they make better and different decisions if they had more data, or more accurate data?
We’re still at the beginning of this journey, and we’ve come up with more questions than answers. But one thing we’re sure about is that it’s going to keep us busy for quite a while. And we hope that you’ll stop by occasionally to see how we’re doing.