Home Search Priceonomics Discovering Market Clearing Prices For Consumer Products

Priceonomics Discovering Market Clearing Prices For Consumer Products


Rohin Dhar of PriceonomicsHaving spent five years growing job marketplace Personforce along with a partner, Rohin Dhar and his co-founders are taking aim at the price of things with Priceonomics, a pricing search engine.

The idea sounds straightforward enough: crawl through the web and figure out how much used things  (e.g. your old iPhone 4) are worth based on secondary markets. The startup has also delivered in-depth analysis of pricing inconsistencies that it sees – such as television resale prices. Read this Priceonomics blog post.

Incubator Y Combinator helped propel the startup to an initial $1.5 million investment early last year. Though Dhar wouldn’t divulge traffic figures today, he confirmed that the 65% month-over-month growth the company was experiencing last April has continued into a “hockey stick moment” – presumably even better than April’s momentum.

AdExchanger spoke to Dhar last week.

AdExchanger: What problem is Priceonomics solving?

ROHIN DHAR: When you are trying to buy or sell anything in any market, you need to have a market clearing price in order for the market to function. Today, there is no well-known market clearing price for most used items. For a handful of things like iPhones, televisions or other popular items, you can go on Ebay and Craigslist and find a price you can sell it at – and that the market will clear it at. But what we do is set up a market clearing price for millions of products like a bicycle, an iPhone, a 20 year old pickup truck or a $2,000.00 turntable – things that aren’t sold that often.  We’re trying to make markets work better by having a price.

How are your data sets collected?

We have two data sets. First, we have to build a product catalogue of everything ever made, because we need to know what is out there that people are trying to sell so we can look for it. It involves crawling manufacturer sites, crawling catalogues, crawling hundreds of various different sites, to figure out, for example, here are all the bicycles made in the last 50 years.  So, half of our data set is building these structures.

The other half is then going through secondary marketplaces, like Craigslist, eBay, smaller auction sites, and figure out how much are people actually selling these things for.

And, how is this different than a shopping search engine?

For the time being, we’re not focused on new products. So all shopping search engines are, basically a price comparison for the latest and greatest things, like a phone or a sweater or a TV, but it’s just for new ones. We’re not telling you what’s the best price, we’re telling you: “Here’s a five-year old skateboard that you’re interested in. Here’s the going price. And, here are a couple of places you can buy it on secondary markets.”


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Could you bring this valuation model to something such as media and media placements?

I don’t know much about how ad exchanges work, for example, but to the extent to which we have something we know exists, and then we can find marketplaces where that product is traded on – if we can find a few things, then we can price anything.

What do you do with that intent data from the pricing search engine? And how is your intent data different?

We don’t do anything with it right now, but we’ve been approached by “cookie-ing” firms.

When someone is on our page searching for a specific thing, we know that that person is looking for a phone made by this manufacturer and this specific model. For us, our intent data is all structured. A hundred percent of the people on our site have this intent to either buy or sell a very specific item. Meanwhile, we know what category and manufacturer it is and things like that. We haven’t focused too much on revenue yet, because even with the least creative ways we could monetize it, we’re not dealing with the problem of people not having purchasing power on our site.

Any insights you can share on what might be the business model down the road?

It will probably be something that helps minimize inefficiencies. At a minimum, if we put ads on the site, we think it would probably be profitable today.

We think there’s so much more opportunity in making all these markets work better such that people are going to try to get more money for their things and utilize their assets better. So in terms of our data and company mission, it’s more built around having people utilize their assets more efficiently.

How many people are you today?  Have you had time to spend the million and a half dollars you raised in 2012?

We have four people.  In every role, we’ve been able to get the best possible person in the world — our front end engineer is an electrical engineer from Stanford.  Our machine learning guy is brilliant, and my co-founder, Omar Bohsali, is one of the best hackers in the world.  We’ll grow the team more as we need to, but for now, we’re okay.

12 months from now, what milestones would you like to have accomplished?

We want to be the price reference for the web at Internet scale — so the way that Kelly Blue Book is a price reference for cars.  We think that we have the opportunity to be that for cars plus everything else – a trusted name to let you know what things should be sold for.

Follow Priceonomics (@priceonomics) and AdExchanger (@adexchanger) on Twitter.

Editor’s note: AdExchanger is a customer of Personforce and its job marketplace offering.

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