I started working in ad tech in 2005 and during the past eight years, the ad tech ecosystem has progressively become more sophisticated, competitive and oligopolistic. It’s hard to innovate in ad tech. But if you’re looking to start a company in the sector, you’ll need to amass proprietary data or develop a market place with unassailable liquidity to vie successfully in the market.

A Mental Model for the Ad Ecosystem

The structure of the ad ecosystem, greatly simplified, looks like the image above. On the left, the advertiser supplies dollars that flow to the right. The DSP (demand side platform) uses algorithms to inform an advertiser’s media purchases; i.e., which websites and mobile apps will perform best. The advertiser and DSP purchase media on the ad exchange which is an electronic market place where advertisers can buy media algorithmically and in real time on Real Time Bidding platforms. On the other side of the exchange, the publisher uses supply-side platforms to find the best paying advertisers to buy their ad inventory.

There are hundreds of SSPs and DSPs, thousands of advertisers, millions of publishers but only a handful of exchanges: Google’s DoubleClick, Facebook’s FBX, Yahoo’s RightMedia, MoPub, Adap.tv and a few others. These exchanges, like most market places, exert huge network effects because advertisers are attracted to the exchanges with the most inventory selection/liquidity. The exchanges see every transaction and have unparalleled visibility and data access into their respective ecosystems.

Data, data, everywhere

If there’s one defining characteristic of online advertising, it’s data. Advertisers buy data and license algorithms to find better inventory. Publishers sell their data and license other algorithms to find better advertisers.

In order to compete in an ecosystem of data, a startup has to bring one of three advantages to market: better algorithms to use on the same data as everyone else, better data than anyone else or a market place with the largest volume of ad inventory in a segment.

Better algorithms is the fastest way of getting into the market as a startup. Similar to starting a new quant hedge fund, you develop a novel trading strategy that works and sell it to customers. But competition in ad-tech is just like the financial markets - as soon as others see your strategy working, they are likely to copy it. Over time, the marginal advantages of better algos erode. Unless a startup continues to invest heavily in algorithm improvement, it will forever be in a cat-and-mouse game.

Better data: Where algorithms can be conquered, proprietary data is unassailable. With access to richer ad performance data, more detailed user data, more granular conversion funnels, your startup has created a significant barrier to entry. Better data means better results. And if you’re the only game in town, then you’ll attract big advertising budgets.

Getting access to better data is very challenging. It means finding and partnering with publishers and/or advertisers on an exclusive basis for some period of time, then leveraging that data to build a successful DSP/SSP/ad network.

Market places in ad tech, as in the rest of the tech industry, are beautiful things. They are natural monopolies, capital efficient and are strategically valuable. Building a new ad tech market place is the most challenging way of entering the market because of the strategic role these products play in the ecosystem.

The most successful startup market places (RightMedia, Adap.tv, BlueKai, MoPub) each took advantage of a discontinuity in the market place (inventory glut, video ads, rich user data, mobile ads) to develop a foothold in the market faster than the incumbents. Over a few years, each of these companies built liquidity into their market places and now are the leaders in their segments.

The Recipes for Success

As the ad tech ecosystem has bloomed, competition has increased dramatically. To best position your new ad tech startup for success and develop a long term advantage, you need to develop leverage by developing proprietary data sources or by creating a market place based on some technology discontinuity. In other words, bring something to market that no one else has and that is difficult to copy.