A modern data acquisition technology stack allows you to maximize your data enrichment capabilities
The process that companies go through to select a data partner is flawed. The data bake off benefits neither buyers nor sellers, but instead promotes an “all or nothing” mentality that doesn’t make sense in a data ecosystem where scale is king. The data acquisition and monetization space is in need of a fresh, creative approach to replace an outmoded process. The first step is to kill the data bake off and replace it to the benefit of both buyers and sellers.
Companies that need access to raw data typically choose one data seller to buy data from. The process by which they select this partner is known as a data bake off. Selecting a single partner from a group of sellers involves comparing results for accuracy, match rate, overlap and scale. Sellers ship their data off to be tested, hoping that it performs well against the buyer’s metrics.
At my previous company, we participated as sellers in several bake offs. We dedicated entire sprints to creating custom features in the hope we’d win. The sales team went into overdrive in their efforts to win each bake off. After such a mammoth effort, you’d think it would pay off even in some small way. The reality was, if you lost, you were left with nothing to show for it.
Data acquisition is a complicated process and data buyers use bake offs for a few reasons:
- Contracts are a time-consuming hassle that require involvement from legal and business development leads
- Optimizing a data portfolio across multiple supply sources is complicated by problems such as duplication and data that doesn’t provide signal
- Integrating each data set is a time suck for both product and engineering, taking away from time spent completing more valuable roadmap work
In theory, a bake off lets the data buyer save time and money by selecting a partner from all the bake-off participants. They’d “make do” with the data the selected partner provided. The other three or four data providers lose access to any revenue opportunity, leaving some of the smaller players with great data behind with nothing.
This isn’t how data acquisition should work for buyers. Why should they have to sacrifice any part of their data strategy goals because the acquisition process is so taxing? When you’re buying data, you should get all the data that’s relevant to you regardless of how many places it comes from.
The ideal situation would be for data buyers to easily obtain standard/normalized raw data from everyone. After all, the data that’s most relevant to their needs may come from more than one seller. This would alleviate the problem of buying data that doesn’t provide signal just because it’s in the firehose. Being able to get pieces of data in a standard format also eliminates the time-consuming integration process that’s different for every seller.
As the Head of Partner Success at Narrative, sellers often ask me, “Who are we up against?” I would argue that they are asking the wrong question. What they should be asking is, “How well does my data match the buyer’s needs?”
By killing the data bake-off, a data commercialization platform changes how sellers think about winning or losing deals. Now instead of focusing on their competitors, they can focus on the value that they are delivering to the buyers.
Separately, the dichotomy of winners and losers that these bake offs create isn’t healthy for the ecosystem. Competition is a prerequisite for any efficient market — in the long run, the bake off actually discourages competition by creating a winner-takes-all effect. There’s a better way to do this that will help buyers and sellers both win.
A data commercialization platform allows buyers to select the data they need from a variety of sellers.
Here’s how it works:
- The hassle of striking a contract with each seller is now easier because you only need paperwork with the data commercialization platform
- You can acquire data on a per record or per event basis — no need to make the huge investment of buying the firehose from everyone
- You can do one integration and have access to everyone on the platform.
Just as buyers have greater opportunity with the platform, sellers have new and easier revenue opportunities available to them under this model. The data commercialization platform gives sellers the opportunity to sell data to a large pool of buyers that may only want some of their data.
Many of the approaches to buying and selling data don’t work well for the data owners or the data consumers. Data bake offs are one example among many that no longer make sense for buyers or sellers.
“There’s a way to do it better — find it.” — Thomas Edison
The data acquisition process is long overdue for a more modern, nuanced approach. If data is democratized through a data commercialization platform, buyers can get all the data they need and sellers have access to more revenue-producing opportunities for their data.
Do today’s methods of transacting data actually work for you?
Think creatively about how you can approach data acquisition to get away from the win or lose, all or nothing approaches that dominate the market. There’s a way to get the data assets you need without having to walk away from valuable, useful data that can help you achieve your goals. Don’t let the status quo dictate future data acquisition efforts.