April 19, 2024

Programmatic

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A Smarter Approach For Your DMP

<p>“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Shiva Vannavada, chief technology officer at iCrossing.  Operationalizing your data management platform (DMP) is not unlike raising a child. Both processes take time and patience. They each require consistent communication among<span class="more-link">... <span>Continue reading</span> »</span></p> <p>The post <a rel="nofollow" href="https://adexchanger.com/data-driven-thinking/a-smarter-approach-for-your-dmp/">A Smarter Approach For Your DMP</a> appeared first on <a rel="nofollow" href="https://adexchanger.com">AdExchanger</a>.</p><img src="http://feeds.feedburner.com/~r/ad-exchange-news/~4/teSjse2mFz4" height="1" width="1" alt="" />

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Shiva Vannavada, chief technology officer at iCrossing

Operationalizing your data management platform (DMP) is not unlike raising a child.

Both processes take time and patience. They each require consistent communication among primary stakeholders. And frequently, to make them perfect, they cost a ghastly amount of money.

But most importantly, neither DMPs nor children can be made a perfect product before they’re finally introduced to the world. A DMP can’t be kept in production mode while you input every last shred of data any more than a child could live in a bubble until they’re ready to start a career. A DMP’s maturation process is exactly that – a process.

And yet, that’s the consistent mistake today’s marketers make: trying to populate their DMP solutions with all conceivable audience data before they ever go to market. Such an approach is, at best, inefficient – and at worse, it’s unrealistic. 

Here’s an alternative: Determine the use case that best aligns to a primary current marketing objective, load only data pertinent to that use case and immediately go to market. That might sound counterintuitive for a tool as advanced as the modern DMP, but it’s really the more logical approach.

First, companies dramatically reduce the time their new DMP is stuck in staging. Instead of spending months (if not years) collecting and onboarding all available customer data, companies can start recognizing return on investment from DMP-driven activations in a fraction of the time.

As a result, marketers also greatly increase the chances of meeting their business objectives. Modern companies change tack frequently; new product launches, market fluctuations or even in-house leadership moves can suddenly shift marketing goals. Marketers need to work in weeks, not years. Onboarding data on an as-needed basis, as opposed to straining toward an all-or-nothing approach, allows them to do that. In other words, the only way to work quickly is to start slowly.

The reality is that most companies simply don’t have the expertise and structure to suddenly start operationalizing all of their customer data simultaneously. But aggregating data into the DMP on a per-use case basis allows the system to grow over time. That way, a company can progressively increase the size of its integrated data pool to tackle use cases for more complex business objectives. The ambitiousness of marketing goals rises in lockstep with the DMP’s sophistication level.

If companies are looking for the right DMP vendor, this approach can actually help solve for a critical selection criteria: ROI. Instead of locking in an expensive multiyear contract, companies with a clear view on their immediate marketing objectives can pilot a DMP solution for a short-term campaign. Doing so requires just a subset of a company’s total data pool – and hopefully proves how platform-driven revenue can offset costs before it’s on the hook for long-term pay structures.

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This post was syndicated from Ad Exchanger.