“I’ve got a DMP, now what?” -Segmentation strategies in a data management platform world

In an increasingly complex programmatic world with view-ability, cookie deletion, cross device attribution and third party data enriched DSP’s to deal with, when you introduce a DMP to a marketer, they either shrug at the need of adding another layer to ad-tech, or just call it out as the last thing on that shopping list order of priority.

And I don’t blame them, I read somewhere that for every dollar a marketer wants to spend, they are paying about 25-35 cents in being able to deliver that message. That’s creative services, DSP charges, attribution, ad verification, reporting all included. Add to that dynamic creative, a DMP, attribution and the cost goes up. And I haven’t even mentioned the pain of managing separate contracts.

So while the industry is no where near consolidating around that problem, the campaign efficiencies you can drive by using your own data for re-targeting, audience extension and look-alike modeling based prospecting can deliver incremental ROI gains that pays up for the entire stack.

As a Marketer, you are running campaigns to create buzz using attitudinal data, after creating that buzz communicating product features based off behavioral data, then following it up with retargeting to convert, and for the converts, execute cross sell/up sell campaigns.

At each stage, you can use your own data to target, re-target, and extend audiences. You are sitting on a gold mine of the right first party data or second party data (someone else’s first party data). You can also buy data to fill in the gaps.

Segmentation Strategy

A segment strategy requires you to understand the source of the data (online signals or offline actions), the method of collection (first party, second party or third party), the process of creating a segment (Boolean rules based or algorithmic look alike) and understanding what the resulting segment attribute is (descriptive or predictive).

Some segmentation strategies applicable to campaigns include :

But rather than just doing a simple re targeting based off the current search, you can apply a layer of signals you have on that person to change your re-targeting strategy to have segment based re-targeting where offers could change by loyalty status for instance. Rather than a simple “because you searched for this sector here is a message reminding you to book it” its now** adding a layer of past purchases.**

The Combination of a Data Management platform powering segments that are tied to templates in a Dynamic creative solution, and also providing the real time data that is driving that decisioning rather than the need for separate retargeting tags, allows for the DMP to deliver incremental value, where although the person falls in a re targeting segment based on the on-site behavior, they are also then helping test and learn from thousands of creatives. These are creatives that are not just changing sector and price but perhaps copy, creative image, button color etc, and also serving as inbound data source for the DMP to qualify or disqualify segments after having been exposed to certain creatives, which paves the way for sequential messaging.

Final Thoughts

A DMP powered campaign strategy can bring in efficiencies as programmatic ad spend increases, and has the ability to help marketers focus on driving loyalty and customer lifetime value. 2016 is the year the marketing stack and the ad tech stack comes together and the DMP sits right in the middle of your marketing strategy making that possible.

So understand campaign strategies, understand the use of descriptive versus predictive signals, empower your traditional quants, and get set for never before campaign efficiencies.