Posted 18th August 2015 by APSIS

What should a data management solution actually do?

So much of marketing-related technology seems to use the same terms or acronyms to describe very different services and usage. The modern marketing environment of more and more technologies, devices and channels can muddy the waters further, since each silo is now asked to perform a wider function than it is used to performing.
From acronyms to anachronisms…
The term CRM, for example, will have a widely different meaning, capability and function from one organisation to another. Formerly a static customer database, a CRM solution is now required to integrate with every other technology that marketers use to talk to customers, in an effort to incorporate more dynamic customer data.
Single Customer View is another. The most memorable example I can recall is when (and without any hint of irony) a very senior marketing director advised me that he thought a SCV was so important that he had 3 of them!
It would appear that the same mindless and multiple interpretations are being applied now to Data Management Platforms, or DMPs. This is largely driven by the big marketing budgets of old-guard legacy system providers entering the arena. Many of them have acquired DMP technology companies, and are now desperately trying to define the term DMP within the limitations of their existing solutions.
Most marketers will be familiar with DMPs as delivered by their agencies for the improved performance of their display advertising budgets. In the modern day, however, there is an incentive to go well beyond this simple, limited functionality…
What should a data management solution do today?
How can the term DMP maintain its relevance today if it only works with third party data?
How about a platform that will bring all your data together, regardless of source, into one place, in real time, then enable you to make sense of it all and align the commercial objectives of the business to the behaviour of both your customers and prospective customers?
This results in a different type of SCV or CRM capability for today’s real-time, cross-channel customer engagement demands (and most definitely not 3 of them).
Any leading-edge customer data platform should be quick to deploy, a lot less costly, and deliver an iterative scalable capability.
The resultant real time cross channel customer view is one that will identify and monetise new and high value audiences, drive real marketing efficiencies across all channels (not just display) and then inform marketing as to profitable new communication strategies and improved messaging throughout the customer journey. All achieved across existing technologies and data.
What about your customers?
From the consumer’s perspective, this sort of solution also helps strengthen people’s trust. As marketing communications become increasingly automated and programmatic, consumers will be concerned about their digital DNA. By being highly targeted, relevant and timely (in other words, treating customers as individuals as opposed to segments), brands can actively demonstrate an ability to take privacy seriously by acting appropriately.
There are other benefits to be gained:
  • Faster response times and better content relevance
  • Shorter project timelines – achieve in days or weeks what has traditionally taken months or years
  • Improved ROI and reduction in 3rd party costs
  • Unlocked data and functionality of traditional legacy systems.
Technology alone does not solve problems, and here at Innometrics we have found a few but very important factors for successful implementation of a customer data platform:
  • As you won’t have data silos anymore, it’s important to identify a stakeholder able to make things happen across channels and organisational silos
  • Ensure that it’s easy to input first, second, and third party data into the platform
  • Make sure that the new platform is capable of integrating with all your existing technologies, while working with both structured and unstructured data
  • Start with your digital assets, then bring in offline data and finally look at full integration. In other words, reverse the usual structured process
And finally: Be careful for what you wish for, there may be management and structural issues arising from bringing all your customer data into a single location.
Start simple, test, learn… and make sure you can scale.