As businesses seek even more sophisticated solutions for targeting audiences, marketing technology companies are plotting like mad to build the most efficient and effective data-management platforms (DMP).
The DMP market, calculated at $2 billion in 2015, is expected to grow 20 to 30 percent annually through 2020, says a Rocketfuel.com white paper placing such products in the “early adopter” stage. Eight to 10 percent of Fortune 500 companies were already using them as of 2014, reports Mark Zagorski of eXelate.
The major attraction? When leveraged correctly, data directly improves ROI of marketing and ad spend. DMPs also adds value by integrating real-time information from multiple online and offline channels, analyzing results and creating highly targeted audience insights for ad and marketing campaigns.
All for one, one for all
The challenge of integrating a company’s entire data stash into a single system cannot be underestimated. Frequently, different company factions have already stored data without the involvement of IT; the best of breed DMP’s are taking a holistic, mapped-out approach encompassing every department as well as incorporating 3rd party data. Equally important are well-defined security standards and the ability to incorporate real-time and geospatial data from multiple sources.
More food for thought?
Three other aspects to consider when building DMPs:
1) Good vs. bad data – The unprecedented amounts of already manipulated data being processed can make sources and authenticity difficult to trace, sometimes making for unverified or “bad” information that may or may not be trusted. Assisting with that are metadata-management tools by companies tackling the inventorying of such data, marking source records and affiliations with other data.
2) Overarching goal – Consider the customer bases end goal first, then map out technology accordingly. Maybe the problem is data fragmentation, underused data assets or lack of audience insight. Perhaps the userbase wishes to better target audiences, interpret data, fine tune ROI, form content strategy or better track content effectiveness.
3) Customization sells – Many customers have unique or specific needs that require customized functions. The online dating site eHarmony, for example, uses a specialized platform that collects multiple data points on its users to create complex customer modeling. The resulting personalization of marketing communications has been highly successful, according to Tracy Kobzeff of eHarmony.
“As recently as the last two years, one of the seminal issues regarding big data was … the exponential growth and size of unstructured data that did not fit into databases,” explains Ben Kerschberg in Forbes. “(Today), proper storage is merely a pre-condition to finding the real jewels in big data — turning data from massive streams into knowledge, and thereby actionable intelligence in real time as events unfold.”