To identify the essential requirements of a Data Management Platform (DMP) it is useful to start from its definition. In the recent Evolution of DMP report, produced by London Research in collaboration with Adobe, it is possible to read: "The Data Management Platform has evolved from tactical media purchase tools into much more sophisticated and strategic platforms at the heart of corporate customer intelligence. The modern DMP can ingest first, second- and third-part data, connecting anonymous data and authenticated data. Basically, DMPs allow companies to transform data and insights into real-time actions, helping them to deliver the most relevant and personalized content and messaging to each digital touchpoint ».
Considering this quote, it is possible to deduce that at least 3 are the fundamental requirements of a platform Data management:
- transversal nature of the solution;
- professional management of Big Data in a data-driven key;
- ability to automate the outputs according to the objectives and contact channels.
DMP, a marketing tool for all companies
The evolution highlighted by the London Research study makes us understand why today DMPs are no longer exclusive platforms for media centers and Internet advertising programming. In fact, customer intelligence is a requirement of any organization that wants to obtain reliable information about its customers. For sectors such as retail, for example, they have become essential both for the online and in store customer journey tracking.
But for any company that aims at a marketing strategy in line with today's consumer trends, it is necessary to adopt a solution that, like DMP, can convert various customer interactions into a source of knowledge that guides tailormade supply. Therefore, Data Management Platform suppliers do not focus so much on limited commodity sectors, as on the specific needs of companies that wish to obtain value from a set of otherwise unusable data.
The necessary skills for the Data Management Platform
Several organizations around the world have already understood this. According to Gartner's 2017 Marketing Technology Survey, over 50% of companies use a DMP. Percentage that in our country, based on the results of one of the Observatories of the Politecnico di Milano, drops to 19% for third party DMPs and 9% for proprietary ones. A difference, compared to the international context, which can be explained by crossing these numbers with those of the Politecnico related to the Big Data Analytics, closely connected to the Data Management Platform. 77% of the large companies involved in the survey complain of a lack of internal resources dedicated to Data Science. It means that in the field of data-driven it is not possible to improvise and that, between the system integrator and IT vendors, specialized skills are now emerging that range from an advanced use of NoSQL databases to the integration of open source services and storage in sight of the DMA to be realized.
From descriptive to predictive analytcis thanks to artificial intelligence
The third requirement of a Data Management Platform, which includes all the information collected and organized to become marketing automation output, depends on the integration of DMP with artificial intelligence (AI) algorithms. The report by London Research recalls this, underlining the transition from descriptive to prescriptive and predictive analytics. If before analytics tools were used to explain the past, for example after a marketing campaign, now they can anticipate the future. A change that consists in "the ability to tell what the next best action is for a marketer at every point in the customer journey. And this must happen through multiple channels, in real time and in scale». In other words, the Data Management Platform, with the help of AI, closes the circle by automating customized actions (sending newsletters, push notifications, cross-selling and upselling proposals) aimed at specific clusters or even individual customers.