Marketers are often tired of hearing that they can't operate an effective marketing strategy without properly leveraging their first-party data through a DMP technology. However, are the marketers that have jumped on board making the most of their investment? Ahead of his participation at ATS Paris next week, ExchangeWire speaks with Ghislain Lefebvre (pictured below), sales lead, Oracle DMP, about what makes a sound DMP strategy, how marketers should be maximising their data usage, and the importance of machine learning.

ExchangeWire: What are the elements of building a sound and sustainable strategy around data management and activation?

Ghislain Lefebvre: Organisation is definitely key when running a strategy around data management and activation. Marketing departments need new digital capabilities and data expertise internally and with external partners.

A sustainable strategy around data management needs marketing technology, and marketing technology adds precision, science, and data; but these new additions require new expertise and new strategies. The long-term value of developing a clear, focused data strategy is undeniable; but knowing where to start, and who can lead and implement such a strategy, is the biggest challenge for many brands and their agencies. Therefore, everything starts from a new way to create interaction within the marketing department between teams in charge of media, CRM, performance marketing, technologies, etc, to define a concerted data management strategy and the best way to leverage it for its activation.

Are marketers leveraging the true potential around their own first-party data?

We are still at an early stage of marketers having an understanding of how they can firstly, get back control of their first party-data, and secondly, leverage their true potential. The data-driven marketing era, and all the technologies attached to it, give the marketers a unique opportunity to get the control back of data (and media) and then start to leverage the potential around their owned assets through more sophisticated remarketing strategies; in merging data from different sources to get more insights; in considering sharing and monetising their data into new usage – the potential is huge, and we are just at the start of the adventure!

In a world where users generate as many unique identifiers as the platforms, applications, and devices they use, it becomes very hard to have a full view of a consumer’s engagement in a fragmented world. Relying on a technology that can unify all those identifiers uniquely will become the first condition in building a consumer-centric strategy. This is the way the Oracle Data Management Platform designed its technology; and it is fuelled through the most connected IDs within the ad tech ecosystem.

Is the central buying stack approach helping marketers execute across multi-channel?

What is essential is for marketers to be able to have a single data management repository and to be able to get a holistic view of all marketing initiatives resulting in a single analytics report. The cross-channel orchestration does not need, necessarily, a single stack from one vendor; but it needs a consistent, concerted execution strategy upfront, which is only possible with a complete view of all data generated by audience engagement.

How difficult will it be for marketers to build interoperability between all pieces of marketing and ad tech?

The difficulty will essentially come from the partners the marketers decide to work with; from the walled garden partners, that have no wish to make their solution open, rather than the more API-friendly and open technology platforms, which have been designed to help marketers to create their own marketing suite.

How important will machine learning be in helping to optimise media buys?

Machine learning will continue to play a big role in the data-driven media buy; but the human element will also remain absolutely essential. Machine learning and big data, by themselves, really can't solve a marketer's problems. In fact, it's likely to lead to more problems. It's not about 'big' data. It's about the 'right' data, activated the right way, in the right channels, at the right time.

To take this one step further, the creativity aspect in the automated media buys has so far not played the role it was intended to; so we can expect to see that evolution in the coming months. Then machine learning, combined with a better creative strategy, will continue to liberate the power within data.

Lefebvre will be participating in a panel discussion on ‘How the Buy-Side Can Make Data the Key Component to Success in Programmatic’ at ATS Paris on 13 April. Find more information here.