Using your own data at the Dynamic Desk
L’Oréal is pursuing a resolute path in marketing through consumer targeting, crafting a precision appeal to consumers that uses relevant information based on close observation of the data
Andreas Neef envisions around 1000 campaigns per year, with an annual budget in the mid-double-digit million range. After all, the company has 28 brands in the DACH region alone. Controlled from a “Dynamic Desk,” increasingly goal-oriented, increasingly successful. The Media Director DACH at L’Oréal starts out with a look to the past.
“When the first programmatic solutions came onto the market three or four years ago, things didn’t all work satisfactorily right away,” Neef points out And, he recalls, the services purchased were mainly ones that couldn’t achieve all the defined objectives. Audit findings on agencies’ previous IO digital purchasing found, for instance, that women aged 50 years and older have already been mistakenly approached with pitches for men’s products.
Reason enough to learn from this and reset everything. With multiple test campaigns for better retargeting based on demographic characteristics, reactions, bonding and a better view of the audience. This led to creation of the “Dynamic Desk” at L’Oréal. For Andreas Neef, following very good results, today this is a reason to “take things into your own hands.” An opportunity to be quicker and more precise.
He likes to cite the La Roche-Posay brand as an illustrative example. More specifically: a skin-care product for toddlers with neurodermatitis that helps them sleep better. A smallish, five-digit budget was all it took to reach more than 2.5 million parents of affected children with precise targeting and close monitoring of the customer journey.
With increasingly improved technology such as the use of artificial intelligence, Media Director Andreas Neef sees even further opportunities already bolstered here with very good results. In the technical area, for instance, if the ROI of the videos used recently quadrupled with the support of TD Reply.
Neef also sees greater opportunities through the use of AI at the creation stage. With the support of colleagues in Paris, today advertising can already be broken down into nearly 300 to 500 elements in order to differentiate advertising into nuances on the basis of learned rules. This offers a way to appeal to individual target groups with ever-greater precision.
He also observes how agencies have increasingly reorganized themselves in recent years. He sees this in agencies’ current approach to recruitment.
With a critical look at the development of publishers in past years, Andreas Neef is optimistic about the future. He identifies three important points: 1. What is the publishers’ availability, 2. What will become of addressable TV?, 3. And, again: How do publishers navigate the path from the text path to the consumers? And adds: When will publishers realize that the days when it was all about the sale of ad space are long past? Neef believes they have since turned their attention to the topic. Much will become apparent over the next three years.
Andreas Neef is audibly optimistic: “Starting in 2020, the years are going to be exciting for digital marketing again.” In his view, almost everything will be handled programmatically, even TV. Technology will permit targeting with greater and greater precision. To him, mobile isn’t “second screen” any more but “first.” One thing is exciting either way: the ways in which devices will evolve in the near future, perhaps even regardless of the number of screens. Neef’s view of the future: We are going to engage in people marketing.
The bottom line:
Companies are increasingly succeeding in reaching target groups with greater precision, thanks to their own data ownership and well-structured marketing. In the end, those who are not afraid to learn from their own mistakes will benefit. Creativity is constantly in demand, however, and now it’s backed by clever analytical methods. The systematic approach companies can take to pay into their own success is to use data in ways that more clearly reflect the added value for the consumer.