Rik Doppenberg, marketing automation Phone Number Database specialist, only started working at TNT six months ago, as did many of his direct colleagues. Combining data was also a huge challenge there: more than 200 separate Phone Number Database including a huge legacy dating back to the days of PTT post, are linked together to build a single customer view . All customer data, interactions with TNT (inside and Phone Number Database outside the TNT domain) and a number of purchased resources are sucked into their Data Management Platform (DMP). Algorithms are used here with the aim of matching their customer programs with customer profiles.
Data-driven marketing TNTTNT is therefore Phone Number Database a good example of a corporate in the Netherlands that recognizes the need for a fairly rigorous approach. Management realizes that this requires a Phone Number Database significant investment and is setting up a dedicated team to make data-driven marketing Phone Number Database a reality. Data science at publishers Publisher Sanoma also sees the value of customer data in marketing and has set up a team of data scientists to maximize.
Dirk Guijt is one of them and Phone Number Database went in depth on DDDME about how they can categorize topics across all their domains (from nu.nl to SBS and from Autoweek to Viva) by means of machine learning . Every visitor (whether logged in or not) receives a topic profile, which makes it clear which content is Phone Number Database interesting for that person. By dynamically processing this content in e-mails, Sanoma sees 24 percent more clicks. By tracking conversion rates of ads per segment, they then see which ads work on which topic profiles, so they find the right audiences within their platforms.