Interest targeting is the future of customer segmentation. It automates target group definition and messaging. Leading to more sales, new visitors and more personalized communication.
Even if all this sounds less than satisfactory, there are now solutions to the vast majority of challenges. Understanding interests and visitation motives is the holy grail for marketing concert or opera performances. Thanks to companies like Netflix, their scale and a technical mindset based on trial and error, the search for an answer to these questions has come to an end.
Putting the audience and their interests at the centre is no longer a luxury or a nice-to-have. It is the most successful, efficient and effective way in audience development and marketing. No more complicated and time-consuming CRM activities, no more guesswork about the right message or image, but a significant acceleration of processes and time savings of up to 90%. And all this with increasing independence from large platforms, greater reach and visibility, and higher data protection standards, because interest-based marketing does not rely on traditional web tracking methods for targeting new customers.
Understanding customers' interests increases independence from large platforms and opens new doors to other platforms and networks. Interest-based targeting works the same everywhere, is transferable and does not depend on years of presence on a particular platform. It levels the playing field between well-known and smaller institutions. No one wins based on brand awareness, only on relevance to your customers.
The ad tech industry is currently in a state of flux. Cookie-based attribution and targeting will disappear. For some use cases they will still work in the next 12-24 months, but the majority of institutions will already see big drops in attribution quality. All the proposed solutions therefore share one key element: they are all interest-based. They focus on the most important interests of the users. Those advertisers who know their customers best will be able to benefit the most. Those who rely on advertising platforms to find the right users, on the other hand, will have a hard time. Because in an interest-based ad market, lookalike audiences (custom in Facebook jargon) and retargeting campaigns are clearly losing ground.
The next wave of social platforms will be different. This one is characterised by algorithms, not networks.
A second aspect has an even greater impact on the daily business of many organisers. Facebook and Instagram are the best choice for most advertisers when it comes to reach and efficiency. However, competition in the digital social space is increasing rapidly. This will lead to a more fragmented market. This means that it is not enough to communicate and advertise on just one platform. Institutions need to be present on a variety of platforms. As early adopters of Facebook & Co, cultural institutions have benefited from the early days of the platforms when it was relatively easy to build substantial organic reach. The next wave of social platforms will be different. This one is characterised by algorithms, not networks. TikTok's secret to success is not a network: I don't see the best from my network, but the most appropriate from the entire content offering. A fundamental shift that so far is too often misunderstood. Interest-based customer insights enable the transfer of knowledge about visitors from one platform to another, which makes a cold start on a new platform much easier. For advertising campaigns based on interest targeting, organic reach is irrelevant, because interests are targeted, not existing connections!
The traditional customer insights approach relies on learning as much as possible about a particular customer. Age, gender, location, household size, education level, household income and much more. This is in stark contrast to an ever-increasing sensitivity in the handling of personal data. This is particularly important in Germany, which was only recently confirmed in a survey as the most privacy-sensitive country in the world. Interest Targeting protects the privacy of visitors because it does not require socio-demographic characteristics. No names are needed, a randomised ID is sufficient. This facilitates collaboration with internal or external systems and partners.
In an interest-based world, CRM systems are a thing of the past for managing newsletter and direct mail lists.
Selecting and addressing customers based on their interests is essential, but in the end, it is only 50 percent of the marketing task. To return to the example of the concert with Beethoven's 3rd Symphony: With a traditional approach, a marketing team would have targeted a key demographic and solved 50 percent of the campaign (who to target). They would probably have spent hours trawling through their CRM system to find the perfect filtering logic. How would that work with an interest-based method? Appropriate software delivers an optimally tailored list at the push of a button. No work for the marketing team. In an interest-based world, CRM systems are a thing of the past for managing newsletter and direct mail lists.
Instead, it means focusing on the other 50 percent of the campaign: the "what". Manual analysis will rarely help to understand which message should be sent. Interest-based customer understanding, on the other hand, can recommend detailed keywords and topics for each part of the message, and answer specific questions like: What should be written in the subject of an email? What headline should be used? Or which image should come first. For the last 10 years, people have focused on finding the perfect audience with all kinds of data points about each customer. But very, very little time and energy has been spent on an insight-driven methodology that helps marketers tailor messages to each individual audience. This will be the focus for the next 10 years.
Among a thousand interested visitors, you can probably identify a hundred different reasons for what they are interested in. Targeting all potential customers with the same message is not very efficient and certainly not a good experience for users. Interest targeting answers not only WHO but also WHAT, reliably and automatically.
Proceed with Part 3: What you need to do
Go back to Part 1: What we have learned in the last 10 years