Digital publishers today are amassing volumes of ‘Big Data’ about their site visitors, which they could use to better engage with and target their audience. This may sound like a daunting task, and that is because it is. Publishers have access to so much data about their users that they often do not know how to make sense of it all, no less leverage it for financial gain. Fortunately, technology tools are available, such as data management platforms (DMPs), to simplify this monumental task.
Knowing their Readers
DMPs are used by businesses across the industry – marketers, ad agencies, e-commerce companies, and more. For publishers, DMPs can serve as the backbone of their digital operations, identifying who their audiences are, and determining their interests based on their online behaviors. Armed with this knowledge, the publishers can push relevant content and advertisements to them.
This data-driven granularity means more useful segments, for example, “those most likely to read articles about Iraq,” or “those actively searching for a new electric car in East London,” rather than just “males between 20-40 years old.” And that means better success rates for advertisements, and more profit for those serving up the ads.
At a minimum, a good DMP aggregates, analyses, segments and actions data. The best systems gain intelligence about the site visitor with each visit, and then through advanced analysis predict his or her interests and intent on the site. Armed with that knowledge, they then serve the most relevant content and ads, keeping readers on the site longer –increasing the odds of click-throughs to learn more about products and service offerings.
DMPs and Segmenting
With the right DMP, the publisher can see what trends, indicators, and segmentation methods are most powerful to create actionable insight from the gathered data. When the data are well organised, it makes it far easier to develop detailed individual profiles and customer segmentation based on a wide variety of data points (interests, demographic, location-based, behavioral, contextual, purchasing history, device and more).
The next important part of segmentation involves capturing results from targeted campaigns to update and optimise segments. New segments can be created based on user behavior – for example all those who clicked on a particular ad and article are grouped together. By introducing personalised elements based on user likes, the site is more engaging for users, and provides much higher conversion rates for classified listings, promotions and advertising.
Cross-device
Sophisticated DMPs can also track the audience across all devices used. This means the system knows a visitor who has seen an ad while browsing on a laptop should be served a different iteration of the ad when he clicks on the site from his smartphone, for instance. The DMP also should be capable of gathering, analysing and actioning from all of the various access methods, combining the data to create individual user profiles and segments. In this way, the publisher will know that this particular reader will watch ads about fast food late at night, but not in the morning, for example.
While good DMP solutions provide actionable intelligence, better ones also offer the tools that allow for the action, such as an ad server or content recommendations tool to enable highly-targeted communication.
Actioning the Data in Real-Time
The most powerful DMPs, like our own DMP for publishers, enable businesses to gather, analyse and action data in real time so publishers can reach users with relevant and individualised content and ads while they are still on the publisher’s website.
The “real time” aspect is key because it allows for extended content recommendation personalisation levels. For instance, the publisher does not want to recommend articles the user has already read on another device, or that the reader has seen but not clicked on. By personalising the experience, the reader stays on the site longer, seeing more ads.
It is worth putting in the effort when deciding on the right DMP; breaking it down into manageable components should provide some guidance on what to look for before taking the plunge. A scalable DMP will sort the data, create segments and take it a step further – creating actionable insight out of data chaos in real time.