Publishers will be well aware that, despite Google’s stay of execution, the end of third-party cookies remains on the horizon, and so too do the challenges associated with this change.  The only difference is they have longer to prepare. 

Alternative solutions might be in the works, but most are still in the initial stages of testing and are far from issue-free, especially when it comes to data access and adoption by the market players. 

Many publishers recognize that first-party data presents a viable alternative – the wealth of audience information they already hold has significant power to fuel revenue streams. But the issue now lies with unlocking its potential and making it a scalable solution. 

To use their existing data assets well, publishers need to convert them into a complete view of users that allows for better understanding, segmentation, and revenue generation. 

So, could the answer lie with smarter analytics? 

Owning data is not enough to stay competitive

The key problem for publishers looking to tap their first-party data more effectively is that it’s often a complex, time-consuming task. Users engage with content in many different ways, and their interactions produce huge volumes of unstructured data. Additionally, information within disordered data pools is frequently incomplete. For example, audiences will usually be a mix of logged-in users — for whom publishers have consent to gather certain data and a record of some attributes, but not all — and opted-out visitors who are anonymous. 

Most publishers, therefore, end up with a jumble of data pieces that can be hard to decipher, especially when internal data handling capability is lacking. Some elements will be simpler to track and assess – such as the number of visits and time spent on sites – but these data points alone aren’t enough to produce the complete view of individuals needed to provide tailored content that bolsters engagement or builds detailed advertising profiles, particularly for anonymous users or those who choose not to share key details, such as age and gender. 

This, however, is where analytics comes in. With the right evaluation tools, publishers can unify fragmented audience data and gain valuable insights into user interests and behaviours; and that’s just the start. 

Using more sophisticated predictions

Analytics technology can take on the heavy lifting of data management at a basic level and help publishers make their first-party assets usable. Instead of manually navigating vast stacks of disparate information, they can harness automated mechanisms to blend, cleanse, and harmonize data into a consolidated hub. From there, it’s easier to apply initial analysis to uncover insights previously lost in the chaos – such as which types of content logged-in users prefer or common search queries that indicate popular topics. 

But it’s in the next phase of data processing where the full value of innovative analysis truly becomes clear. When used in conjunction with machine learning predictive analytics, it can enable publishers to coordinate their data better and enrich it, filling in the gaps for specific users and leveraging existing data to predict the behaviours of anonymous users. 

By harnessing the known attributes of specific users, smart analytics tech can use audience modelling to expand insight scope significantly. Moreover, artificially intelligent (AI) algorithms can leverage ‘ground truths’ – such as account information – to identify key trends for individuals with certain traits and augment users who share the same characteristics or follow similar behaviour patterns. 

The core benefit of this data extension is, of course, sustaining advertising appeal without depending on third-party cookies. By making the best of their own data, publishers can achieve refined audience segmentation and continue to offer precisely tailored placements in real-time and at scale. This in-depth understanding of user attributes enables publishers’ marketing teams to predict which products are more likely to capture user interest, pinpoint the most receptive audiences, and deliver a more tailored experience. 

Related:  The Need for A Fake News Solution

Unlocking consumer insights to boost loyalty

Now we come to every publisher’s most enduring core priority: experience optimization. In today’s highly competitive online environment, success increasingly relies on speed and relevance. To grow a large, loyal audience monetized, publishers must quickly hook user attention by presenting truly engaging content that speaks to their unique tastes. Once again, this is an area where the effective deployment of analytics provides a crucial advantage. 

Through granular analysis of real-time site interaction, AI algorithms can instantly deliver an in-depth view of individual habits, preferences, and even sentiment towards specific content. This comprehensive insight forms the ideal foundation for personalized content recommendations. Not only does it demonstrate publisher commitment to meeting audience needs, but it also creates streamlined experiences that strengthen user relationships, sustains loyalty, and heightens the value of audiences – which in turn attracts ad spend. 

And that’s not all. Publishers can also tap advanced predictive analytics to combine incoming data with historical behavioural patterns and accurately predict the next content users are likely to engage with. As well as paving the way for relevant, personalized experiences that add extra value for users, these insights can further boost advertising opportunities, allowing publishers to match ads in line with current user needs and the topics — and products — with the highest probability of sparking their interest in future.

Future-proofing targeting strategies and audience growth

Smart analytics can also give publishers a view of how users engage with specific content across various digital properties. Not only does this further enrich user profiles with granular insights around interests, but it lets publishers optimize the experience on audiences’ preferred digital devices as well. With the average US household owning 10 internet-enabled devices, which is expected to hit 15 by 2030, engaging desired segments however they interact with content is hugely important.  

Moreover, using this insight to ensure highly relevant advertising for each environment will enhance the publisher reputation. The stereotype of irritating, disruptive digital ads is becoming a thing of the past, and advanced analytics is essential for understanding how receptive consumers are at each stage of their digital journey. This level of audience insights is very appealing for advertisers and will support publishers in effectively monetizing their inventory and bolstering revenue streams.   

Alongside improving targeting capabilities across multiple platforms, smart analytics offers publishers the potential to fuel audience expansion. When combined with real-time context and content data, predictive capabilities make impressions addressable without user-level data. In turn, this can support retargeting methods, allowing publishers and advertisers to match audiences using clean-room technology. In addition, by providing clarity into trends and shared preferences, these solutions enable publishers to reach more users across all devices. 

Shifting their focus towards first-party data is a step in the right direction for publishers. As they continue to look for new ways to thrive without third-party cookies, unleashing the value of their owned content assets will be crucial to retain the advertising edge and keep delivering the personalized experiences users expect. But before they can put their first-party information into effective action, they’ll need to strengthen their ability to organize and harness it, and that will call for smarter analytics.

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