Identity-Free Targeting in a Post-Cookie World: Q&A with Nano Interactive

In this Q&A written exclusively for ExchangeWire, Carl White, CEO & co-founder of Nano Interactive, discusses identity-free targeting, how it can benefit advertisers and publishers, and what its future could look like in a post-cookie world.


What are the core benefits of identity-free targeting from the perspective of advertisers? What new opportunities does this shift open for marketers?

The loss of third-party cookies presents a great opportunity for those who embrace identity-free targeting, as they’re set to achieve increased reach, scale, and a more engaging user experience.

Identity-free targeting means that advertisers are able to deliver campaigns without any kind of identifiable user information - no first- or third-party cookies, no universal identifiers, no email addresses or any other proxies. Instead of IDs, advertisers can use live intent signals to intercept users the moment they perform their search. This has been proven to be the moment that they are most receptive to brand messaging. It is then possible to layer on advanced contextual targeting models encompassing on-page semantic and sentiment analysis to deliver ads across hyper-relevant and brand safe content with scale.

This approach, therefore, provides a durable and future-proofed approach to digital marketing, allowing advertisers to manage their campaigns regardless of changes made to browser or mobile identifiers. Identity-free targeting also provides increased reach for marketers. Users can be targeted across the open web in cookie and non-cookie environments. This opens up approximately more than 60% of inventory not available to advertisers employing a cookie-based activation strategy due to browser, cookie clearing or private browsing. It also overcomes challenges of reaching hidden valuable audiences across Apple devices.

We’re seeing first-party data become a popular alternative for marketers in their cookieless future strategy. However, most advertisers simply don’t have enough scalable first-party data, and therefore it isn’t realistic to expect that this data will be able to fully deliver on all of the needs of large clients. Realistically, businesses will need to use a patchwork of solutions and a large part of the targeting challenge posed will be best addressed by utilising new and scalable machine learning-driven contextual solutions to deliver successful advertising outcomes.


How are publishers set to benefit from the shift to identity-free advertising? How can both premium publishers, with ample logged-in users, and smaller publishers reap these benefits?

Due to the combined powers of live intent data and sentiment and semantic analysis, publishers are able to discover, curate, and deliver new audience segments that improve their overall yields and revenues.

Through such advanced learning models publishers can also understand their page content at a much deeper level, going beyond just keywords and categories to charting how intent evolves on their site over time. In addition, data can be fed back to enable publishers to understand which placements and content are driving the best attention. These rich insights fuel their future content and help optimise their sell-strategy, which in turn drives more revenue whilst driving incremental effectiveness for clients and brands (Nano are the only players in the market offering this combined intelligence).


How does identity-free targeting benefit the user both directly and indirectly? What steps can be taken by the industry to ensure user experience and consumer trust is maintained?

Live intent identity-free targeting is able to profile each ad request in a 100% privacy-compliant way. It doesn’t rely on third-party cookies or any other form of personal identifiers, and therefore it has been purpose-built to support trust and respect the users' privacy.

More directly, users are able to view ads relevant to them at the exact moment that they’re expressing intent, supporting them with their search and streamlining their online experiences. Garnering live data, such as a user's journey, combined with moment data (for example device, location, time of day) and advanced contextual analysis enables the best suitable segment for the request. IAS research found that 72% of consumers feel their perception of an ad is influenced by the content surrounding it, and 48% of consumers from the same survey prefer contextually targeted ads. There is therefore huge potential available for advertisers to increase attention, engagement and, ultimately, purchase intent.


How can advertisers further optimise their contextual and identity-free targeting solutions in the absence of cookie-based data?

Carl White, CEO & co-founder, Nano Interactive

By overlaying the semantic meaning behind the content and underlying sentiment analysis, and also by applying these techniques at the level of a product or a brand (what we call entity level analysis), we are able to deliver a 360 degree optimisation and targeting approach that operates perfectly in a live environment.

Sentiment analysis leverages Natural Language Processing (NLP) to extract and decode the levels of positivity or negativity in the content so it is then possible to analyse and compare a large subset of news articles, blog posts, and other content over time. This enables an understanding of the evolving intent landscape and topic sentiment over time. When applied at a brand or product level sentiment analysis can help to target successfully against competitor brands and products, as well as fully capitalising on positive sentiment environments for your own products or brand.


How are concerns around the measurement and attribution of identity-free targeting being addressed?

With the deprecation of third-party cookies, we know that the industry is grappling with the challenges of tracking and measurement. But on the flip side, it has brought with it a welcome opportunity for the industry to overcome its preoccupation with traditional measurement metrics. Marketers should start to look more broadly at newer, more meaningful brand-focused metrics which arguably give a truer picture of the quality of a user’s engagement with a brand's message.

Ultimately, we are now living in a world where the path to purchase is far more convoluted. The average person is estimated to be exposed to 4,000 commercial messages per day, therefore metrics like viewability no longer go far enough. A better understanding of the attention (user engagement) paid to an ad is much more significant.

As part of our identity-free, advanced contextual targeting capabilities, we’ve developed attention tracking and optimisation models such as Time In View. This metric enables us to optimise campaigns towards the length of time a viewable creative is displayed. This approach has been proven to have a much higher correlation to ad effectiveness. This goes beyond more standard optimisation approaches such as Viewability.

As an example, in a recent campaign for Superbet, we were able to prove the impact of optimising to attention using our Time In View (TIV) metric, over the standard CTR. As part of the campaign, we monitored the difference in brand uplift using a cookie-less brand lift study so we could track uplift. Results successfully showed that in optimising to attention we were able to deliver uplifts in every key brand metric versus CTR optimised activity. In fact, through optimising to attention we saw:

  • Sixty-two percent increase in prompted brand awareness
  • Fifty-eight percent increase in positive brand perception
  • One hundred and twenty-one percent increase in brand consideration
  • Thirty-three percent increase in unprompted brand awareness


What does the future of identity-free advertising look like?

Now is the time for advertisers to start testing solutions to prove that identity-free targeting approaches do in fact work. Brand advertisers should be embracing the opportunities and benefits that ID-free solutions bring to the user's engagement experience. Modern forms of contextual and sentiment analysis offer a route to a privacy-friendly targeting environment without the egregious downsides of past identity solutions. The most successful brand advertisers will be those that embrace new attention-based digital advertising models that help them to deliver measurable impacts on brand performance. Advertisers will now be able to enhance the effectiveness of their campaigns whilst knowing their users' privacy rights are fully protected.