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As we migrate to a post cookie world, brands and advertisers will now be thinking about new ways that they can reach consumers effectively. This week, Johann Hermann, our COO, caught up with Exchangewire’s Ciaran O’Kane on its latest episode of ‘TraderTalk TV’ to discuss Identity-Free Consumer Intent Targeting.
Consumer Intent Score – Powered by machine learning
Johann started by explaining the different approaches brands are exploring when you are considering the death of the first-party cookie. The first is to consider an identity solution, but though effective these come with their limitations. The alternative is to consider Identity-Free Consumer Intent Targeting.
To put it into context – when looking at the websites a typical user visits on a regular basis, there are very few that you need to be logged into, therefore limiting the reach and targeting effectiveness if you are dependent on identity-only solutions .
However, combining live user intent signals and a more advanced form of contextual targeting, powered by machine learning, the outcomes can be far more effective. Our CIS technology leverages a range of signals across four categories: User Journey Score, Moment Score, Brand Relevance Score, and Interaction Score. Collectively the outcome indicates the influence an ad will have on achieving the campaign goal.
The score and the sub scores can have values ranging from 0 to 10, with 10 representing the maximum influence an ad could have. The scoring is unique to an advertiser’s campaign and every campaign has its own custom algorithm. Working with the advertiser to identify what they want to achieve upfront allows us to determine the required score for each ad request to serve a specific ad, within a certain environment so they achieve their goal. If the score isn’t favourable – the ad isn’t shown. Through our machine learning extrapolating data from thousands of campaigns it allows us to more accurately predict the best outcome, and deliver an ad based on this. This data provides Nano with a bank of knowledge and constantly refreshed learnings that new players to the market can’t compete with.
Our new browser extension – a window into our Machine learning
Johann then gave a live demo of the CIS at work using our new browser extension – a media first and a unique offering from Nano. The browser extension allows marketers to have full transparency over how the product works in real-time, allowing them to understand the benefits of using machine learning to ensure their message shows up in front of the right audience.
With brands often referring to machine learning as a ‘black box’, the browser extension allows us to dispel any ambiguity surrounding it and demonstrate how CIS works live, against any publisher page within the network.
To find out more about Identity-Free Consumer Intent Targeting and the Consumer Intent Score (CIS) please contact email@example.com to ask any questions or book in a live demo of the technology at work.