Intent /ĭn-tĕnt′/ (noun): the thing that one plans to do or achieve – an aim or purpose.
The original benefit of digital advertising was having access to data that other media couldn’t reach. Data that would help advertisers understand people’s intent online, even as it was being expressed.
But then signal loss became the overriding market trend. And Google Chrome’s on-off cookie breakup is just the latest, most prominent example. Zooming out, it would appear people-based data – once widely gathered and shared across the ecosystem – is going out of fashion.
The Journey from Contextual to Intent
Content as a proxy for audience pre-dates the internet: think of print ads placed in a motoring magazine, or target rating points (TRPs) in the world of TV. And in turn, contextual targeting online also pre-dated audience- or people-based methods.
In the early days, contextual targeting online meant little more than website vertical – not much different to its print cousin.
Then it evolved to targeting by keywords appearing in the website URL. And there it stayed for a long time. A progression surely – but not exactly earth shattering, even as audience targeting overtook context, as programmatic took hold. And with it, the range of people-based data signals available to buyers grew – at least until the past few years, when that process seemed to go into reverse with signal loss.
Context’s re-emergence on the scene was enabled by advances in machine learning (ML) and natural language processing (NLP) – both of which predate the current market obsession with generative AI – allowing contextual platforms to include page copy in full, as opposed to just URLs. And meaning rather than just keywords.
Intent Graph
In its third iteration – don’t call it contextual 3.0 – further developments in ML and the RTB protocol have allowed us to refine and enhance content signals further – while steering clear of cookie-like IDs or building profiles of individual consumers. These insights range from estimated search terms used to reach a specific page, to time of day or weather.
It is here we can define exactly what we mean by intent – the above live data, with next-gen contextual information and placement-level performance insights – all recorded in Nano’s LIIFT™ Platform.
Intent Graph is the product that allows Nano to make sense of those 4.9b+ intent signals it deciphers daily, parsing, sorting and connecting this abundance of signals.
Blending all of these non-people-based datapoints enables Nano to build custom targeting strategies focused on scalability, relevance and dynamically optimised to deliver performance.
Since, as some argue, the linear path to purchase no longer exists, intent is now present at every stage and important to measure throughout the funnel. Some refer to this phenomenon as the ‘messy middle.’
In With the Old, In With the New
In a further development for intent and content as a proxy for targeting, in 2023 Nano launched Intent Personas.
This product is unique to Nano – bringing together all of the above, advanced developments in intent targeting, alongside trusted verification of those targeting choices in the shape of a panel.
Advancements in AI have allowed us to develop our technology faster than we could have even imagined just a few years ago, but its true strength lies in the combination of tech and human validation: panel research is used to verify the content of each segment, authenticating its accuracy, while removing any question of stereotypes.
