With tighter legal restrictions on data use in advertising, browser crackdowns on third-party cookies, and increased consumer concern around how personal data is used in advertising, contextual targeting is becoming more and more attractive as an alternative to cookie-based targeting.
In response, we’re perhaps seeing more innovation around contextual targeting now than we have in a long time as advertisers look for contextual solutions which match audience targeting for effectiveness and efficiency. And some who work in the space believe the argument for contextual targeting is only going to get stronger with time.
“The current industry challenges around privacy mean identity based targeting is dying,” said Raman Sidhu, VP of business development at Beemray, a tech company which looks at what they call ‘human context’. “There are solutions around that, but they’re effectively workarounds, and they’re not robust ways of dealing with the challenges that the marketplace is facing.”
Sidhu says the industry has perhaps been somewhat complacent for several years with cookie-based targeting. “I think the industry to some degree stopped innovating, or maybe the innovations have mainly been focussed around playing cat and mouse with GAFA [Google, Amazon, Facebook and Apples],” he said. But he believes that innovation is now needed, as the workarounds to cookie-targeting restrictions and privacy regulations won’t hold up long-term.
Targeting Moments, Moods and Mindsets
Beemray hopes that “human context” targeting can be a viable alternative. While contextual targeting traditionally looks at the content a user is consuming as a basis for ad targeting, Beemray says human context also takes into account the user’s mindset, as well as external factors which could impact their behaviour. “What we’re providing is the ability to analyse and target moods, moments and mindsets, and to do that in real time – to both analyse and target them as they occur,” said Sidhu.
To do this, Beemray effectively sits with the supply-side platform or demand-side platform and ingests data provided within the bid request, for example an IP address, a lat/long, and the URL. This data provided is put through Beemray’s algorithms to pick out several attributes which can be applied to that individual – for example, whether they’re at home, commuting, or at work; or hether they’re an early riser or a night owl. External data on weather, traffic, financial markets, and sports results among other things is then layered in, the idea being that all these things combined paint a picture of the “moment” that individual is currently in.
“Effectively we take the raw data we receive and replace it with the information that we see that is of value, within ten milliseconds,” said Sidhu.
Bridging the Gap Between Media Buying and Analytics
Beemray says part of the value of this data is to use it either to decide whether to bid for a specific impression or not, or to decide which creative to serve.
“A lot of brands are talking about targeting ‘consumption moments’ – the moment that a consumer is most likely to buy their goods. So for a coffee company it could be when they’re commuting to work, for a drinks company it could be people who are currently on holiday.”
A coffee brand, then, could decide only to bid for impressions where Beemray’s analysis shows the consumer is commuting to work. Or alternatively, they may decide to serve one ad when the individual is commuting to work, and a different ad when they’re at home.
But Sidhu says a lot of the value comes from helping advertisers build profiles of who their customer bases are, which helps with targeting, as well as with the wider functioning of the business. “When you look at the multiple attributes that we can highlight from each request, it helps brands get a better level of insight on the type of consumer they’re looking for, without having to rely on a persistent identity or third-party cookie,” said Sidhu. “It helps them to build a profile of the type of consumer they should be targeting.”
Beemray believes this can serve as a viable alternative to audience targeting as it currently stands, in part because of the similarity. “This model is kind of like an extension of how people have been looking at audiences. With audience targeting, you’re saying “this group of people have done this thing at some point in the past”. In our case, we’re able to look at multiple data cues to see what behaviour people are exhibiting right now,” said Sidhu.
To use an extreme example, a particular brand might find over time that they get the most success from targeting early birds and workaholics when its just started raining and their football team has just scored.
Brands could use this information for future targeting, or even those without in-house media buying might value it in terms of business intelligence. And Sidhu believes that if this same data is used by both media buying and business intelligence departments within brands, that’ll be beneficial for the brand overall. “We’re trying to bridge gaps between media buying and business intelligence, and do it in a smarter way, whilst maintaining transparency and control between the brand and the media buying part of it,” he said.
Identity Under Threat Beyond Cookie Targeting
Sidhu says it’s likely that the noose around cookie targeting’s neck will carry on tightening. “The fallout of privacy has led to browsers changing the way they handle identity, and the timeouts they put on cookies,” he said. “But looking forward, it’s totally feasible that a lot of identity solutions used on mobiles as well will have some sort of timeout or diminish completely. So what we’re building is an infrastructure for that future.”
How ready the industry will be to let go of audience targeting remains to be seen, and indeed Beemray isn’t relying on cookie-targeting dying out completely as it works in complement to it as well. And a measure of education would be required to help advertisers understand human context as an alternative to audience targeting.
But if cookie-based targeting does die out completely, brands will certainly be keen to maintain the precision targeting they’ve become accustomed to through digital advertising. Any solutions which help meet that demand will likely do well.