In the early days of the California Gold Rush, prospectors had it easy. Stories circulated of vast fortunes being made overnight, with huge quantities of gold lying in rivers just waiting to be discovered. By the mid 1850s, of course, the easy pickings had long gone, and miners had to go through backbreaking work for diminishing returns.
Something not too dissimilar is happening now to the digital advertising industry. The industry is at something of an inflection point. Behind us are the ‘gold rush’ years of the industry. Thanks to cookies and Mobile Advertising IDs, publishers and advertisers have been saturated with data. Meanwhile, the adtech industry has evolved rapidly and created an ecosystem that can serve perfectly personalised content to individuals in real-time. The model is so accurate in targeting people that some are even convinced that the big tech companies are secretly listening to us through our phones.
Ahead of us lies a new, privacy-first industry, where data will be much harder to come by. The General Data Protection Regulation (GDPR) is having a profound impact on data availability. Cookies are on the way out, and the data available through Mobile Device IDs is depreciating. The data that fuelled the gold rush era is drying up. But that doesn’t mean the prospectors should leave town. Rather, the digital advertising era needs to adapt and innovate new ways to reach the right audiences with the right message. Here, context will be everything.
Context-based advertising is nothing new. Brands place ads next to content that is relevant to their product or service. It’s advertising 101: a sports shoe brand will place ads on a sports training app, for instance. Location-based advertising isn’t new either: brands place adverts in locations they’re likely to be seen by the right audience. Our sports shoe brand, for instance, may choose to display their advert on a digital frame in a sports stadium.
However, thanks to advances in adtech, brands can now go much further and use context-aware data as a substitute for personal data. Think of this as ‘context 2.0’. It provides a means to target individuals without compromising privacy one iota.
Sharpening proximity targeting
One of the most exciting advances in the context-based geo-targeting revolution is the ability to predict human mobility across geographical locations, such as parts of cities. Here, audiences are targeted in real-time based on where and when they go to various locations within a city. Imagine, as that sports shoe brand, being able to activate a marketing message on a digital billboard the moment a sports lover walks by, and then retargeting that same person on their mobile device moments later.
This builds on the existing proximity targeting value proposition. Proximity targeting traditionally targets based on location context. For example, census data might reveal high income areas, allowing luxury brands to target people in those areas with ads sent to their devices or Digital Out of Home Displays within the radius. It’s a great approach for reaching that specific audience, but it’s worth noting that all people in that area are served the ad – even those who are just passing through and who may not be from the target audience.
Proximity targeting is also a good way to target people within a given radius of a store location. A steakhouse restaurant chain, for instance, might advertise to anyone within 500 metres of its restaurant. Of course, as well as catching the eye of all the ribeye lovers in the area, it’s also possible that vegetarians and vegans will catch sight of the ad.
Today, however, brands can target areas based on audience movement. By combining consented mobile audience data with SDK-derived background movement data and overlaying it on top of spatial data such as geometries or OOH poster locations, brands can build a precise picture of their audiences as they move through their towns and cities.
Calculating ‘Audiences in Motion’
The approach relies on being able to calculate indexes for each audience segment based on the ratio between all users within a geographic area and the desired audience. Using these calculations, brands can score each audience segment for each geometry and for each hour of the day. This allows brands to build up a picture of exactly where their target audiences go throughout the day, and what times they go there.
Armed with this information, brands need only serve the ad. Using their Demand Side Platform of choice, advertisers can integrate geo-location context data pre-bid. In short, advertisers can reach audiences’ devices, or Out of Home screens, based on their location in the exact moment of an ad impression – serving just the right ad to just the right audience at just the right moment and in just the right place.
A specific data type that is currently highly demanded when it comes to applying data through a spatial lens is telco data. Spatial telco data is cross-referenced movement and CRM data in an aggregated and anonymised form connected to a geographic level such as postal code. Spatial telco data helps programmatic advertisers to target the right local context without relying on cookies, Mobile Advertising IDs or other PII identifiers.
But it is not the only data element that is helping to reimagine contextual advertising for our privacy-first age. There are other proximity-based datasets such as places data, aggregated census data, weather data or geo-located purchase and social data.
Say, for example, a high-end handbag brand hopes to target wealthy women with ads for its new luxury handbag. Census data will show where wealthy individuals live in a city, as has long been the case with proximity targeting. However, now the brand can go further and use audience movement information to identify specific frames within the area that are overrepresented by women during the course of any given day. The approach means the brand is not only targeting the right locations to reach its audience, but the right time of day too.
There’s no getting away from the fact that the adtech ecosystem is having to adapt to a very different world. However, as events unfold the worst predictions about GDPR and the decline of Mobile Device IDs is not coming to pass. Instead, the industry is finding new ways to target audiences with the right messages and in the right moment. New kinds of context-aware advertising are a key part of this innovation, and will play a fundamental role in the new era of digital advertising we see emerging today.
Tom Laband, CEO & Co-Founder at Adsquare
© Copyright Adsquare 2022
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