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Why location-based dynamic audiences are the key to targeting in a post-cookie world

By Kate Kaczmarek, Senior Product Manager at Blis

As someone who has worked in the industry for more than five years, I have never known a time of such incredible change for the ad tech ecosystem as 2021. While Blis is fully attuned to and prepared for the upcoming disruption, there is still a significant number of vendors that don’t appreciate the scale of the change and most importantly the impact it is going to have on all stages of planning, delivering and measuring the digital advertising strategy.

The final withdrawal of third-party cookies from Google’s Chrome web browser and the recent launch of iOS 14.5 from Apple will negatively impact advertisers’ ability to target individual users and track their cross-site activity and physical location. Without those cookies and with fewer individual identifiers from iPhones to rely on, many marketers are now looking for alternative ways to target and engage their key audiences in specific locations.

For many businesses and their media buyers, location is an important element of their advertising strategy resulting in bidding on and buying specific media inventory that will drive the most value. One of the major uses of location information in targeting strategies is the ability to reach people while they are in a specific place at a specific time of the day. Retailers, for example, may wish to concentrate their campaign on serving ads to the mobile phones of people currently located within a short distance from one of their bricks-and-mortar stores in order to maximise on the chances of people coming into these stores.

Location, location, location

While location data is not regarded as a ‘personal identifier’ as such, it is still personal data, and privacy regulations such as GDPR (General Data Protection Regulation) and Apple’s recent iOS 14.5 update make it clear that consumers should always be given the option to opt out of sharing their device’s GPS location data with external vendors. Lots of consumers choose to do just that.

At Blis, for example, we see around 1.5 billion individual signals being fed into our platform every day, but only a relatively small percentage of those, typically, somewhere between 5-10%, contain location data. That ratio alone makes it difficult for marketers looking to target people by location as it restricts them to bidding on a very small portion of the available inventory out there.

As this data is already scarce, it poses a further problem for advertisers to deal with the high level of industry fraud associated with location data. Some publishers, in the absence of a GPS signal, choose to ‘guesstimate’ or randomise the location of their audience, using a variety of unreliable techniques. For this reason, at Blis, we heavily filter the GPS data we receive into our platform and often reject up to 80% if it shows any characteristics of fraud, inconsistency or doubt that the data might not represent human behaviour. A consequence of this filtering process, of course, is that it shrinks the available buying opportunities for advertisers even further.

Scale model

None of the issues mentioned above are particularly new problems. In response, around five years ago, Blis developed its own way to physically locate someone without receiving a GPS signal from their phone in order to future-proof location advertising and help advertisers to effectively reach the relevant audiences.

Our solution, Smart Scale, is a proprietary technology that builds a reliable, accurate and scalable location data by automatically and regularly detecting the relationships between Wi-Fi hotspots and their IP addresses) in order to physically locate them. This anonymised dataset is then used for scaling the ability to target people in these locations in real-time.

By looking for and analysing patterns in the usage of Wi-Fi hotspots, we can be confident that an IP address belongs to a specific business, based in a particular area. If you’re trying to reach anybody within that area, targeting any of the IP addresses we’ve identified allows you to really extend your reach and achieve the scale you’re looking for. When a dynamic IP address gets reassigned to a different location (which happens a lot), Smart Scale corrects itself in real-time, refreshing its database of IP addresses every four hours to keep it up to date and accurate at all times.

Proximity is possible

At Blis, we can confidently say that both proximity targeting at scale will still be possible in a post-cookie world, and with the right strategies, tools and approach, brands can continue to achieve great results.

*Blis is a client of Bluestripe Communications, owned by Bluestripe Group, owner of NDA.

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