Our location has become pivotal to our mobile lives. From Uber pinpointing exactly where we need a ride from, to dating apps which connect us with people nearby, sharing our location vastly improves the service we get.
The power of location in advertising is not lost on the majority of leading brands and agencies. In fact, mobile accounted for $76.17 billion of US media ad spend in 2018, according to eMarketer, with a large proportion of this being location-targeted.
However, the meteoric rise of location-based advertising means that few brands have taken a step back to analyse the quality of the location data they are getting. Most rely on third party location signals and the ugly reality is that (like many parts of the digital and programmatic ecosystem) there are murky players. It is a landscape plagued by fraud, unclear methodologies, and wildly different standards in quality and accuracy.
As a result, brands and their agencies are often missing the level of precision they need to deliver high-impact location-targeted campaigns. They could have all the best intentions to reach real and relevant mobile audiencesthrough location signals, but miss the full potential of this technology. There are some companies doing great work in this space. Yet in a market which lacks transparency, it’s impossible to separate the good from the bad.
Location ad-fraud has therefore become a massive problem for the advertising industry. Brands and their agencies count on the fact that the premium location data they buy to drive media campaign decisions is valid, yet it cannot always be trusted. Manipulation and bad practice is prevalent across the entire value chain.
This puts huge sums of ad spend at risk. As campaign budgets are increasingly squeezed, it has never been more important for brands and their agencies to understand the quality of location signals. Here’s how they can ensure locations are accurate and their campaigns are optimised:
Look at the types of location data
You can divide location sources into two categories: GPS data and IP data. The type you use will depend on your campaign goals. While IP data is a good fit for city-level targeting, drilling down to more localised areas will require more expensive GPS data. Understanding the differences between the two types of location data is the first step for brands to identify potential quality issues. For example, the accuracy of IP data depends on the uniqueness of the IP address and the quality of the IP-to-location database being used. With GPS data it’s possible for an unscrupulous app publisher to provide a randomly-generated location in place of a real one.
There are multiple anomalies brands should be looking out for when they are running location-based campaigns. For example, mobile users may be spotted at multiple locations a large distance apart within a short space of time. It’s simply not possible for a user to be in London one minute and in Yorkshire the next. Other red flags might be a location that appears to be in the middle of the Thames, or an app that is sending multiple device IDs from the same location. The only way to identify these inaccuracies and address ad-fraud is to have a clear view of where ads are being served, and to monitor performance throughout the campaign lifecycle.
Establish new standards
There are already initiatives such as the Joint Industry Committee for Web Standards for brand safety, ads.txt for fraud and the Interactive Advertising Bureau gold standard for quality. It’s time that location data was also held to account. The marketplace remains unregulated and unmonitored, making the quality and authenticity of location signals impossible to verify.Technology that independently authenticates location should be used to make sure budget is spent how and where it is intended.
Greater transparency over location quality and location ad-fraud will help brands make sure ad spend is maximised. By not burying their heads in the sand, and giving this issue real attention, they will be able to optimise their location-based campaigns and get even better results.