When proximity advertising first arrived on the scene almost fifteen years ago, the ability to serve up deals or ads to consumers based on their location was considered groundbreaking. Today, location data is used for much more. Embraced by marketers as a way to understand real-world behavior both historically and in real-time, its use cases span from planning out-of-home advertisements to building audience segments for targeting, and ad measurement and attribution.
Location data presents enormous potential for marketers to deliver personalized, and ideally relevant and timely, messaging to consumers and to do so cost-effectively–so why was $4 billion of the $16 billion spent1 on targeted mobile ads this year wasted?
Turns out, according to a Forrester study, 94 percent of mobile marketers have difficulty working with location data, with the biggest challenge being the inaccuracy of the data. Research shows that 59 percent of location data is inaccurate — this is a huge problem for marketers who have custom-created ads based on that inaccurate data. The results are ineffective advertising and billions of wasted ad dollars.
Until recently, there was no real solution to this problem. When the three most common sources of location data are GPS, Wi-Fi access points, and tower cell triangulation, marketers are sometimes forced to choose between accuracy, precision, and scale. Ultimately, these trade-offs risk running ‘targeted’ location-based campaigns that completely miss their mark.