Advertisers need accurate location data in real time with audience scale for their campaigns to be successful
7 March 2018
Recently, a lot of the “kids on the block” in the world of mobile advertising have been talking about the issue of location data inaccuracy. Referring to the inaccurate, fraudulent, and incomplete location data which is often supplied by publishers to increase the value of an impression this discussion is an important one. However, verifying the quality of data should be standard practice in any business dealing with huge volumes of data and not some massive revelation or secret sauce.
These “kids” are also missing a crucial point: removing data also removes audience scale; which is required to make the proposition work for advertisers.
So herein lies the question: how do you remove bad data while maintaining a scalable audience?
Mobiclicks agrees; if location advertising is done poorly this works in advertisers’ disfavour, both monetarily and in terms of ad relevancy, as their ads aren’t sent to the right location. The industry itself is trying to address this issue and while location-targeting verification does filter out bad location data, it can only remove as much as 85%. The use of data mining, data analysis and data extraction techniques are a standard across the location advertising industry and Mobiclicks’ location partner Blis, has been doing this for years. Each of us has different technologies to tackle this issue but we are all in agreement; there is a lot of bad data.
Even good location data needs filtering to ensure it is “brand safe” for an advertiser. Location data provided by certain dating apps, for example, might have accurate Lat/Long GPS coordinates but it may not be an appropriate ad placement for an advertiser and could lead to negative brand association. If, and this is a big if, your location provider has built the right proprietary tools to understand where the lat/long data is coming from, it can remove the wrong impressions for your brand. This kind of filtering should be standard across the industry. Less than 5% of the data coming into the Blis platform from publishers can be verified as ‘good data’ and matched to our customer’s campaigns.
With all this filtering removing location data, how do you build audience scale for an advertiser? Lat long does provide good proximity but it doesn’t provide real scale. If a location-specific ad is to generate successful engagement a brand needs a bigger audience. This is where we can bring something else to the table.
We build audience scale in location-targeting by understanding the relationship between an IP address at a specific building and the devices connected (whether that be mobiles, tablets or laptops). Our platform constantly matches IP addresses to locations globally at a rate of 10million per day. We refresh this data every 24 hours to ensure its accuracy and context. This is in addition to the 630,000 global points of interest built into the Blis database.
Another way we build audience scale is through data partnerships. By overlaying this 2nd party location data to campaigns Mobiclicks can again add significant audience scale for an advertiser that would not have been there previously by only relying on lat/long data. Thus: more screens, more accurate location data, bigger audience.
Bad location data is everywhere and it’s available to everyone. Filtering it out solves this problem but without adding other content, demographic and 2nd/3rd party data, advertisers will always be faced with reducing scale. Only Mobiclicks can do this for the market.
This proprietary technology enables agencies/brands to harness the power of location and understand real-world behaviour, in real time.
Christopher Wilson Partnership & Sales Director – Africa