Advertisers need audience scale as well as accurate location data for their campaigns to be successful
A lot of the “new kids on the block” in the mobile advertising world have recently been talking about the issue of location data “inaccuracy”
A lot of the “new kids on the block” in the mobile advertising world have recently been talking about the issue of location data “inaccuracy” – the term used to describe inaccurate, fraudulent and incomplete location data which is often supplied by publishers to increase the value of an impression. And quite rightly too! 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 “new kids” are also missing a crucial point. Removing data also removes audience scale which is required to make the proposition work for advertisers. So the question is: How do you remove bad data while maintaining a scalable audience?
Blis agrees if location advertising is done badly it wastes advertisers money because their ads are not sent to the right location. The industry is trying to address this issue and while location-targeting verification does filter out bad location data, it can remove as much as 85%. Using data mining, data analysis and data extraction techniques come as standard across the location advertising industry and 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 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. Again, 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.
But 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 Blis can bring something else to the table.
We have the ability to build audience scale in location-targeting by understanding the relationship between an IP addresses a specific buildings where there are all kinds of devices connected – mobiles, tablets and laptops. Our platform constantly matches IP addresses to locations globally at a rate of 3m per day. We refresh this data every 24 hours to ensure its accuracy and context. This is on top of the 330,000 global points of interest built into the Blis database.
Another way we build audience scale is through data partnerships with the leading public WiFi ISPs O2 and Sky, covering more than 40,000 hotspots in UK high street retailers. By overlaying this 2nd party location data to campaigns Blis can again add significant audience scale for an advertisers that would not have been there by only relying on lat long data. More screens, more accurate location data, bigger audience.
There is bad location data 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 Blis can do this for the market.