Read the original article in Italian on Data Manager here.

Over the past decade the massive growth in smartphone usage has prompted the development of a wide range of location-powered ad-tech solutions for brand marketers and agencies. From analytics solutions through to media activation opportunities, a confusing array of ad-tech vendors have emerged, all promising marketers the ability to target consumers based on their location in real-time. 

When it comes to unlocking the potential of location-based marketing, it’s important to remember that not all location data is created equal and, what’s more, that many of the ad-tech solutions on the market are vulnerable to the negative impacts of bad location data. For brands and their agencies, this is an issue of increasing importance. 

Given the growing restrictions on the use of third-party cookies and personal identifiers to track customers across the internet, many marketers are turning to location-based ‘contextual’ marketing campaigns to help plug the targeting gap, i.e. using knowledge of a person’s physical location to target them with highly relevant messaging. However, when using hyperlocal data as part of an advertising strategy, the accuracy and the precision of the data being used is absolutely vital to the success of any campaign. 

For example, imagine there’s a male consumer working out at the gym on his local high street, but poor-quality location data places him in a fast food restaurant 200 metres down the road. For marketers, this sort of bad location data is worse than no data at all, as it grossly misrepresents the audience that the brand is trying to profile and leads to marketing budgets being wasted on the wrong people. 

The scale and widespread use of bad location data often comes as a surprise to marketers. In the Italian market, for example, we at Blis regularly flag up to 65% of location data that we see coming into our platform every day as suspicious. This equates to millions of impressions and, potentially, a very significant amount of wasted media spend if left unchecked and unfiltered. But what exactly do we mean by ‘bad location data’? 

Bad location data: 3 examples

GPS data, the most well-known and highly regarded location signal. It is widely considered to be reliable as it is sourced directly from the GPS chips in a phone’s hardware and can be accurate up to five metres. This data typically comes in the form of latitude and longitude coordinates. Each extra decimal place in a set of latitudes and longitudes is equivalent to an additional 10 metres in accuracy. Best practice is to use lat-longs with four or more decimal places, making them accurate to around 11 metres. From a marketer’s perspective, this all sounds great, right?

However, some publishers round up their lat-long signals, which can greatly reduce the precision of the location data being fed into advertising campaigns. There are some other inconsistencies to look out for that are indicators of bad location data. For example:

• Lat-long signals that correspond perfectly with a location known to be a ‘centroid’, the centre point of a wider geographical area, as used by the large ‘IP to location’ databases; 

• Lat-long signals that form suspicious grid like patterns when mapped out across the city or country; 

• Lat-long points that see an unreasonably high volume of data tracking through often a single square metre, such as millions of impressions a day.

All data conforming to these patterns should be removed from any location data set immediately. They are imprecise and misleading, resulting in inefficient use of valuable marketing spend. 

As a brand or an agency, it is vital to ask the right questions of your location-based marketing partners and their machine-led verification technology. Now, more than ever, marketers need to ensure that they are working with truly accurate location data. Only then will they begin to leverage the incredible potential of location intelligence technology as a marketing tool.