Click Insights: Understanding location data and why accurate location-based targeting works

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If a brand or media agency is interested in leveraging location strategies with any partner, it’s important to ask the right questions about how they approach filtering out bad location data. In-house technology, able to accurately detect and remove bad data, is absolutely critical for any player in the location space.

Amy Fox, Product Director of Blis talks about good vs bad location data and why accurate location-based intelligence is so valuable and exciting.

So how can you tell the difference between good location data and bad?

Firstly, start by looking at where the data is sourced from. Key to this is GPS data.

GPS data is highly regarded as the most reliable location signal because it is sourced directly from the GPS chip in a phone’s hardware and can be accurate up to 5 metres – the same data used by your maps or uber apps.

To access the GPS chip in your phone, an app must have explicit permission from the user (those pop-up consent pages when you first download a new app). If the user doesn’t allow the app access to location data from the phone, then the publisher cannot use GPS data in any way.

Because of the increased CPM value associated with location data, some publishers have developed alternative means to ‘estimate’ a user’s location when they don’t have access to GPS data – and none of these is good enough for precise location targeting.

But how can you tell when this is happening?

GPS data comes in the form of latitude and longitude coordinates. Each extra decimal place in a set of lat/longs is equivalent to an additional 10m accuracy and best practice is to use lat/longs that have 4 or more decimal points (accurate to around 11 metres).

Some publishers ’round-up’ lat/longs, which, in fact, reduces their precision, they might look like they’re in a gym when they really are 100m down the road in a McDonalds. We view any latitude or longitude with 3 or fewer decimal points not precise enough to be considered good location data.

There are other inconsistencies that are the hallmarks of bad location data, some examples of these could be:

  • Lat/long signals that correspond perfectly with points known to be centroids used by the large IP-to-location databases.

  • Lat/long signals that form suspicious grid-like patterns when mapped out across a city or country.

  • And lat/long points that see an unreasonably high volume of data trafficking through them, often a single square meter seeing millions of impressions a day.

All data conforming to these patterns should immediately be removed from any location dataset as they are accurate, at best, only to city level.

As you can see, there is a lot of bad data to contend with, and these are only 3 examples of this. As a brand or agency, it is important for you to understand this, in order to ask the right questions of your potential location partners and their machine-led verification technology.

Why accurate location-based targeting works

Once you know you’re working with accurate data – you can really start to explore your options for how to use location technology to it’s best.

Location data is multidirectional and can work for a brand in a variety of ways.

Not only is it useful to reach a consumer within a catchment area of a particular store, but, when repeated visits over a period of time can be joined using mobile advertising IDs, location data can also be used to build a segment of consumers who have historically visited a particular store or brand.

This historical view of location data is very powerful as a brand can define time, recency and frequency of visits to build a really precise and relevant audience to target.

Not only that, but location data is also the most accurate indicator of ’real’ behaviour and intent at scale vs any other type of data. This is because location data tells us what people actually do as opposed to what people say they are going to do. For example, you might spend a lot of time aspirationally browsing high-end fashion magazines, but a physical visit to a high-end clothing retailer is a much stronger indicator of purchase intent.

With accurate location intelligence, you can effectively target and engage your customers at just the right time, in the right place and with the right message to drive results.

Read the original article here. 

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