Location Insight: Cinemas

Cinema Ticket

Location Insight: Cinemas

At Location Sciences, we access billions of precise location data points, which enables us to see the complete paths of many millions of consumers. This data lake then feeds into our location graph, which shows how consumers interact with places – whether it’s their home, where they shop or where they spend their leisure time. Our location graph can then help answer questions like ‘where do consumers go after they shop?’ or ‘are my loyal customers really loyal?’ for any business that has a physical presence. All of this is done in aggregate, securely and anonymously using the industry standard advertising IDs (equivalent of cookies for mobile).

In this blog, we’ll be sharing some of the insights we’ve drawn from this location graph, focusing on a specific sector. And with the Oscars award ceremony having recently taken place, where better to start than with cinemas?

In the UK, the cinema industry has undergone a lot of consolidation, and is now dominated by just three cinema chains – Cineworld, Odeon and Vue – which together account for around three-quarters of the market. We compared the London locations of these three chains, to see which had the highest footfall and the most loyal customers, and which days were busiest for each.

How do we know who is at a cinema?

When it comes to location, cinemas provide a particularly tricky challenge. Their opening hours vary greatly, they are generally situated in busy areas alongside multiple retailers, and people often spend time in a similar area before or after visiting the cinema. Let’s use the example of Surrey Quays Odeon, below, to show how Location Sciences turns millions of mobile phone location ‘pings’ into a definitive view of visitation.

Surrey Quays Footprint Map

  1. The cinema footprint is precisely mapped – visitors must be verified to spend between 30 minutes and 4 hours during opening hours only in this exact area<
  2. Nearby restaurants are excluded even if dwell time is similar
  3. Passing traffic (e.g. consumers travelling at higher speeds) are filtered out

As we derive our GPS location data from a Software Development Kit (SDK), integrated directly into apps within the phone, we can pull location at an accuracy far greater than bid-stream data alone, frequently down to one metre. We define the cinema in terms of its exact geographical footprint, so it doesn’t get confused with nearby restaurants – which, as you can see in the example above, are a common occurrence.

We can also access the speed and direction of the device – insight which is unavailable programmatically – meaning we can exclude consumers driving past in cars, or people walking through the car park. Finally, we take into account the cinema’s opening hours and location of its entrance and exit, in order to better differentiate a customer visit from non-customers – namely, members of staff. We then end up with a precise audience of verified cinema visitors:

Surrey Quays Heatmap

What did we learn?

This graph shows the daily footfall for the three main cinema chains’ locations within the M25, over the sample period of 23 September-21 October 2017 (days 1-30 on the x axis). On almost all of the days, all three brands are more or less on an even keel.

Here you can see those footfall figures mapped against one another. Note the regular peaks and troughs: in this sample, Sunday is consistently the quietest day for all three brands, with Vue suffering especially badly. Meanwhile, despite the rise of midweek offers, Friday and Saturday still prove to be the peak cinema days.

Frequency of Visits Chart

One of the unique abilities of the data set is the ability to look across competitor data sets and determine visit frequency. When it comes to repeat visits, Cineworld Luton was top of the pile, as the only cinema to be visited an average of twice. Vue Wood Green (1.97) and Odeon Streatham (1.96) weren’t far behind however, taking the second and third spots – suggesting that in this sample set no chain is beating the competition when it comes to customer loyalty.


The above just gives a taste of what our data set and capabilities can achieve. In the coming weeks, we’ll look at how we connect these visitors and visits back to the brand’s advertising campaigns – and in particular examples of how we can connect advertising campaigns to store visits, not just for digital and mobile ads, but for the conventional out of home advertising industry.

To find out more about the possibilities of location data insight, please get in touch.