Huq is real-world consumer research database. By collecting anonymised location histories from an SDK (software development kit) in thousands of mobile apps, and marrying this insight with an advanced point-of-interest database (a.k.a. a really smart map that uses multiple sources), Huq makes it possible to measure consumers’ real-world likes, wants and interests in a digital, quantifiable form.
In short, by taking in the 10x millions everyday real-world actions of millions of consumers around the world, Huq enables OOH planners and advertisers to qualify purchase decisions based on their relationship with our specific OOH locations and where else they go.
Huq’s mobile panel stands out against other panels because of the quality of its data, and the unique insight that it gives us about audience’s relationships with the real world. It is a first-party dataset (rather than third-party, like ad exchange data for example) and it describes observed behaviours (rather than claimed behaviours, like an interview or diary panel would).
In South Africa, the Huq panel consists of over 250,000 unique users with a history of approximately 18 months collected via 1,138 different apps, and it is continually growing. For the Tractor DOOH network study, we observed 1,280 unique users who visited our network of locations. By mapping out our samples’ location histories and comparing against the Huq POI database, we are able to extract a wealth of insight about our screens’ audiences.
The below heat map shows the movements of each user that visited one of our digital screens over 18 months...
The first thing we wanted to understand was the average frequency of visits of our audience to our network. Huq’s database was able to demonstrate that our audience was visiting any combination of our network an average of 12 times per month (average monthly visits per user), with more than 90% staying on site for less than five minutes. This very much corroborates what the forecourt managers were telling us, and is what one would expect from locations that exist as convenience shopping hubs. When we look at visits of day of week and time of day, we see that the peak hours are throughout the working day, with a small spike over lunch.
This is all great for understanding the viewing occasion of our audience, but where the Huq data gets really interesting is in its ability to describe our audience’s relationships with other points of interests, i.e. where else do they go.
By analysing the specific locations (by brand or by category) that we were able to see our audience in, we can now show that 12.9% of our audience (or 43,246 people) are also McDonald’s visitors and 19.8% (66,378 people) are café category visitors. We have access to hundreds of brands and category variable scores, so can build out and define audiences according our clients campaign targets. This is really exciting because we are now able to tie OOH exposures and investments to actual opportunities to buy.
Tractor Outdoor has built up a network of over 100 digital out-of-home screens across South Africa and have streamlined their content management systems making it possible for advertisers to have a single point of entry for what is arguably the biggest DOOH network in the country. By making use of Huq’s audience metrics they are now able to develop a meaningful consumer journey which gives advertisers and clients a laser-guided ability to target exactly who they wish to influence.
In addition this, Tractor are also able to develop highly accurate cost-per-thousand (CPM) valuation metrics through the utilisation of the Huq data, which enables buyers and planners to do like for like comparisons with other campaigns that they may be running online, and in many instances they have found that advertising on the Tractor DOOH Network is in fact a far more cost effective way of reaching an audience than many other online/digital campaigns.
Conrad Poulson, CEO of Huq Industries, said, “We are thrilled to be working with Tractor and IRL Consulting in South Africa and it’s great to put our global geo-intelligence datasets to use in new markets. The insight they’ve obtained is truly compelling, and offers a view of what the future holds for precision audience planning and campaign activation in out-of-home.”
