Combining POI and store data with OOH placements and traffic patterns gives us a basic idea of where we should be looking to buy, but it's when we overlay intent data from our proprietary microapp NearMe that things get interesting. This layer highlights where people have been searching for a specific product and provides us with intent zones.
A second intent layer comes via our direct integrations with the country’s biggest mobile publishers (Arena, eNCA, News24 and so on). We process 500 million location data points every month, which show us where and when people are in stores (as well as at other POIs) – a powerful in market or affinity signal.
We have the same location technology tagged onto the websites of our clients allowing for geospatial analysis. This helps determine where a client's audience is for planning, and indicates if the client's site saw a lift in traffic post campaign, specifically in the areas around the selected sites – a real game changer in OOH measurement.
We further utilise footfall data to provide brand overlap insight which opens up a new view on consumer behaviour during the strategy phase. For example, the data may show that for a fast-food restaurant, their audience overlaps with certain competitors, fashion retailers, liquor stores, and cell phone stores. This allows you to understand your consumers, and build out a targeting strategy that uses, for example, geo-conquesting (target messaging around competitor stores) or focusing around certain overlapping POIs that your audience visits.
Below is an example of employing both proximity analysis to identify nearby DOOH panels and overlaying NearMe search data for a pharmacy retailer, based on the retailers following brief:
Data isn't just for planning and measurement – data can greatly enhance the actual execution of your campaign.
Dynamic distance allows you to inform your consumer with the distance to store, store name, drive time, or address.
Geo conquesting as mentioned uses location data to identify a brand's competitors in an effort to promote a competing or competitive offering to their customers. This example uses both as we selected a site close to where the competitor’s store is… and published how close the audience actually was to the client’s store.
Other examples of using 1st party data in execution include:
Our audience data is what makes Vicinity Media stand out in the market. We pride ourselves on the quality of our audience data (with a very healthy dose of quantity).
We are bringing true measurement to DOOH through a four-pronged measurement suite:
For a leading premium beer brand, we ran a campaign to push event ticket sales on a ticketing website. The website runs our location technology, allowing us to track the user journey both digitally and geospatially on this booking site. This means we could provide the client with both conversion data as well as geospatial data on where the interactions happened, thus measuring the efficacy of respective DOOH placements.
An automotive brand ran a mobile campaign in July. At the end of July we activated the DOOH portion of the campaign. This is where things got interesting...
Due to a late start, the campaign had to play catch-up, and for the next few days DOOH impressions were at a high point.
The visit data tells the story of the increased activity with a big lift in store visits being tracked, as can be seen from the graph below.
This wasn't the only area that showed a lift. The client runs our location tag on their website, as can be seen from the below graph there was a powerful lift in web traffic.
As I mentioned above, we track up to four sources to bring measurement to DOOH, the final area we saw activity was in searches.
Simple. Not all data is created equal. Verify your data sources where possible and stress test them against your campaign performance. In addition, always ensure they are fit for market and fit for purpose.
Seek to develop inventory that fulfills brands requirements in reaching very specific audiences and that importantly drive performance. With measurement now available in DOOH, certain sites may prove to be less effective than originally suspected whilst others may prove to be more so.
Clutter and over concentration in certain areas could damage performance across the board and devalue some sites if media owners are not cautious with digital roll outs.
Don’t do anything in isolation. Take an omnichannel view and use the best data to plan, execute and measure.