In the early days of publishing, advertising was sold based on ‘circulation’. There was no way to actually prove that just because a magazine had been shipped that it was actually even opened or just binned. Yet this concept persisted for many decades. Similarly, there was a time in sponsorship monitoring when simply identifying how many people viewed and attended a sports event was considered enough to estimate the ROI of a sports sponsorship investment. However, with multiple channels, fast-moving media and an abundance of brands visible at sports events, that’s no longer sufficient. Sponsors need more granular detail than viewing figures. At the very least they want to know how many times their brand was exposed versus others.
Furthermore, with sponsors often choosing various points and locations on clothing, vehicles, and stadia, to show their logo they wanted to know which placements performed best. And so placement measurement was born, and today measuring placements in sports sponsorship is crucial for gaining a better understanding of the value created by your sponsorship campaigns.
The reason an analysis of viewers and attendees of an event isn’t enough to understand the value of sponsorship is that, quite simply, not all placements are created equally.
Thinking about the layout of a pitch, tennis court or racetrack, it’s obvious why this is. First of all, the viewpoint of a spectator differs greatly from that of someone viewing on their television or on a device. Second of all, some areas of a sports arena are in view for longer periods of time, some advertising panels only show for set periods of time, some placements are smaller, some are bigger.
Much like an advertisement placement on a website or in a newspaper, size and frequency equate to value.
Advertising Value Equivalency or AVE is a basic metric used by PR and advertising agencies to measure the value of a placement. The formula is SIZE * RATE and it essentially gives you a general idea of how much the sum of all your screen time exposures was worth. It still has value in print media, but isn’t truly applicable in broadcast or streaming media sponsorship in sports.
The issue becomes very obvious when you look at the following example. Let’s say you paid $1 million dollars for some advertising panels at a Formula 1 event, taking up 10 feet of space in what is deemed to be prime sponsorship real estate. The value of that sponsorship comes to $10 million based on how often it appeared on screen during a broadcast and how many people would have been able to see the panel from their seats at the track. You also had an opportunity to sponsor ten inches of a race car’s wing mirror, however, you felt the hoarding placement was more valuable based on the size. It might transpire, though, that the wing mirror was shown more times than the stretch of hoarding that was sponsored as it had more time on camera during live broadcasts and during the highlights. Additionally, its physical size might be irrelevant given that it is seen in close up shots of the car, and so takes up more of the viewing frame than the advertising panel which is seen from a distance and so is smaller.
It’s therefore important to look beyond older measurement metrics such as AVE and take into account the various viewpoints and the frequency of placement appearances.
Monitoring placement is all about the frequency at which your brand appears and how many times your audience is actually seeing your brand, rather than how many people watched the event.
For spectators at home, this is a very different experience to those at the event. The broadcast event shows close up shots of cars, often in slow motion, and then, of course, there are the highlights.
Being able to analyse the frequency at which a sponsorship placement appears on screen is crucial in understanding the true value.
Now that the importance of understanding placements in sports sponsorship has been established, we can look at where computer vision comes in.
Visual-AI has the power to not only detect logos in images and videos but also account for placements of said logos. The key is to ensure that you are working with a computer vision provider that can process video content as video in full frame-rate, rather than convert a small number of frames every second into still jpg images for processing. This is important because processing video allows the computer vision system to retain the relationship of the placements across each frame, enabling highly accurate measurement of time on screen for each placement..
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At VISUA, we’re all about being hands-on when it comes to implementing and managing your sports sponsorship valuation solution. We’re available to discuss logo detection and placement detection for sports sponsorship monitoring and help you decide whether VISUA is indeed the right fit for your needs. Please fill in the form below and we’ll be in touch soon. In the meantime, why not try our computer vision wizard to see what solutions might work for you.
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