With Disney and Netflix becoming the latest providers to succumb to the inevitable commercial realities of the subscription-only TV business model, it did set me thinking again about the amount of advertising consumers now have to endure and what this means for both customer experience and advertising effectiveness.
Disney+ has unveiled details of its ad-supported tier, planning four minutes of advertising per hour, roughly in line with competitor AVOD services, such as, Discovery, Peacock and HBO Max. We wait to see what Netflix will implement but many other providers (even Disney-owned Hulu) and commercial broadcasters already have ad-loads significantly in excess of this.
Empirical research suggests that most TV viewers would ideally prefer not to have any advertising, although will trade off the access to free, or low cost, content in return for consuming adverts, so long as they have some relevancy. However, we are in a media age where consumers are exposed to up to 1000 ads per day at multiple touchpoints: home, work, transport, and many more. Most of these adverts are untargeted or poorly targeted. At what point does this just make consumers tune-out or, worse, drop-out of subscriptions altogether?
A recent report from the Internet Advertising Bureau (IAB) spelt out bluntly the changes in consumer expectations of advertising. It found that consumers are tired of traditional advertising, especially when it manifests as interruption to digital video consumption. Lower consumer tolerance and higher expectations of brands are impacting the composition and size of audiences for ad-supported media and entertainment brands.
Whilst no silver bullet, one factor that would make a huge difference is to improve the relevancy of advertising to viewers through accurate targeting based on their observed interests. It is our habits that define us and viewing behaviour is a powerful means of identifying consumer affinities and intentions, particularly in a VOD, post-cookie world. Unlike online behavioural data, however, it remains a vastly under-utilised asset.
A big part of the problem is the complexity and cost of turning viewing data into audience attributes that advertisers want and that’s why I’m excited about the developments at Think Analytics. It is a solution that can rapidly produce a large set of accurate affinity attributes to standard IAB audience definitions from any TV operator’s first party viewing data set.
It means that TV operators and advertisers can use the power of audience TV behaviour to reach the right target audience at the right moment with the right message. Not only does this improve advertising spend effectiveness, but it should also go a long way to mitigate the potentially deadening effect of a blizzard of advertising messages on consumer satisfaction, engagement, and response.