Thoughts On Second-Order Effects For Content Discovery in Voice
Second-order effects are rarely considered when new technologies come to the fore and reach critical mass. For example, the realisation of smartphones, the emergence of Apple's app store and the ubiquity of Wi-Fi and cheap, effective data in mature digital markets means a service such as WhatsApp makes more immediate sense, but Uber and Snapchat are less obvious.
Analogously, we are now within the early days of voice control’s commercialisation. Its most immediate starting point is as a centre-piece for the Internet Of Things (IOT) utilities, controlling thermostats, ovens and the like. However, when it comes to servicing entertainment, its impact is yet to be realised. Although we cannot know for sure at this stage, the confluence of emerging technologies the device finds itself within points towards several potential second-order effects. To ascertain these, here are a few first order effects:
· Immediate Mass Smartphone Penetration
· Searching for content through voice
· Easy access to considerable Data
· Emergence of Machine Learning
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Find out more…Another case of bait and switch:
Voice control limits search results. Google and Amazon when pushed for information offer pages of results; voice does not. At a push, it often will only serve around two results.
If we explore incentives from either side (the voice control operator and the content creator), two things happen. The voice control operator is in the position to charge the content creators to appear in these results should there be reasonable competition for placement. This creates a similar situation to that of Facebook, where companies and brands built audiences organically on the platform before they were then informed they would have to pay to reach consumers. Ceding such audience control to a single entity increases the likelihood of diversifying content across platforms. However, this will be problematic given the current propensity to engage in exclusive content deals.
Accelerating cultural bubbles:
This has implications for the creative and production side. By increasing the winner-takes-all effect in limiting the amount of content served (compared to search choices as well as mass retail of entertainment), we could see production lifespans for creative work hastened, in order to compete in such a small window. Data will likely be mined to diagnose which content is most often served through voice control and audiences subsequently micro-targeted.
Creators with name recognition will be even further empowered:
Musicians, Writers and Directors with established fan bases (think Vince Gilligan of Breaking Bad fame and Paul Thomas Anderson), by-pass this effect because they have a direct relationship with their audiences.
Through requests such as ‘Play another film with this actor, this writer, this director’. Name recognition in effect becomes a next-gen distribution system by which the creative talent becomes the key link between content. To capture this value, a potential second-order effect in this area is that creators may begin to seek contracts that give them revenue share based on the use of their name as a content discovery pivot. As again this will be indebted to the superstar effect (few creators have this name-recognition), we could see an even bigger power shift towards creators than when the studio system of contracted actors was ended in Hollywood during the late 1940s.
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