Friday, April 02, 2010
Social Strategies: Clarity
Recently, at my HBR blog, I discussed shifting from 20th century strategy to a new approach: social strategy. The simplest social strategy is clarity - and here's a killer example.
"Two researchers at HP Labs, Sitaram Asur and Bernardo Huberman, have discovered that you can actually use Twitter mentions to predict how well a movie will do in it's first couple weekends of release. What's more, the method works even better than the most accurate method currently in use, the Hollywood Stock Exchange (HSX)."
Twitter, in other words, offers media decision-makers more clarity about which movies are people are likely to value most. How? By unbundling conversations, letting people send and receive in real-time, more knowledge is aggregated faster.
It's a fascinating - and telling - example. Movie studios think of social media as another channel by which to market the same old lame blockbusters.
But clarity is a better strategy. Huberman and Asur's work suggests that a far more productive use of social media is learning how to make better movies in the first place. Now that's radical. Expand that across industries, and the future of strategy begins to come into stark relief.
I think the problem with this approach when applied specifically to a popular artform is that no one knows, and I posit will ever know, what is a "better" movie. If you're basing it purely on box-office, you aren't talking about better, you're talking about more commercially successful. The problem though with formulae predicted by what's commercially viable now is that the shelf-life is limited, and success may actually make it more limited-- the formula gets old faster. I don't see this as a path towards "better" movies, just an accelerated and perhaps more efficient version of Hollywood's current focus-group strategy.
Alex: the other opportunity is on the flip side in being able to monitor reactions post-purchase. How much value did the customer derive from consuming the product (movie), and how likely are they to say good things about it? This kind of insight is easily found through social media and likely isn't available elsewhere. So while you can predict box-office results, you can also measure consumers' reactions to those movies - which certainly could lead to 'better movies'.
Alex, I think there is absolutely value in this [particular flavor of] feedback from an artistic standpoint too...but totally see your point re: what is "objectively" "good".
One point from the research: the fact that there *is* a commercial transaction means that the feedback is more credible, because the people "voting" actually have some skin in the game.
FYI full paper is here if anyone else wants to check it out:
// Ethan Bauley // 3:35 AM
Good example but I think it mainly highlights that we have a faster feedback loop with social media (twitter being the fastest of the faster) than ever before. The 'being' able to predict seems simple statistics to me.
So to me, it's faster but not better. Unless you're able to qualify the source of the feedback, all you have is more or less what we can get today, just faster. I think it becomes really really valuable if you can also qualify the various and take that into account in the prediction. For example an 'adventure movie' may be rated very good by 'mommies' and bad by 'extreme sports adepts'....I see more value in the ability to segment the feedback and may be that what's behind 'make better movie' as you learn more about the many target audience that exists.
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