Digital media disruptions XIX – video vs text, Twitter vs the Google – Facebook duopoly

SUMMARY:

In this edition – is video crushing text content? Are companies over-investing in Twitter for content marketing? And: what we can learn from Netflix’s recommendation algo.

dominos-fallingIt’s time for another media disruptions gut check – the enterprisey review. Rules: I pick the impactful stories from my media disruptions channel and give them a hard look from the enterprise side – along with a course of action. This series is NOT geared for the media industry, but for enterprises looking to win audiences.


Lead story – Is video pushing text aside?

Stories include Ken Rosenthal on Fox’s shift to video: ‘I was surprised that we went as far as we did’
by: Alex Putterman
key excerpt: “I am just an employee. I have my opinions about this. I don’t believe this is the answer, all video. I don’t even know that it will work. At the same time, Fox is not the only company that has struggled to figure out how to make money off the internet.”

A slew of news stories aired hyperbolic views on the pending demise of text and the mobile immediacy of video (assuming you have the broadband to stream it). A flurry of layoffs of experienced sports and entertainment writers – or a shift in their roles to video-only – have fueled the video discussion. (see my special feature, Digital media disruptions – learning from buyouts and blog reductions at the Times, WSJ, and MTV News).

enterprise relevance: medium. Most enterprise marketers are trying to figure out the role of video.

best course of action:

  • Video has a key role in the enterprise content mix. Videos for customer case studies and trade show testimonials are a good place to start.
  • Resist the temptation to produce videos with “viral” aspirations that aren’t tied to core brands or values.
  • Begin experimenting with live video productions and informal productions that have less marketing polish, but address meaty customer topics.
  • “Mash” video, audio and text productions and always feature key video excerpts as text for search relevance.
  • On the rise of video: Facebook’s Debuting A New Video Service So You Spend Even More Time In Its App.

Twitter’s stock plunges as user growth stalls
by: Joe Mullin

Despite the implied endorsement of Twitter by the President of the United States as his preferred way of, well, communicating, Twitter continues to struggle with monetization. Yet Twitter, with all its herd mentality and bluster, remains the best public social channel for sharing, particularly around hashtags (e.g. on-the-ground events). Facebook, Google, and LinkedIn have all solved monetization in a way Twitter can only dream of.

enterprise relevance: low to medium.

best course of action: Enterprises have potent reasonns for diversifying beyond Twitter:

  • For most B2B companies, far more decisions makers on are LinkedIn. For B2C, Facebook may be the better play.
  • Too many enterprises over-rely on Twitter sentiment analysis because the data is easier to access. But if your core audience or buyers aren’t on Twitter, you’re measuring the wrong things. Expand analytics into other networks – even if it takes work to get behind the log-in wall. Tie email and web analytics together as a contrast to social activity.
  • The best use of Twitter is for events. The next best use is for routing product and service feedback (good and bad) back to internal leads to act on (a use most companies are not good at. For some, Twitter customer service can be effective, if cases can be escalated and resolved without switching platforms.
  • Twitter isn’t going bankrupt, but it make sense to proceed as if it might be acquired someday, and morph into a new offering. Hedge social investments accordingly.

This is how Netflix’s top-secret recommendation system works
by
: Libby Plummer
key excerpt: “Netflix uses machine learning and algorithms to help break viewers’ preconceived notions and find shows that they might not have initially chosen. To do this, it looks at nuanced threads within the content, rather than relying on broad genres to make its predictions. This explains how, for example, one in eight people who watch one of Netflix’s Marvel shows are completely new to comic book-based stuff.”

enterprise relevance: medium, depending on level of investment in predictive/recommendation engines.

One of the better pieces on the company that has come as close as any to cracking the content recommendation nut: “More than 80 per cent of the TV shows people watch on Netflix are discovered through the platform’s recommendation system.”

best course of action:

  • There is plenty to learn from Netflix’s three-pronged content recipe. It’s not just sticky content. It’s intuitive UX, and algorithmic recommendations that go well beyond “show them every movie with Julia Roberts in it.”
  • True content personalization is still an elusive goal. Companies should begin the process of deciding which machine learning components they might build and which they might pull in via third parties or APIs.
  • It’s also worth studying how Amazon integrates recommendations, content (reviews/previews) and commerce. Unlike Netflix, most B2B players are trying to sell or upsell amidst content. As the lines blur between commerce and community, serving up the content that leads to progressive actions (engagement, sign up, purchase) matters.

Bonus content – a few more stories worth tracking:


These pieces were picked from my curated scoop.it channel, enterprise media disruptions. You can also view the entire digital media disruptions series, including special features.

Image credit - Problem Solving - Hand Stopping Domino Effect © Romolo Tavani - Fotolia.com

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