The Future of Twitter is Data Analytics

There’s something to be said about unique companies that have a stellar product, who go IPO, and then suddenly find themselves having difficulty coping with their new public identity. While the ultimate benchmark of success is always going to be their ability to generate consistent revenues, what sometimes gets lost amidst shareholder demands, are the finer nuances of why consumers love the business, and the need to avoid falling into the trap of comparison. As the age-old saying goes, you can’t compare apples to oranges, just because they’re of the same ilk.

Much commentary over the departure of former Twitter CEO Dick Costolo has already been made. The #ThankYouDickC tributes in particular were an apt gesture in saying farewell to a man that transformed Twitter into the technology business it is today. Whether you agree with that or not, is of course your prerogative. But I wanted to write this post to focus on a different, yet related aspect of Twitter’s headline grabbing news: the case for sustainable growth.

I wish I had a more positive experience of working with Twitter’s advertising products as a Marketing buyer. For transparency, I’ll add the disclaimer that this was over a year ago, and the product is bound to have evolved for the better since then, perhaps rendering the points here moot. But it doesn’t change the fact that at the time, there wasn’t a whole lot of value derived. On any given day, angry Twitter users would lambast us for clogging their feed with irrelevant ads, which is not a great outcome, considering the ad campaigns are sold as a targeted communication mechanism. The reporting available was disappointingly high-level and practically anonymous, while I couldn’t quite justify paying for retweets and favourites (a practice that has since changed), when I knew that the key to real engagement was good content, useful information and timely dialogue.

Of course there are always soft benefits to such advertising like brand awareness that are worth mentioning, along with the argument in favor of piloting small marketing projects to see what sticks. But overall my lasting impression of the program was that the targeting criteria Marketers could leverage was limited, and the placement algorithm incredibly weak – a sacrilege considering the amount of rich, personalized data the Company has on user interests. With so many businesses prioritizing data modeling to analyze user behavior and context, you would expect Twitter to have the king of algorithms. And therein lies the problem, and the solution.

For years now, software companies in the business of social monitoring have created lucrative returns mining the data available from social media sites like Twitter. They help companies address a myriad of challenges related to measuring brand health, consumer sentiment, customer service success and overall user engagement, by offering in-depth reporting, analysis and a semantic view into the data. And while Twitter seems to have come to it’s senses to realize what a gold mine they’re sitting on (the GNIP acquisition, restricting ‘firehose’ data access et al), there’s a real urgency to take more radical steps towards regulating access and the governance of this proprietary data.

The revenue Twitter makes from syndicating data plays second fiddle to the star attraction: earnings from advertising. Admittedly, I’m not a fan of their advertising offering, although I still think there are more obvious avenues Twitter has yet to explore – the simplest example being to create an advertising program where companies can hire the wallpaper of subscribed users. Twitter could pay opted-in users a small commission fee in return for being able to rent out such real estate. Consumer brands are already doing this to a degree, working directly with users who have influential followers to plug their products in tweets and pictures. So long as it’s operated within the confines of a structured program, this could be a solution to offering a less intrusive advertising solution.

But by nature, Twitter’s advertising product is always going to have its limitations – and rightfully so, in order to protect the authenticity of the platform. The monetization of user data is where it’s at, a solution that would also go a long way to address the concerns of shareholders. While I appreciate there’s always a case for wanting user growth, Twitter could become an example where the emphasis is less on net-new user acquisition, but more on making better use of how to mine information from the 360 million users active on the platform today. Putting significant resources into creating semantic and semi-semantic views of the data, where outputs relating to trends, activity summaries, user relationships, behavioral interpretations and transactional reviews are easily summarized, would form the basis of a suite of business intelligence reports. Hiring best-in-class data scientists and programmers to build a killer reporting and analytics console with different monetization flavors based on the type and volume of data consumed, would be the logical conclusion.

Organizations have already figured out how to make good use of Twitter’s data to address customer service problems, as part of the social selling equation, to conduct focus groups through listening and monitoring conversations, and to research future trends by building their own data warehouses. There’s no risk to implementing the above – the platform has become too valuable a source of information for companies to give up caring about what users are saying. The most important relationship here i.e. the one with Twitter users themselves, can be maintained unaffected. By securing recurring revenues through a formula that’s much more systematic, the company will be able to re-focus their energies on continuing to deliver an authentic, worthy and engaging user experience.
Image credit: digitaltrends.com

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