Great question. Twitter provides a unique platform to engage in real-time with bite-sized information in an open forum; it has become the next-generation wire service. In terms of improving the platform, is there a specific challenge the company needs to address? (Profitability) Interesting, I’ll look at the revenue-side of the profitability equation as I’ve read cost optimizations are mid-cycle at the moment.
User Personas & Pains:
Casual User: Interested in casual consumption of latest news, updates, and ideas. Will participate monthly in a discussion of an activated importance monthly, but generally centralizing on the entities activeon the platform. Twitter may serve as a substitute to phone or email.
Pains -> Finding new content, no influence, confusion over platform value (Platform is rapid distribution, I’m casual).
Power User: Interested in a regular exchange of ideas and discussion. Enjoys recognition and engagement. Enjoys enabling the sharing process to shape a narrative and see what it grows into.
Pains -> Developing a brand without a viral loop, lack of feedback on tweets that are seen as noise, ability to participate in a more meaningful way to effect action.
Key Opinion Leader: Interested in developing brand awareness, influence, and coordinating action to achieve goals, either financial or social. Content creation and editorial skill development are more important to act as curators and acquiring new users. Acquisition is of primary importance.
Pains -> Managing brand risk, improve monetizing/ call to action requests, reaching new verticals of users unfamiliar with content.
Prioritizing Pain Points Revenue Growth:
The success/ failure of Key Opinion Leaders is the most tied into the Twitter platform. Managing success is easier than to create success for someone without success, especially in media (power user); think show ratings and the statistical shotgun approach of pilot episodes. Solving this problem does provide a solutions platform to scale to Power Users nucleate and grow.
There is a measurable value to a product that can target new consumer segments and reducing churn.
1). Peer review platform for content prior to release. The platform can be a focus group of Power Users that provide guidance with a set of metrics to show how well the message aligns with the psychology of the group profile and if it elevates dialog, neutral, or causes conflict. The process can be expedited with ML as we develop more and more user data. In effect this feature becomes an insurance policy to ensure brand is protected. This feature does slow-down the rapidness of distribution, but would be targeted at original content where speed is secondary. Insurance policies are typically valued at 1-3% of value and would be best deployed as a subscription model.
2). Paid access to the feeds of non-subscribers and targeting information for user values to shape content. In the current environment this should be strictly non-political or religious content, but rather offering a platform for Katy Perry or Barack Obama to write an original piece about the state of solar panels and have it seen by the technical community who may engage well with an outside opinion. The product could generate value from a low-cost subscription for the targeting tools and an additional cost for acquired user.
3). Live heat maps for word formation in the tweet to give insight about tone and context. In situations where time is everything, providing a real-time keystroke feedback to make sure tone is properly aligned with intent would add value to ensure messaging is on point. Scalable to include tweet like/ retweet predictions based on past tonal qualities. Most of communication is the author perception and tone so this would lend itself well to predictions. Similar to the insurance model this feature would be in line with an insurance policy at 1-3% of value and perhaps more if it can grow efficacy of message and not just defend.
I would recommend implementing live tweet tonal heat maps as a first product to test whether there is value in brand protection and possible user growth. The most value to Twitter lives in option 1 about peer reviewed original content, but it is a much larger undertaking before value is understood. The longer feedback loop also hurts viral adoption as the feature is less punchy, despite being more valuable. Option 2 is controversial in the current climate and has been rolled out previously. The unique angle is the develop of customized original content for audiences, but the feedback loop will require a lot of iteration.
In summary the best way to improve Twitter’s revenue in a scalable platform is to release tonal heat maps for key opinion leaders to protect their brand and ensure messaging is consistent and possibly increase user acquisition. The model could be rolled out as a monthly subscription with pricing based on AB test results surrouding statistic models of tonal related user churn and user acquisition.
I would measure success of the tonal heat map by measuring percentage user acquisition (new followers, retweets, and positive comments) and churn of users (unfollowing, negative comments) before and after model implementation.