Twitter. It's Where Data and Advanced Analytics Innovation Is Happening

Sometimes even digital natives need to rethink their data strategies

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Few have mastered data monetization like the social media giants such as Facebook and Youtube. Unlike traditional subscription based business models, with social media, the product is the user. So instead of you paying to access the platform, advertisers pay to gain access to you and your behavioral data. 

While Twitter is one of the most well-known and talked about platforms, with roughly 335 million monthly active users (MAUs), it’s far from the largest. For example, Facebook has over 2 billion MAUs not including its META counterparts Instagram and Whatsapp. 

In addition, as user growth has plateaued in recent years, some researchers believe that Twitter has reached its natural growth limit. In an industry where investors have come to expect impressive MAU growth numbers year after year, this is likely a very big problem. In addition, recent upgrades to the Mac iOS have made it more difficult for advertisers to track users. In fact, once given the option to do so, an estimated  96% of U.S. based users chose to opt out of tracking. 

Despite these challenges, Twitter has continued to thrive. In Q3 of 2021 alone, its earnings grew 37% year-over-year to $1.28 billion, ad revenue increased 41% YOY, and its average monetizable daily active users (mDAU) reach 211 million, up 13% YOY. The secret to its success? New and improved data analytics strategies. While they can’t compete when it comes to sheer number of users, they can use data to build better products and services. 

 

Personalization 

Like all established social media platforms, Twitter uses artificial intelligence (AI), machine learning (ML) and other advanced algorithms to connect users with relevant content/experiences and advertisers with targeted customers. 

However, by its own admission, Twitter has been a little behind the curve here. During a recent earnings call, Twitter CEO Jack Dorsey acquiesced, “We have so much more work to do in terms of machine learning and just generally applying AI to every surface area we have.

So we're going to put a premium on finding all the right signals to make sure that you're not just seeing more relevant ads, but you're seeing more relevant tweets as well. These are very similar systems, so I don't think it's all that far off and that we can start using more and more of these signals to increase the relevance of what we show. But this is the greatest opportunity for us in terms of relevance. And that drives everything from growth in usage, but also to our advertising segments.”

In line with those sentiments, on November 9, 2021, the company launched its new subscription service, Twitter Blue, that includes a number of new AI-powered personalization features aimed at boosting engagement and differentiating it from other ad-based competitors. For example, one of the new features is Nuzzel: a news curation tool that shows what people what their connections are reading. 

In addition, True Blue subscribers will also gain early access to new features before they hit the rest of the platform through Twitter Labs. Not only is this an added perk for users, but it also gives Twitter a chance to test out and refine products before they gain wide release. 

 

e-Commerce and Performance Advertising Business

In order to meet its goals of doubling annual revenue by 2023, Twitter will need to dramatically increase its ad-based revenue. In addition to enhancing its in-app purchasing capabilities, Twitter is also adding new data-driven tools to help sellers more effectively identify who is most likely to buy their product and optimize their existing performance advertising algorithm. 

As a result of the new and improved, Twitter saw a 36% increase in ad campaigns that achieved at least five downloads, according to a recent Reuters’ article. 

 

Responsible AI and ML

The recent scandals and outrage over the societal impact of social media has made “algorithm” a household word. There’s no doubt about it, Twitter has made a lot of mistakes in the area.

A recent internal study found that, for unknown reasons, its algorithm amplifies right-wing media. In addition, last year, academic researchers found that Twitter’s AI-powered image cropping tool was good at recognizing the faces of young, slim, white people, but basically ignored everyone else. In addition to automatically cropping out people of color, it also excluded people wearing headscarves, sitting in wheelchairs and who had grey/white hair. 

In order to combat these and other issues, Twitter launched its Responsible Machine Learning Initiative back in August of 2021. Run by an interdisciplinary team (the include both tech evangelists and skeptics), the initiative is built around 4 pillars:

  • Taking responsibility for our algorithmic decisions
  • Equity and fairness of outcomes
  • Transparency about our decisions and how we arrived at them
  • Enabling agency and algorithmic choice

Though the initiative is still in its infancy, Rumman Chowdhury, Twitter’s Director of META (ML Ethics, Transparency, and Accountability), recently shed some light on a couple of the projects they’re working on in a recent interview with The Morning Brew. One of which are worksheets and checklists to help AI developers more effectively identify and address incidents of AI bias along with other potential ethical issues. 

As she explained, “One of [the worksheets] is probably considered to be kind of boring, but it's my favorite thing to work on: standards development and risk assessments. We're already starting to see speculation and regulators talking about assessments and audits. So one thing I'm building is a risk assessment methodology. Right now I'm literally in the process of figuring out the best way to assess our models for risk—we're interviewing model owners and starting to dig into our catalog of models.

Another worksheet we have is on algorithmic choice and, more broadly, user agency. I have long said, even before I came to Twitter, that everybody talks about human-in-the-loop, but nobody has really solved what it means. As you pointed out very correctly, even people who aren’t on Twitter are impacted by it. So what does it mean to give people choice and agency over their experience with Twitter and how Twitter impacts them? That's pretty broad; it’s even something Jack has talked about to Congress. So we’re working on understanding how users understand agency and choice from the ground up.”

 

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