Copying on Purpose

Threads’ user base seems to be an object of fascination among the tech press. Mark Zuckerberg says it is “on the trajectory I expect to build a vibrant long term app” with “10s of millions” of users returning daily. Meanwhile, third-party estimators have spent the weeks since Threads’ debut breaking the news that its returning user base is smaller than its total base, and that people are somewhat less interested in it than when it launched, neither of which is surprising or catastrophic.1 Meanwhile, Elon Musk says Twitter is more popular than ever but, then again, he does say a lot of things that are not true.

All that merits discussion, I suppose, but I am more interested in the purpose of Threads. It is obviously a copy of Twitter at its core, but so what? Twitter is the progenitor of a genre of product, derived from instant messenger status messages and built into something entirely different. Everything is a copy, a derivative, a remix. It was not so long ago that many people were equating a person’s ban from mainstream social media platforms with suppression and censorship. That is plenty ridiculous on its face, but it does mean we should support more platforms because it does not make sense for there to be just one Twitter-like service or one YouTube-like video host.

So why is Threads, anyway? How does Meta’s duplication of Twitter — and, indeed, its frequent replication of other features and apps — fit into the company’s overall strategy? What is its strategy? Meta introduced Threads by saying it is “a new, separate space for real-time updates and public conversations”, which “take[s] what Instagram does best and expand[s] that to text”. Meta’s mission is to “[give] people the power to build community and bring the world closer together”. It is a “privacy-focused” set of social media platforms. It is “making significant investments” in its definition of a metaverse which “will unlock monetization opportunities for businesses, developers, and creators”. It is doing a bunch of stuff with generative artificial intelligence.

But what it sells are advertisements. It currently makes a range of products which serve both as venues for those ads, and as activity collection streams for targeting information. This leaves it susceptible to risks on many fronts, including privacy and platform changes, which at least partly explains why it is slowly moving toward its own immersive computing platform.

Ad-supported does not equate to bad. Print and broadcast media have been ad-supported for decades and they are similarly incentivized to increase and retain their audience. But, in their case, they are producing or at least deliberately selecting media of a particular type — stories in a newspaper, songs on a radio station, shows on TV — and in a particular style. Meta’s products resemble that sort of arrangement, but do not strictly mimic it. Its current business model rewards maximizing user engagement and data collection. But, given the digital space, there is little prescription for format. Instagram’s image posts can be text-based; users can write an essay on Facebook; a Threads post can contain nothing more than a set of images.

So Meta has a bunch of things going for it:

  • a business model that incentivizes creating usage and behavioural data at scale,

  • a budget to experiment, and

  • an existing massive user base to drive adoption.

All this explains why Meta is so happy to keep duplicating stuff popularized elsewhere. It cloned Snapchat’s Stories format in Instagram to great success, so it tried cloning Snapchat in its entirety more than once, both of which flopped. After Vine popularized short videos, Facebook launched Riff. After Twitter dumbly let Vine wither and die, and its place was taken by and then TikTok, Facebook launched Lasso, which failed, then Reels and copied its recommendation-heavy feed, moves which — with some help — have been successful. Before BeReal began to tank, it was copied by, uh, TikTok, but Meta was working on its own version, too.

But does any of this suggest to you an ultimate end goal or reason for being? To me, this just looks like Meta is throwing stuff at people in the hope any of it sticks enough for them to open the advertising spigot. In the same way a Zara store is just full of stuff, much of it ripping off the work of others, Meta’s product line does not point to a goal any more specific than its mission statement of “bring[ing] the world closer”. That is meaningless! The same corporate goal could be used by a food importer or a construction firm.

None of this is to say Meta is valueless as a company; clearly it is not. But it makes decisions that look scatterbrained as it fends off possible competitors while trying to build its immersive computing vision. But that might be far enough away that it is sapping any here-and-now vision the company might have. Even if the ideas are copies — and, again, I do not see that as an inherent weakness — I can only think of one truly unique, Meta-specific, and successful take: Threads itself. It feels like a text-only Instagram app, not a mere Twitter clone, and it is more Meta-like for it. That probably explains why I use it infrequently, and why it seems to have been greeted with so much attention. Even so, I do not really understand where it fits into the puzzle of the Meta business as a whole. Is it always going to be a standalone app? Is it a large language model instruction farm? Is it just something the company is playing around with and seeing where it goes, along the lines of its other experimental products? That seems at odds with its self-described “year of efficiency”.

I wish I saw in Meta a more deliberate set of products. Not because I am a shareholder — I am not — but because I think it would be a more interesting business to follow. I wish I had a clearer sense of what makes a Meta product or service.

  1. Then there is the matter of how Sensor Tower and SimilarWeb measure app usage given how restricted their visibility is on Android and, especially, iOS. Sensor Tower runs an ad blocking VPN which it uses in a way not dissimilar from how Meta used Onavo, and several screen time monitoring products, which is something that was not disclosed in an analysis the company did with the New York Times.

    SimilarWeb has a fancy graphic illustrating its data acquisition and delivery process, which it breaks down into collection, synthesis, modelling, and digital intelligence. Is it accurate? Since neither Apple nor Google reports the kind of data SimilarWeb purports to know about apps, it is very difficult to know. But, as its name suggests, its primary business is in web-based tracking, so it is at least possible to compare its data against others’. It says the five most popular questions asked to Google so far this year are “what”, “what to watch”, “how to delete instagram account”, “how to tie a tie”, and “how to screenshot on windows”. PageTraffic says the five most-Googled questions are “what to watch”, “where’s my refund”, “how you like that”, “what is my IP address”, and “how many ounces in a cup”, and Semrush says the top five are “where is my refund”, “how many ounces in a cup”, “how to calculate bmi”, “is rihanna pregnant”, and “how late is the closest grocery store open”. All three use different data sources but are comparable data sets — that is, all from Google, all worldwide, and all from 2023. They also estimate wildly differing search volumes: SimilarWeb’s estimate of the world’s most popular question query, “what”, is searched about 2,015,720 times per month, while Semrush says “where is my refund” is searched 15,500,000 times per month. That is not even close.

    But who knows? Maybe the estimates from these marketing companies really can be extrapolated to determine real-world app usage. Colour me skeptical, though: if there is such wide disagreement in search analysis — a field which uses relatively open and widely accessible data — then what chance do they have of accurately assessing closed software platforms? ↥︎