This essay originally was published on May 26, 2022, with the email subject line CT No. 123: Creating a better diet for the beast.
In January 2018 Facebook changed its algorithm to feature fewer branded posts in favor of more "meaningful" user-generated content. Many of my first-generation social content manager colleagues experienced a situation SEO folks knew well: dramatic performance drops in the face of an unannounced algorithm change.
We suspected then (and know now) that Facebook's prime directive was to keep people engaged on Facebook. Facebook didn't want users to leave the platform; it didn't want brands to reach customers without paying Facebook for the privilege; and it wanted to prove to its audience that the newsfeed wasn't becoming a living advertisement.*
One of my colleagues was stressing: the consumer brand whose Facebook channel she managed was seeing significant declines in reach and traffic. The brand's solution was to post seven times a day on Facebook to make up those numbers. Her entire professional life for the next few months was consumed by the tedious work of compiling seven original posts per day.
Of course her content performed well: she's a professional who knew her brand and had 40 hours a week to devote to creating social media content.
Like many other social media managers at media and brands, her job wasn't to critically evaluate where the audiences were coming from and whether her job was effective. Her job was to fill the queue with numbers that marketing managers could keep predicting, content burnout and algorithm changes be damned.
Other brands and media companies (legacy, digital-native, all) followed suit: instead of rethinking their social media strategies, they just posted more, usually so they could meet their pre-algo change numbers and prove that social media contributed to bottom-line business growth.
Interest in Facebook's algorithm was at an all-time high. Even though Facebook was actively rejecting organic branded content, brands just kept on posting to meet the old numbers. Social media agencies wanted to keep their contracts and prove their worth.
The machines kept learning that posts would continue appearing at an ever faster pace, that the accounts willing to be content factories would keep producing. Content marketers and publishers obliged. No one paid much attention to whether the content business was actually working efficiently, as long as the numbers remained predictable.
In the name of techno-optimism, being a "good fit" in a cultish company culture, the initial joy of being paid to create, and a desire to be taken seriously at work, social media managers blamed the algorithm instead of their bosses.
*The "meaningful" posts Zuckerberg sought in the 2018 change now seem laughable in retrospect. That algorithm change allowed shock, awe and misinformation to thrive.
More = better and the illusion of eyeballs
Until that algorithm change, social media was a return-on-content-investment paradise. Brands and media companies were raking in traffic and attention from social channels (not that they necessarily knew how to monetize it), and the novelty of easy publishing had everyone's eyes gleaming with dollar signs.
The prevailing 2010s digital content strategy for both SEO and social was quantity over quality, low-cost ads, low-cost content from eager, digitally savvy writers. The more often you post, the more algorithms see your content, the more people click, the more traffic you get, the more money you make. Executives at marketing conferences talked about "good content" like it was a spigot you could twist on as long as you hired an English major.
After all, newspapers and cable news spewed out tiny, unlinked stories for years, sweeping advertising dollars up on the premise that passive consumption from a large common denominator was the best way to make money at scale. Why wouldn't that exact model be replicated on digital channels?
Marketers and growth hackers studied Google's algorithm like it was a natural ecosystem instead of the product of an iterative business model. The "science" said bigger websites were better, more pages were better. Companies like Hubspot saw wild success from blogging marketing advice to attract searchers, selling software that replicated its blogging strategy with turnkey automations.
Even as Google became more sophisticated, enforcing guidelines on poor content (Panda) and using Natural Language Processing to evaluate good content (Hummingbird), many of the MBA persuasion persisted with the notion that more was better as long as content was cheap. Media success was an easy formula if you'd never run a media business before: More pages, more posts, more words, more images, wrung out of the same few people.
It was a perfect storm. Google and Facebook marketed their algorithms as magic instead of logic. Digital MBAs and growth hackers extrapolated that algorithms would perform predictively as long as they were "fed" content. Companies that were successful at more, faster content posited theirs was the only strategy to success. And since everyone creating digital content had been raised on a consistent stream of mediocre 20th century television, the notion persisted that a continuous stream of mediocre content equaled business success.
Breaking the content burnout cycle
The digital hype cycle continues today, perpetuated by Twitter investor types and writers who never leave the internet. Media brands and marketers alike have yet to get out of the habit of throwing dollars at "feeding the beast," chasing real-time trends instead of long-term business. It made sense for New York-based media companies who love the idea of real-time anything, being on-top of the world, being first, winning the market... for those of us in humbler climes, the ridiculous content hustle feels more than a little forced.
Myths like "feeding the algorithm" persist because they serve legacy media's old business models, which assume that passive audiences take whatever is built to entertain them. Selling daily papers, filling 24 hours with disconnected news and yelling heads, it's all the same thing. If executives blame the tool and not the business model, they can shift blame to "market forces" or "the duopoly" instead of their own unwillingness to adapt sustainable, audience-led practices.
When creators and myths who have succeeded in digital channels repeat these myths on Twitter or in their social circles, they contribute to the belief that the only way to survive is more chum.
But it's really not. The numbers show that consistent quality wins consistently, and that it's more sustainable when it's created by smaller teams at slower paces.
I've been looking at content performance analytics for nearly a decade, and I can safely advise: chum is the hardest, most expensive way to build a creative business or content marketing effort. Burning out by posting multiple times daily wastes everyone's time. Algorithms are not responsible for whether content is successful or not (although well-optimized content can be supported by algorithms).
Instead, here's what makes digital content successful in the 2020s:
- Experienced creators and collaborators with unique perspectives and ideas
- Proactive content strategies that account for potential algorithmic changes
- Consistent posting to meet the needs of an engaged audience
- An editorial approach that's tailored to the medium (structured, connected) and informed by audience needs
- Realistic expectations for long-term content performance (it's a long game, based on trust)
- A business plan that includes multiple revenue streams that aren't reliant on outside algorithms
- Harnessing the power of the behavioral patterns in your content analytics