Does the Algorithm Tell the Whole Story About Your Content?

When it comes to content strategy, it’s easy to lean on algorithms to make decisions on content presentation—but algorithms aren’t perfect, and they can create content blind spots if you’re not careful.

Sometimes, the secret to making a piece of content more useful or appealing to your audience is all about the presentation.

And the failure to present it in the right context initially can cost you some momentum.

A saga in the world of streaming media has me thinking about this issue. Recently, Netflix announced it was canceling a show called Tuca & Bertie because of apparently low ratings—but that may seemingly stem from an algorithmic oversight on the part of the company. This is surprising because of the show’s critical success and pedigree—it was created by Lisa Hanawalt, the illustrator behind one of Netflix’s most popular animated shows, BoJack Horseman, and it starred high-profile actresses Tiffany Haddish and Ali Wong in the lead roles.

Predictably, after Netflix announced the cancellation, it generated a sizable backlash, with many accusing Netflix of failing to promote the show. At least anecdotally, it seemed like the show wasn’t promoted in its dashboard the same way most of the service’s other shows were. Even Hanawalt said the show wasn’t recommended to her—despite the fact that she created it.

It’s far from the first time the service has faced criticism for its cancellations, but it seems like the company took this one to heart. In response, a Netflix social media manager, Jarett Wieselman, asked Twitter users what a lack of promotion meant to them.

Did a busted recommendation algorithm kill a well-regarded show? That seems to be the implication. Hanawalt said the show drew very passionate fans, something that pure data points didn’t seem to catch. (Those fans are trying to save it.)

“None of this makes a difference to an algorithm, but it’s important to me and the way I want to continue making art in this world,” she tweeted.

The Blind Spot

In many ways, contextual weaknesses have always been a problem for television, long before Netflix was making its own shows.

One famous example: When Family Guy’s time slot kept moving, Fox felt it had a dud on its hands and canceled it—but when reruns drew massive ratings on cable, the network revived the show, which is now on its 18th season.

But the fact that a recommendation algorithm can play a significant role in content’s success feels like a modern twist on that age-old problem. It’s one that likely will be felt by a lot of organizations that are also struggling with their own “programming” of content.

There is a case that, beyond pure numbers, letting the algorithms run the show may create issues of coverage that no program would think to account for.

Basically, content is an investment with potential risks and rewards. But when it fails to make a big splash, the problem may not be the content itself, but the way it’s presented.

And when that content is largely put out into the world via an automated tool—such as a recommendation engine, an email marketing platform, or a social media scheduling tool—part of the problem may be an algorithmic blind spot. In a lot of ways, associations could run into the same problems as Netflix if the decision-making process is driven by data alone, no gut.

There is a case that, beyond pure numbers, letting the algorithms run the show may create issues of coverage that no program would think to account for. In recent years, for example, Facebook has faced lawsuits for its targeted job ads being discriminatory. In the case of Netflix, the problem is similar but more subtle: As The Daily Beast argued over the weekend regarding ‌Tuca & Bertie, Netflix appears to be giving shows created by women fewer chances to succeed.

While not a fail-safe, giving humans more say over certain automation-related decisions ensures that blind spots become less glaring. As more types of organizations, especially associations, use such tools, these kinds of problems are going to become more common.

Create New Contexts

So let’s say you’ve dug yourself into a hole where some of the content you’ve invested in isn’t being promoted properly or is a victim of a “blind spot.” What do you do?

I have a streaming world example for that, too. One of digital TV’s most interesting services these days eschews the algorithmic recommendation model in favor of something more traditionally linear. That service, called Pluto TV, is actually kind of brilliant: Basically, it takes cheap archival content—old movies or TV shows that haven’t appeared on cable in years—and puts them on their own themed channels. It works kind of like an alternate-universe version of cable for cord-cutters—like traditional corded cable TV for things that haven’t aired on cable in a good long while.

Like Unsolved Mysteries or old Nickelodeon cartoons? Good, because there are dedicated channels for each. It uses algorithms, too, but those algorithms seem to be used mostly to figure out where to put the ads, because the service is free. You don’t even have to log in if you don’t want to. (And if you want to pick the show you watch, an on-demand option is also available in the service.)

The potential of the platform was clearly obvious, because Viacom—a company with a lot of traditional cable channels—quickly scooped it up earlier this year. Last week, it announced that it was creating dedicated MTV channels for music videos, a famous example of something the Viacom-owned MTV dropped in favor of more traditional ratings-friendly programming.

Maybe your content doesn’t lend itself to that approach specifically, but the thinking here is clear. Perhaps if something isn’t succeeding, the problem isn’t the content, but the way it’s being presented. Maybe it shouldn’t be an article, but a webinar. Maybe it’s getting buried in the inbox but plays better in search.

If your content strategy is creating gaps, don’t just rethink the content. Rethink the context.

Was the Netflix show “Tuca & Bertie” a victim of an algorithmic “blind spot”? (via Netflix)

Ernie Smith

By Ernie Smith

Ernie Smith is a former senior editor for Associations Now. MORE

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