CPU No. 3: AI for writers, bad reviews & the best TikTok metrics to track
Everything we've published on The Content Technologist in the past month
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This month in The Content Technologist
Here's a rundown of the essays we published for paid members in the past few weeks:
On iteration: Why digital business folks and content producers don’t always see eye-to-eye
by Deborah Carver
The goal of iteration, on the other hand, is to work from a minimum viable creative idea and test what will grow toward the intended result. While the goal of iterative design is to know half-baked ideas have potential — fast — the outcome in the real world is a sea of unfinished products and roughly hewn promotional content, much like the internet itself.
The iteration business exists in sharp contrast to traditional print media and video production; in industries more aligned with manufacturing than software engineering, iteration is difficult and not particularly profitable. Whether printing newspapers, records or books, tiny changes to content mean type must be reset, plates and colors re-calibrated. Once the book or magazine ships, its physical being is out there in the world, not to be changed until the next printing.
Video production is an even bigger mess when iterative methods are introduced. Anyone who's been on a video set knows that seemingly minor changes to staging can mean extra hours of work for the lighting crew. “We’ll fix it in post” causes eye rolls from veterans who see clearly how the whole thing could have been planned better. Sure, Hollywood can make changes during production, but that could mean hours or days of union time wasted and money burned… all because someone wanted to change a line.
Twentieth century manufacturing-driven cultural industries also value originality and exclusivity, whether that means publishing a juicy scoop in the evening news or releasing the only girl toy–themed summer blockbuster. Getting it right on the first try often means a more profitable product.
The people who think, “We should do the exact same thing as last time but with one minor tweak to better affect market performance” tend to underestimate the expense and intention of creative work. They don’t see that iterations can have a butterfly effect, that “just one small change” early on can affect an audience’s comprehension of a message or have some cascading ripple effect that causes errors down the line.
AI tools for professional writers: How to prompt, what to build, and what to avoid
by Natasha Serafimovska
Originality in language and ideation can help both search engines and human audiences categorize content as high quality. You don’t want AI to rehash the same ideas hundreds of other websites have already published on the topic.
When I asked the AI for tips on improving sales, its suggested topics were pretty mainstream. If I run the same prompt a few times, I can spot patterns and identify repeating topics. Using human expertise, I can deduce what’s missing from the list that could be a unique take.
Key takeaways:
Assume AI will generate the most mainstream ideas, then eliminate those from your writing.
Probe the tool for more unconventional suggestions.
Play with inputting tone of voice or industry knowledge to generate unusual answers.
How to mine good insights from negative feedback for content strategy
by David Gonzalez-Cameron
Want to know what buyers think of your products? The first place to look is in your product reviews. Not company reviews, which encompass your entire brand, but product reviews on individual SKUs (if you have them).
Tools like Yotpo and Google reviews enable ecommerce marketers to embed reviews on product description pages. Normally on a scale of 1–5, shoppers can leave feedback on their experiences.
Maybe it was a 5-star review and the experience was great. Or maybe it's a 1-star review and the person hated that product. Both reviews are useful.
Product reviews don't just apply to physical goods. They also apply to businesses that sell services, experiences, or paid content.
For example, a ski resort in Utah turned negative reviews into a positive ad campaign, owning their challenge and targeting a more advanced audience. Your niche product or content could do the same: Maybe your content isn't for beginners, and it's aimed at seasoned professionals. Lean into that. Focus your content on the intermediate and advanced practitioners.
Are you hitting the mark? Analyzing social media data for content success
by Emily Rochotte
A routine social media checkup identifies how your content is progressing. Ideally you’ll be checking weekly or at least every other week, but the prescription for health is never one-size fits all. For example, if you only post once a week, monthly would be best.
Checking too frequently may get you hung up on minutiae. Checking your analytics after each post is like Googling your symptoms when you feel a cold coming on. If you hyperfixate on one small symptom, you might think you’re sick with a deadly disease… when all you have is a headache.
Don’t let daily performance overwhelm you. Much like weighing yourself, results can fluctuate day-to-day. Most content businesses are more concerned with how long-term performance relates to business goals. Focusing on the analytics insights of today’s Reels won’t make or break social media results, but taking stock of Reels analytics month-over-month is a valuable snapshot of how your content affects your audience and your business.
Parrots are not stochastic and neither are you
by Arikia Millikan
I’ll be the first to admit that I am incredibly biased — toward parrots. I’ve always liked them and felt a connection to them ever since I saw them in my backyard as a toddler.
It’s disappointing that humans, as a species, spend so much energy and money hunting for intelligent life in outer space when we have a remarkable form of non-human life right here: a creature so intelligent it can use our own languages to communicate with us. All that effort put into interspecies communication, and the best we can manage to treat parrots is to capture and subjugate them.
Meanwhile, we destroy their habitats to clear the land that hosts the server farms, which in turn power the “intelligent” LLMs that ethics researchers attempt to denigrate when they call them “parrots.” It’s a good thing parrots can only speak human and not read it, lest they fully comprehend the tragic irony of their circumstances.
And yes, parrots do comprehend, like humans. They understand options and make choices based on that comprehension. Sometimes they change their minds mid-action. While the stochastic output of an LLM can seem like an entity deciding or exercising creative thought patterns, it’s just an algorithm running on a computer.
Paid content from the archives
Algorithms as interpreted by TV writers
by Deborah Carver
"The algorithm felt it wasn't hitting the right taste clusters," the network exec says.
Sally, stymied, argues that her Rotten Tomatoes metric proves it's worth everyone's time, that it barely had a chance to reach its core audience. After all, the network invested time and money into Sally's project. But in this case, the critical aggregator metric (Rotten Tomatoes) doesn't stand a chance against the predicted return on investment (the streaming network's proprietary black box of data).
The audience identifies with Sally's indignation at the algorithm's swift dismissal of her art. It's a familiar feeling for writers and creators, the algorithm that deems content unworthy of pursuing. I love the executive's language in her dismissal: "The algorithm felt," reflecting both how executives occasionally speak and the godlike deterministic power businesses can give to algorithms.
But Sally's attachment to her own KPI, also a black box of dubious merit, is equally unfortunate. I know Rotten Tomatoes holds some clout in the entertainment industry for measuring critical praise, but it's every bit as problematic and arbitrary as every other ranking algorithm. It's just a single point in the plot, and it's never the whole story.
The writing team on Barry most likely doesn't really understand algorithmic decision-making or the value of good stories, and they don't have to. But they're counting on the fact that the audience perceives algorithms as arbitrary and ruthlessly deterministic. In legacy creative industries, algorithms are the anti-art, the angry god, the unflinching paper-pusher.
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