February 2024 Issue

Dear Publishing Professional,

We're past the coldest month of the year, but it's too early to start looking for crocuses. Grab a warm beverage and settle down for a few minutes of publisher talk.

Should you encourage your editors to post their content on social media?

You've discovered that when your editors promote their content on social media, it dramatically improves your web traffic, or downloads of your podcast. You're considering asking (or even requiring) your editors to post their work on social media.

Is that a good idea?

No, it's not, unless you address a few problems.

Problem #1 – If you ask your editors to post your content on social media, you're tying your brand to their personal lives. That isn't fair to them or to you. You will inevitably face a situation where an employee has a controversial view. What are you going to do?

  1. Be a dictator and police what your employees do on social media.
  2. Have your content side by side with who knows what kind of crazy opinion.

Neither option is good.

Problem #2 – You're ignoring personality differences. If you gather 100 employees in a room and give them a talk about how much social media can help with this or that, 10 of them will be gung-ho and champing at the bit, 10 of them will want to quit, and the rest will be somewhere else on the continuum in between.

Some of your employees are introverts and some are extroverts, and no amount of motivational talks, training, incentives, threats, or anything else will change that. You're going to cause your introverts to look for another job.

Problem #3 – Some people will be better at it than others. You can train to a level of basic competency, but often there's a hidden whatsit that makes one person excel and another just get by. If you compare your editors on their social media results, you will create resentments. Is it worth it?

What then? If you're going to do this at all, consider these suggestions.

Suggestion #1 – Ask your employees to post brand-related content exclusively on LinkedIn and ask them to keep everything they post on LinkedIn professional. No personal opinions. That's the way people envision LinkedIn, and this solves problem 1.

Suggestion #2 – Have a company account on as many social media platforms as you like and appoint someone to manage those accounts. If other employees are eager to post content on social media – beyond LinkedIn – let them suggest a few things, try them out on your company account, and if they're good, give those employees access to that company account. That addresses problems 2 and 3.

Suggestion #3 – Be sensitive to different levels of talent, comfort, and general opinions on social media. Don't try to force everyone into a particular box.

My own attitude might shed some light on this.

Recall a time you've been at a conference or an event where some excited person gets up front and tries to rile up the crowd. "Are you excited out there?" and all that kind of stuff.

Some people enjoy that. I can't stand it. If you try to motivate me that way, it'll backfire. I might leave.

Not everybody wants to be on the cheerleading squad. Those other people – the grumps in the corner, like me – won't play your game, but they have other ways to help.

Don't try to clone your talented, gung-ho, extroverted social media stars. It's not going to work. Instead, find ways for other people to provide help and support to make your stars even more effective.

Deploy different talents and personalities appropriately. Don't try to force everyone into the same Myers Briggs category. (In fact, don't use Myers Briggs at all!)

These personality differences mean that you have to give people different options. Don't tell everyone "please post this on your LinkedIn account," because the person who wrote the copy is going to be the ra ra "get fired up" cheerleader, and the introverted editor is going to read it and think, "I'd rather die."

In sum, have a company social media account on lots of social media platforms. Ask your employees to post brand-related content on LinkedIn only, and leave them alone on other platforms. Accommodate different personalities and levels of talent.

Will the print-to-digital transition spell the end of print?

We are clearly experiencing a transition from print to digital. The question is whether it will be a complete or a partial transition. Let's look at some examples of earlier transitions and see what they tell us.

Complete or "mostly complete" transitions would include …

Partial transitions would include …

What distinguishes these two lists is that when the new tech is miles ahead of the old tech we get a complete or mostly complete transition.

When the new tech isn't a complete or exact replacement for the old tech, we get partial transitions.

For example, online shopping is fantastic, but some people enjoy being in the store, seeing the actual item, or even picking it up and handling it. The new technology can't completely replace the old technology.

Use this as a guide to determine whether print will continue in any given market. In cases where the digital version is not miles ahead of the printed version, print will remain.

The cool but scary future of e-newsletters

AI models can do a lot of the hard work for content creators.

Imagine I have a website with three main audiences: people who love swimming, running, and hiking.

Also imagine that I have a customer data platform so I can identify individual users and keep tabs on what content they like.

With a CDP I can put website visitors into audiences – e.g., swim fans, running fans, hiking fans. There might be some overlap between these groups, but that's fine.

Within each audience, I track what's popular and what's trending. But not only that. I can check to see if there's a difference in content preference between (1) the highly engaged visitor and (2) the drive bys and the casual readers.

At this point I might have six collections of content consisting of what the highly engaged fan is reading in each of my three audiences, and what the not-so-engaged fans are reading – or watching or listening. I could divide this further – between video and text content – but let's leave that aside for now and just focus on the content as content.

I'm going to pick the highly engaged swim fan as my example.

I grab the content viewed by highly engaged swim fans and pull out the keywords, tags, categories, and so on. I'm not going to restrict myself to the keywords and tags assigned by the editors. I'm going to use natural language processing to scan these articles and come up with another level of categorization that adds additional words to the mix.

Once I have a collection of all the keywords that are popular with my swim fans this week, AI can find similar words and concepts and start to build a pretty interesting model of what sorts of topics swim fans care about right now.

What's next?

How AI views a word or phrase

A word like "king" is represented in an AI system by a multidimensional vector. Something like [0.2, -0.4, 0.7, …] There might be hundreds of dimensions, and the values are assigned so that words with similar meanings are located close to one another in this multi-dimensional space. Words might be close along one axis and not on another. "King" and "queen" are close in the context of being a ruler, but they're not close in the context of sex, while "king" and "duke" are close in the context of sex, but a little farther apart in rank.

These sorts of vectors allow math, like king - man + woman = queen.

AI models don't understand anything. They just have a complicated mathematical representation of words and phrases that are derived from processing huge amounts of text.

I could just generate a report for the writers showing what types of concepts are playing well with the swim fans. The benefit of using AI here is that this report isn't just a matter of keywords, like "goggles," "freestyle" or "sample workouts." I can get sentiment analysis, like "fun, light-hearted articles are more popular," or "challenging articles are more popular." There's any number of factors I might want to consider. This is analytics on steroids.

My writers can use this analysis to come up with ideas for next week's articles.

Or I can take this all the way to the scary level and ask AI to write the articles based on the information I'm getting from my data. (With a human to review, of course!)

Realize what I've done here. I've come up with a technological way to listen to my audience, discern what interests them, and then give them more of what they want.

This method might have an inherent danger of getting into a spiral, where I go deeper and deeper into a narrower and narrower set of concepts. That's a possible consequence, so it might be good to build mechanisms to prompt people outside of their stated preferences – at least to some extent.

For example, Spotify might get the idea that I only like songs similar to the ones I've listened to. That's usually how recommendations work. But it's a good idea to toss in the outlier from time to time, or to do what Spotify does and say "people who liked this also liked …."

There you have it. A system along these lines could revolutionize content creation. My weekly e-newsletter could express exactly what my audience is interested in.

Sincerely,

Greg Krehbiel
240-687-1230

P.S. – Please let me know if there’s any way I can help you succeed, or if you know someone else who could benefit from my services.

The Krehbiel Group

"The Krehbiel Group" is usually just me, Greg Krehbiel. But from time to time I engage people to help. Here are some things I (we) can do for you.

But honestly, I've been in publishing my whole career. I can probably help with anything you need. Or I can point you in the right direction. Let's talk!