WORKWEEK

There’s a lot of doom & gloom out there, but the quality of content AI should get you excited. 

Here’s what it can already do:

• Programmatic SEO
  • Product pages 
  • Definitions (For glossaries) 
  • FAQs 
• Repurposing of content for distro channels:
  • Social media 
  • One pager / white paper copy 
  • Email copy & nurture streams 
• Parts of the editorial process:
  • Research! 
  • General “how-tos” & listicles

Here’s what it can’t do all that well:

• Case studies
• Feature stories 
• How-tos with real brand walk-thrus

In other words, it can’t tell a unique story with a point of view that adds to the current conversation about that topic––and that’s exactly where you and your team should focus. 

The Media & Content Marketing Divide 

**Before we get into this section, I know this will seem like a tangent, but I promise, it’s relevant background for how to think about your role as a content marketer, and how to leverage AI to do that job even better. 

We’ve been on a long pendulum swing the last decade as media organizations lost steam. Many went under. Many lost trust. The rise of content marketing happened during this period (but rest assured, content marketing was alive and well even before). 

But it was in this period that brands like Shopify and Hubspot were able to build large inbound marketing efforts through content marketing–-acting as publishers in their own right. 

This has led many to say that brands should be the new media companies––and that content marketing should be run as a media organization. 

After all, media organizations use a variety of content types across articles, podcasts, videos, events and more to create a niche metaverse and community. 

Great content marketing should do that, too. But… 

• At media companies––content is the product. 
• At B2B companies, your product is the product––and it should be until the company is ready to invest heavily in content as a product (which may never happen). 

In fact, content folks have been laid off at organizations that have tried this (i.e. B2B orgs that invest in content as a “product” rather than conduit.) To me, when nearly all of Shopify’s content team was laid off in 2022, that was the real kicker in the “media company” model for B2B content marketing. 

Not even Shopify wanted to invest in content as a product, and that’s because content marketing is a tool to drive more folks to the actual product––whatever that is for your company. 

This is a big difference between media and content marketing. 

And as a result––I see media and content marketing taking two different paths over the next decade:

Media:

Will become creator-led, like WorkWeek and even like MorningBrew to an extent. 

When your content is the product, you can hire the thought leading influencers to be the names and faces of the media––and build cult-like followings around them. Those influencers will be paid well for this too, and organizations will build trust based on the “lineup” they can cultivate. 

This is a huge shift for media––but with the rise of AI, and the rise of the creator economy, great, thought-leading writers are building networks of their own, and media will need to tap into this and harness it to continue to grow their brands by association. 

Content Marketing: 

Will become reporting-led, similar to how media organizations used to work. 

That is, all content published will gather (i.e. interview) the experts and influencers the brand has access to to put together a unique and strong take on a current topic, leverage distribution across channels, and grow the brand’s perceived thought leadership through the expertise and influence of the community the brand has. 

Now, this isn’t to say that a media company can’t take the route of the content marketing org, or vice versa. A lot of folks will try a lot of tactics, but this bifurcation optimizes for the product being sold by each content organization:

• Media: The content is the product, which means the producer of the content (its origin) is the most important part of the content production process. People trust people more than brands, esp. with AI content rising––and media companies will need to harness the best of the best producers for their own brands. 
• Content marketing: The company’s product is the product, and content needs to help sell that product at a more and more efficient scale. To do that, the brand needs content assets throughout a funnel (not necessarily across types, though that can help)—and they need to optimize how that gets created. To do that, content must be optimized for all potential use cases at its creation. 

Those channels include, but are not limited to:

• Growth marketing (SEO, in particular, and potentially affiliate marketing)
• Social media marketing
• Paid media advertising
• Lifecycle marketing
• Partner marketing
• Customer marketing and retention 
• Sales enablement & sales, in general 

And, content likely needs to do this for a brand across a variety of segments. 

How does this impact content production processes?

Content marketing teams aren’t going to get much bigger––and will still be required to make the above happen. 

The best way to solve for this is interviewing well-known partners, customers, and influencers for any given piece at the top of the funnel, so that those interviews and quotes can be reused throughout the funnel for every possible use case––specifically where AI comes into play. 

This makes content scalable, since AI tools can take a finished product, and easily repurpose it for distribution across those teams and channels (and will get better at this). 

This also means content teams can focus on higher quality editorial top of the funnel that can be easily repurposed down the funnel (rather than spending so much of their time repurposing content across all those channels themselves). 

This changes existing production models… 

Anything that can be made programmatic––uses AI:

• Glossaries 
• Product pages 
• FAQs
• Chatbots
• Automated emails

**Copywriters/editors should edit these prior to them going live, for accuracy, brand voice, etc (Until AI gets even better at least). I don’t think these folks need to live on the content team. 

Anything that needs to be repurposed for a channel––uses AI:

• Social media marketing
• Paid media advertising
• Lifecycle marketing / Newsletter
• Partner marketing
• Customer marketing and retention 
• Sales enablement & sales, in general 

**The input for these assets needs to be a high-quality brand asset, since we know that AI can be generic, can be wrong!, and is better when you give it high-quality inputs to pull from. This is what you’ll use the humans to create. 

Same thing here, though, copywriters should edit these prior to them going live, for accuracy, brand voice, etc (Until AI gets even better at least). I don’t think these folks need to live on the content team. 

And finally, anything that needs to be created to feed AI––i.e. content marketing content like blogs, case studies, webinars, podcasts, etc.––goes through a human production process. 

It looks like this:

• Research: AI-enabled. This includes topic search, SEO research, persona research, etc,. 
• Interviews: Real interviews, not just surveys / questionnaires. Need interview expertise here from folks on how to follow the pain, test hypothesis, and not just lead interviewees to predetermined answers. 
• Transcripts, AI-generated––and then edited. 
• Writing & synthesizing: Synthesizing the information together to present a net new, compelling point of view on a specific topic. Likely no longer than 2,500 words, and quoting the experts themselves. 
• Approval: Approval of copy and all quote variations by the interviewees for use across the brand’s marketing channels. Send the article, as well as any variations from the transcript that the team may want to use as standalone (these will need to work out of context).
• Hand-off to channel partners for content repurposing: AI-enabled.
  • Social media marketing
  • Paid media advertising
  • Lifecycle marketing / Newsletter
  • Partner marketing
  • Customer marketing and retention 
  • Sales enablement & sales, in general 
• Content conversion optimization: Because content marketing needs to support a product in general, it should also drive lead gen. Prior to publishing, content will need some kind of lead gen asset added––either created by the repurposing segments––or using a related but older piece. These will be CTAs that collect lead gen information and include:
  • White papers
  • One-pagers
  • Webinars

If there is no other team to hand-off finalized content to for channel repurposing and distro, and that job falls on the content team (likely in smaller orgs), then content orgs should reduce the number of top of funnel assets they produce:

• Bigger orgs with supporting distro channels: ~8-12 blogs per month
• Smaller orgs with no supporting distro channels: ~2-4 blogs per month

Those supporting distro channels work a lot like new media companies like WorkWeek do––where a larger team supports the high-quality content of the creators, but in this case, the creator is the content marketing team. 

The rest of the org works to repurpose that content via AI for more trusted and on-brand results to speed up content repurposing and distribution to hit goals for their own channels. 

So far, my team is already experimenting with tools (ChatGPT and JasperAI) to test these theories, and are seeing pretty impressive results. The skills that will become important here are:

• Prompt-writing: The better your prompts for AI, the better the output. 
• Interviewing: To get the human element and add a new take to the larger conversation.
• Editing: Editing the AI! 
• Project management: As content becomes a more centralized hub of production, project management will become more and more critical for content leaders. 
• Go-to-market: Understanding how content needs to live in a variety of channels and repurposing content for those channels will be vital for content marketers at smaller orgs. At larger organizations, content teams will likely need to manage teams through project management tools for proper distribution, which will still require a high degree of go-to-market management and understanding. 

And that about sums up the office hours information I shared yesterday. What do y’all think? Are y’all testing this out? Do you have any questions about how to implement, or about AI in general? 

Would love to hear ‘em and see if I can get some thoughts back to you.