INBOX INSIGHTS, July 26, 2023: Agency AI Readiness, AI Podcast Guests

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How to Get Your Agency Ready for AI

A few weeks ago I got to sit down and talk with my good friend, Brooke Sellas for her podcast, “The Marketing Agency Show”. In case you missed it, you can watch the episode here:

In the episode, we talked about how to get your agency ready for AI. This is the burning question everyone has right now, isn’t it? That, and, “What tool should I use?”

What I told Brooke is that starting with AI, starting with the platform is the wrong way to approach it. You need to start at the top with your purpose – the question you want to answer.

Oh snap – it’s a 5P post.

Yes, it IS a 5P post. Because if you’ve been reading this newsletter for a while, you know that the 5P framework is incredibly versatile. You can even assess your AI readiness.

Ok, let’s go!

As a refresher, the 5Ps are Purpose, People, Process, Platform, and Performance.

When Brooke and I talked, I highlighted the fact that where a lot of us go wrong is that we choose the platform first. Then we try to retrofit the technology into our existing processes and ask too much of our people. We’ve lost sight of the purpose and have shaky performance metrics.

So let’s fix that, shall we?


Better known as, “What is the problem you’re trying to solve?” Let’s be clear about this. You’re not asking, “What is the problem I am trying to solve with AI?” No. If you ask that question, you’re getting it wrong. Take AI out of the Purpose. It starts you off on the wrong foot and assumes that AI is the answer. It might not be.

As you define your purpose, you should use user stories. A user story is a simple statement with three parts:

As a [persona], I [want to], so [that].

Here’s an example: As a CMO, I want to use AI, so that our company stays relevant.

That’s a terrible user story because it doesn’t state a clear problem. Staying relevant isn’t a measurable outcome and it will vary depending on who you ask. What is relevant? If this is the problem you’re trying to solve, you need to dig deeper.

Let’s try again: As a CMO, I want to scale up my content marketing team, so that we can reach a wider audience with more helpful content.

We can work with this. The CMO is the stakeholder. Scaling the content marketing team is the process and platform we’re picking apart. Reaching a wider audience is the purpose and what we’re looking at for performance. Notice that we haven’t talked about AI yet. The assumption might be that a tool like ChatGTP to create more content is the solution, but we don’t know that yet. Let’s keep going.

People and Process

The problem you’re solving is that the CMO wants to scale up the content marketing team. Truthfully, that’s still a little vague. To get more specific, we want to evaluate people and process together. We need to get a better understanding of where the process isn’t working for the content marketing team. Additionally, where are the optimization opportunities? Start with having a conversation with your content marketing team and asking them what they need, instead of assuming that AI will solve their problems. The problem might be communication from the stakeholders about the purpose of the content or who the audience is. These are not problems in the process that AI can solve. This is a communication breakdown that you solve with a stronger content brief and better expectation setting. Interesting, but still no mention of AI.


As we start to understand more about how the content marketing team could scale, we want to look at the platforms you’re using. How are you doing your customer research, your keyword and topic research, and your content dissemination? This might be where you can incorporate AI into your content marketing team. However, as we’re digging into the purpose, people, and process we’re not seeing a strong case for bringing in AI yet. You could use a platform like ChatGPT to assist with editing the content, but that hasn’t presented itself as the core purpose. If you feel strongly about using AI, set up some A/B tests to get a better understanding of the value of AI in your process. Is it making your content stronger? Is it shaving time off the overall process? Are the people feeling supported or are they even more frustrated by having to use AI? If you’re starting down this road, I would restate the purpose.

As a CMO, I want to do A/B testing with AI tools, so that I can see if it makes my content marketing process more efficient.

By restating the purpose, you’ll have different perspectives on people, process, and performance. You’re measuring the effectiveness of AI, versus the reach of your content.


This is the other P that companies get wrong when they are trying to figure out where AI fits into their company. If we look at the other 4 Ps we’ve evaluated, we want to measure the reach of our content. How does that translate into metrics? You need to define what “reach” means for your company. Does reach mean more followers on social? More newsletter subscribers? More traffic to your website? Those are your performance metrics.

Otherwise, you might not be clear on your original purpose. In that case, go back to the top and revise your user story to be more specific.

As we’re wrapping up this particular example, I want to point out that AI was not the solution. That doesn’t mean that AI shouldn’t be used in your business. The point here is that if you’re starting with AI as the solution but you aren’t clear on the problem you’re not going to have a lot of success. Going through the 5P framework can save you a lot of money and headaches. You’ll have your blueprint for how to move forward and a built-in measurement plan.

Lastly, I have big news! I’ll be talking about this in more depth at Social Media Marketing World in San Diego next February – see you there?

How are you evaluating your AI needs? Reply to this email to tell me about it, or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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Binge Watch and Listen

In this week’s In-Ear Insights, Katie and Chris answer the question: is ChatGPT getting dumber? They discuss the recent changes in ChatGPT’s capabilities, examining if it is getting dumber and less accurate over time. We look at the implications for businesses relying on AI tools and considerations when implementing them.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we talked through how we use AI to dramatically accelerate content creation and production. Catch the episode replay here!

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, in celebration both of the ubiquity of the Barbie movie and the endless torrent of news about artificial intelligence, we wanted to bring those two threads together. There are, as one might imagine, a number of podcasts talking about AI right now. We wanted to see – of the episodes (not shows, but episodes, whether or not a podcast is principally about AI or not) that have substantially covered AI, what sort of gender diversity might we see?

Let’s take a look. Using tools like Talkwalker and AHREFS, we identified podcast episodes that had both a host and a guest so far in 2023. That was about 30,000 episodes. From there, we analyzed how many were principally about AI, where AI was the key subject matter, which was 3,074 episodes or about 10%.

Using OpenAI’s GPT-3.5-Turbo API, we inferred the gender of both the host and guest to perform the analysis. What did we end up with?

Podcast Hosts

Of podcast episodes about AI, 32% were female-hosted and 67.8% were male-hosted.

Next, we examined the guests:

Podcast Guests

Of podcast episodes about AI, 36.4% had female guests, while 63.6% had male guests.

Now, we know without question that there’s bias within the AI field; the field tends to skew very strongly male. However, in podcasts, hosts have the choice of who to invite to speak about AI. We did not de-duplicate guests, meaning that Guest A could appear on podcasts X, Y, and Z and be counted 3 times because Guest A made three distinct appearances. Ideally, we would see a pattern where regardless of the gender of the host, the guests would be roughly evenly distributed.

Here’s what we found:

Podcast guests by gender host

Female podcast hosts tended to invite male guests approximately 31% of the time, and female guests approximately 69% of the time.

Male podcast hosts skewed even more unevenly; male hosts invited male guests 79.3% of the time and female guests 20.7% of the time.

How do we fix this so we achieve more parity? Certainly, female hosts shouldn’t need any assistance finding male hosts, so we can skip that part. For male hosts, we strongly encourage them to look out at the AI field to find the female thought leaders in the space. Here’s a list of 100 from Re-Work’s blog. Reach out to any of these folks to start booking interviews.

And hey, if you just want to make it easy on yourself, bring Katie onto your show!

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