INBOX INSIGHTS, March 6, 2024: Ideal Customer Profiles, GA4 Generative AI

INBOX INSIGHTS: Ideal Customer Profiles, GA4 Generative AI (3/6) :: View in browser

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Using Generative AI to Build Your Ideal Customer Profile (ICP)

My brain is buzzing and my head is spinning.

Chris and I have been using Generative AI for the past two hours to build our Ideal Customer Profile (ICP). Why? Often we get asked, “Who is your ideal customer?” I realized that we always give a weak, vague answer. So, it was time to do better.

We have a large amount of data. This should come as no shock to anyone, given who we are and what we do for customers. The challenge has always been figuring out how to make sense of this data in an actionable way. Ironic, given what we do for our customers. But, our company is always the last priority. Something like “the cobblers kids have no shoes.” Anyway, we finally set aside the time and went through the exercise.

What did we do? First, we create a user story. I was floundering around with too many places to start and needed to focus my attention. Chris asked for user story for this exercise.

This was first user story. Like me, it’s a bit of a mess:

“As a CEO I need a better handle on the characteristics of our ideal customer. so that I know who we’re looking for on LinkedIn and who we’re trying to reach with our content. So we can speak to that person.”

I went ahead and refined it to be more focused. This was the second draft that we worked off of:

“As the CEO, I need to better understand the data points of my ICP, so that I can create tailored content and services for them”

It’s still a complex user story, but it hits all the marks. If we break it out into the 5P Framework, this is the data we know:

Purpose: To understand our ICP. To create tailored content and services for our ICPs. Who is most likely to benefit from our services?

People: Me. This is where we should have created more user stories. I’m not the only one who will be executing the eventual plan. However, since we’re a small company, I prioritize and delegate the action items.

Process: What I stated was “better understand” and “who we’re looking for”. This tells me that we need to create the ICP in such a way that the characteristics create a search query

Platform: I listed LinkedIn. You don’t list your platforms in your user story. What you get is your instructions for what you’ll need. To “better understand” our ICPs, we used a wide variety of platforms where the data lives. To have a well-rounded ICP, we need to bring in a lot more data. So we used LinkedIn, our CRM, our website, our contracts, and other documents we’ve created. We used Google Gemini to help us analyze and summarize the information.

Performance: If our purpose is to understand who our ICP is, that’s what I’ll measure our exercise on. (spoiler: we figured it out).

If I were grading the user story, I’d give it a solid B. It could be further refined, but it gave us enough direction to get started.

Next, we had to collect all the data from the Platforms we listed. I’ll spare you the gory details of how we had to pull everything together. That’s not the point of this post. After the two hours we spent pulling everything together and massaging it through Gemini, we had our ICP. I know have a better handle on company size, revenue, roles, and pain points. Knowing these factors will help me focus our efforts.

What I learned through this process was that Generative AI was not the star of the show. Sure, we got through the data faster than we would have doing it manually. However, there was a lot of iteration with the system. The initial results were always generic. The memory of the system was short term. The capacity to take in data has limitations.

The star of the show was us. Me and Chris. The humans. The brains of the operation with the institutional knowledge. The people who know the company so well that we can reject generic results without hesitation. Not generative AI.

I say this because there is a lot of fear and insecurity that AI will take your job. There are hasty decisions to replace entire teams with generative AI. There is a large misunderstanding that generative AI will solve your problems. It won’t. And it should not replace your entire team.

Had we not worked at it, iterated, pressed on, we would have had very mundane results. We would have had an ICP, but there would be nothing that differentiates this profile from the company down the street. What are the specific pain points of OUR customers? Are the services we offer aligned with those very specific pain points?

You are the star of the show. You are the valuable asset. You know your customers, your company, your outcomes. Generative AI can learn these things, but it will forget as soon as you tell it. Generative AI can come up with a marketing plan, but it will give you the same plan it gave the person before you. You are what makes generative AI successful.

Let me climb down off that soapbox and get back to the point. Well, that was the point. Generative AI made our process move a lot faster, but it didn’t replace the hard work. We still went through the 5Ps. We still went through all our data. We still had to refine the outcomes. And now, we still have to do something with this information.

Now that I have an ICP, I can start taking action on creating custom content and services. I can focus my time. I can streamline the topics I write about in this newsletter. Hopefully, I can close more business. Fingers crossed.

Do you know your ICP? How did you create it? Reply to this email to tell me 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 examine the use of generative AI and lead generation. How do you use generative AI to improve lead generation? How do you build an ideal customer profile with generative AI? Tune in for step by step details!

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

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, let’s talk about analytics for a minute. What do we love about data and analytics? When properly done, when grounded in reality, data and analytics can help point us in the right direction. What marketing channel is working best? Data is generally more helpful than an uninformed opinion. How should we allocate our ad budget this quarter? Analytics tells us what we’ve gotten for our spend so far.

The problem with data and analytics is that very often, it’s decoration. We make a report, we build an analysis, and we hand it to our stakeholders and…


It becomes binderware. Shelfware. It’s decorative at best, and while our stakeholders may appreciate the thoroughness of our efforts or the attractiveness of our visualizations, ultimately nothing happens with it.

Why? Because converting analysis into action is difficult. It’s a different kind of thinking and one that many people aren’t necessarily skillful at. This isn’t a knock on them so much as it is a knock on the overall working environment many companies foster, one in which people are under constant stress and strain, unable to make time to think.

Analytics, by its very nature, requires time to think, to reflect, to consider carefully. When you’re presented with a chart that shows this kind of time-to-event decay model (which is what Google Analytics 4 uses as its data-driven model), it’s simply unclear what you should do next:

GA4 Conversion Paths

It’s a good analysis; if you know the underlying architecture, it makes sense. But if you don’t have that experience and the boss is badgering you for an answer now, now, now, what is the average marketer going to do?

Not use the data. They’ll just wing it in the hopes that they’re right and the boss will move onto the next false urgent crisis.

So what’s the solution? How do we get ourselves out of this conundrum? This is where generative AI can be of assistance. Because language and multimodal models like the ones that power ChatGPT and Gemini and Claude are trained on vast quantities of data – including data analysis – they can often help us bridge the gap between analysis and action.

I loaded the above Google Analytics conversion paths report screenshot into Gemini Advanced, gave it a series of instructions about how to interpret the data, and then asked it for 3 things I’m doing well, 3 things I’m doing poorly, and 3 things I should do next:

3 Things Going Well

  1. Strong Organic Search Presence: Your public speaking page is attracting significant traffic from organic search, suggesting good SEO or content that answers the questions people are searching for.
  2. Email Nurturing: Email campaigns play a key role, with many conversions involving multiple email touches. This indicates successful nurturing and engagement with your audience.
  3. Late-Stage Success: The high credit given to late touchpoints shows your ability to close interested leads. Your public speaking page content and any associated calls to action are likely compelling.

3 Things Going Poorly

  1. Underperforming Referral Traffic: While referrals drive some conversions, the overall impact could be better. This suggests potential improvement needed in partner outreach or the value offered to those who might recommend you.
  2. Weak Mid-Funnel Stages: Touchpoints in the middle of the customer journey receive less conversion credit. This indicates a potential drop-off or lack of engagement during that stage.
  3. Limited Social Media Impact: Organic social channels show limited contribution to conversions. Your content’s format or targeting on those platforms might not align well with your target audience for speaking services.

3 Things To Do To Increase Conversions

  1. Optimize Mid-Funnel Content: Analyze what users do in the middle of their journey and identify gaps. Provide content like case studies, testimonials, or webinars that cater to people in a consideration phase.
  2. Refine Referral Strategy: Create targeted incentives or value propositions for potential referral partners. Consider co-marketing opportunities or developing “refer-a-friend” programs.
  3. Focus on a Targeted Social Channel: Determine where your ideal speaking clients hang out online (LinkedIn, for example). Double down on tailoring your content and engagement on that platform.

What was previously a fairly inaccessible analysis now has concrete steps for me to evaluate and decide if they’re right for my marketing strategy. Instead of me puzzling what exactly is going on in the report, I have a roadmap of what’s working, what isn’t working, and what things I might want to try to increase conversions.

Now, this is a relatively small example. To be thorough, you’d want to incorporate other marketing data as well, such as what activities you’d been doing in this time period that generated these results, other data from other systems like your CRM, etc. that could detail the quality of these conversions, but you get the idea. Instead of staring blankly at a chart, this helps nudge us over into the action side, into doing something with our data… into becoming actually data-driven.

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