So we’re at this crossroads where you identified three potential client types (ICPs).

Yesterday, I gave you a three-lens framework through which to evaluate them (A-P-I). At a high-level:

• Access - Can you reach and speak to this audience at scale?
• Problem - Is the problem you’d solve for them predictable and expensive?
• Impact - Does the transformation you provide create significant, direct value?

These are important things to consider, but you could spend weeks or even months on this seemingly simple exercise and still struggle to pick a lane.

Why?

• We over-index on our own knowledge, experience and biases
• Our information will always be incomplete
• We don’t know what we don’t know
• (Also, FOMO 😉)

Luckily, this type of analysis is an excellent use case for AI tools like ChatGPT.

Using the right prompt, ChatGPT can perform this ICP analysis for you instantly, looking at it from angles you never would’ve come up with on your own.

Yesterday, I gave an example of a solo data analyst/storyteller, let’s call her Emily.

Emily is considering these ICPs:

1. Early-stage tech companies swarmed with new user data
2. Online brands hitting unexplained growth plateaus
3. Non-profits seeking to understand their donor base and donation trends

Tossing them over to ChatGPT (💡 link to prompt & full output below) returned insights for ICP #1 like:

• “Groups/Orgs: There are plenty of incubators, accelerators, and VC networks that corral early-stage tech startups. Conferences like TechCrunch Disrupt, Y Combinator Demo Days, and local tech meetups are prime aggregators.”
• “Problem solved in-house? Usually, early-stage companies are strapped for specialized analytics resources. They might have a generalist data person, but not someone who can craft a clear strategic narrative out of large data sets. They often “try” to solve it in-house but lack the senior perspective or time.
• Comparable/Greater Than Alternative: The alternative is often a full-time data scientist or a costly BI solution. You offer a combination of data analysis and storytelling/strategy—a rare combo. This can be more cost-effective and nimble than a full hire or big consulting firm.

Going further, it also provided Emily with a Recommendation and Ranking based on the analysis it performed.

See the full output and try the prompt out yourself using the simple instructions provided.

💡 The site is currently gated for Lightbulb subscribers. If you're reading this on the archive, feel free to subscribe and then email me for the password, wes@weswheless.com

​

The caveats:

• You’ll still want to validate the analysis and recommendations before making a decision
• Consider the AI output as your new starting point, not as a replacement for independent research and market conversations

​

Have fun, and let me know what you think!

With this as the new baseline, there’s so much more to come.

💡

-Wes