Christopher S. Penn – Marketing AI Keynote Speaker

Almost Timely News, March 31, 2024: Step By Step Building an Ideal Customer Profile From Scratch With Generative AI

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Christopher S Penn
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Almost Timely News: Step By Step Building an Ideal Customer Profile From Scratch With Generative AI (2024-03-31) :: View in Browser

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Almost Timely News: Step By Step Building an Ideal Customer Profile From Scratch With Generative AI
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What’s On My Mind: Step By Step Building an Ideal Customer Profile From Scratch With Generative AI

This week, let’s get down to brass tacks. We’ve talked a lot at a high level about building an ideal customer profile, and the very best ideal customer profiles are built on a foundation of lots of high quality data. That’s still the gold standard, the way you want to do things if you can.

But let’s acknowledge reality. A lot of companies… don’t have that data. Either because the data is a mess, or because the company just doesn’t have it. There’s a reason why social networks have ALL locked down their data, cancelled their APIs or raised prices to make them unaffordable, and put up walls to interoperability as fast as possible. They recognize just how valuable that data is.

The good news is, you can still build a strong ideal customer profile with relatively little data. It will not be as good as having lots of high quality data, to be clear. But it will be good enough to at least start using generative AI more powerfully than basic starter “you’re a Pulitzer Prize winning reporter” prompts.

For today’s use case, I’m going to pretend I’m back at the public relations agency I used to work at – but this technique will work for just about any kind of role where you need an ideal customer profile, from sales to marketing to advertising.

First, we need to be clear on who even is in our ideal customer profile. Let’s say I work at a B2B PR agency. I know that I need to get press coverage for my client – we’ll say Trust Insights, my company, is the client. Trust Insights has a fancy generative AI course (shameless plug) and wants to get the word out about it.

We’ll need a media list, or at least the start of a media list, of people who even cover the generative AI space. So our first stop will be any AI-enabled search engine such as Microsoft Bing, Google Gemini, or Perplexity. We’ll ask it for a few names of prolific journalists in the generative AI space.

Perplexity Results

At the top of the list is author and influencer Bernard Marr. That’s as good a place as any to start. Next, we should get a sense of what kinds of things Bernard writes about. Let’s download and store his last 20 or so articles in plain text format; you can automate this step or do it by hand, so long as you end up with plain text articles when you’re done.

After that, let’s grab the contents of Bernard’s LinkedIn profile. The easiest way to do this is to simply download the PDF version of it.

LinkedIn Example

Great. Now we have quite a lot of raw materials to work with. Let’s start building Synthetic Bernard. Open the generative AI tool of your choice that can handle large datasets, such as the paid versions of Google Gemini, ChatGPT, or Anthropic Claude.

Start your session by asking the model what it knows on the topic, like so:

“Today, we’re going to build an ideal customer profile. What do you know about best practices for this kind of thing?”

Every model will behave differently, but this will give you a starting point for framing out the ICP and more important, help the model give structure to all the data we’re about to give it. Once the model has returned its answer, tell it you’re going to give it some raw data to start inferring a profile, a persona:

“Great. I’m going to provide you with a large body of data of a person who is our ideal customer. This person, Bernard Marr, represents the ideal customer for my company, Trust Insights. From this information, and the best practices you’ve outlined, I’d like you to infer an ideal customer persona using the key elements you’ve highlighted and the information I’ve provided from Bernard’s publicly available information.”

After it has a good long think, it’ll come back with a profile that looks like this:

Based on the provided information and best practices for creating ideal customer profiles, here’s an inferred persona for Bernard Marr:

Demographics:
– Age: Mid-50s (estimated)
– Gender: Male
– Location: Milton Keynes, England
– Education: Highly educated, with degrees from Cambridge University and Cranfield School of Management

Professional Profile:
– Occupation: Internationally best-selling author, keynote speaker, futurist, business, tech & strategy advisor
– Industry: Technology, Business, Management Consulting
– Company: Founder and CEO of Bernard & Co. and Bernard’s Wine Cellar
– Expertise: Business performance, digital transformation, data strategy, AI, big data, blockchain, IoT

Psychographics:
– Values: Innovation, efficiency, data-driven decision making, continuous learning, human-centric technology
– Interests: Emerging technologies, business trends, future of work, social impact of technology
– Motivations: Helping organizations improve performance, understand and leverage new technologies, make better decisions
– Challenges: Keeping up with the rapid pace of technological change, educating businesses on the potential and risks of AI, ensuring ethical and responsible use of AI

Behaviors:
– Regularly reads and writes about technology and business trends
– Attends industry conferences and events
– Actively engages on social media and shares content with a large following
– Consults with businesses and governments on strategic initiatives
– Seeks out and uses innovative tools and technologies

Media Consumption:
– Forbes (regular columnist)
– World Economic Forum (frequent contributor)
– LinkedIn (highly active)
– Other social media platforms
– Online publications and research reports

Inferences:
– Bernard is a thought leader and influencer in the technology and business space. He is highly knowledgeable and passionate about emerging technologies, particularly AI, and their impact on businesses and society.
– He is likely an early adopter of new technologies and seeks out solutions that can improve efficiency and effectiveness.
– He values data-driven decision making and is a strong advocate for ethical and responsible use of AI.

– He is a prolific writer and speaker, reaching a large audience through various channels.

This is a great start for this kind of persona. If the people I’m pitching for my PR agency are like Bernard, this persona will be super helpful. Let’s now put it to work. Suppose I have a pitch like this (yes, generated by AI):

Subject: New Course Exposes Marketing Potential and Pitfalls of Generative AI

Dear [Journalist’s Name],

With generative AI tools like ChatGPT booming, many marketers are scrambling to grasp their potential and manage the risks. A new course by Trust Insights, “Generative AI for Marketers,” aims to bridge this knowledge gap. I saw your recent piece on [topic related to AI in marketing] and believe this course would be of interest to your readers.

This 5-hour intensive course goes beyond basic prompt engineering to tackle topics crucial for marketers: AI governance, scaling, risk mitigation, and career impacts. Could an interview with course creator Chris Penn [or a lead instructor] offer valuable insights to your audience navigating this rapidly changing landscape?

Key Benefits for Marketers:

  • Deep dive into AI foundations
  • Practical skills for enhanced marketing strategies
  • Real-world use cases and guidance
  • Who is it for? Marketers interested in, or currently using, generative AI seeking to maximize its benefits while mitigating risks.

Please let me know if you’d like to learn more or schedule an interview.

Best regards,
[Your Name]
[Your Contact Info]

Now, I can say without hesitation, this isn’t a super great pitch to start with. (and yet I’ve gotten hundreds of pitches just like this). So how do we use our Ideal Customer Profile, our synthetic Bernard? From the profile generated… we ask him.

Gemini roleplaying Bernard

In other words, Synthetic Bernard has basically said… pass. As someone who receives a lot of pitches like this, I can say that Gemini’s predicted reaction is much kinder than what usually goes through my mind. So, now that we know our pitch isn’t going to land, what do we do about it? I’ll leave the rest as an exercise for you to complete, but it’s not a great leap of imagination for you to have an ongoing conversation with Synthetic Bernard to ask how to fix this pitch.

The key takeaways from this exercise are that ideal customer profiles can be built with minimal data. In this case, I had the contents of a LinkedIn profile plus 16 articles from the web. That’s it – no multi-year sales data, no deep dive into a person’s background, no secret agent stuff, just a pile of data from publicly available sources.

If you were doing this for your PR agency, for your marketing agency, for your sales team inside your company, for your corporate communications team, you’d want to broaden this beyond just a single person. Maybe you’d have 5 or 10 people’s publicly available data as a starting point and create a rollup synthetic persona or ideal customer profile from that data.

If you’re a job seeker, this technique applies to you. Synthesize a persona for the hiring managers you’re working with – especially the ones that have rejected you – and then use that persona to critique your materials, your interview responses, etc.

No matter what route you take, building an ideal customer profile is within reach for any organization, big or small, wealthy or poor. Leverage the data you do have, plus the best models available to you today, and you can get started making use of generative AI with ideal customer profiles to answer questions you have about your marketing (or anything else you want to ask it).

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ICYMI: In Case You Missed it

Besides the new Generative AI for Marketers course I’m relentlessly flogging, I did a piece this week on how to use generative AI to head off criticism.

Skill Up With Classes

These are just a few of the classes I have available over at the Trust Insights website that you can take.

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Get Back to Work

Folks who post jobs in the free Analytics for Marketers Slack community may have those jobs shared here, too. If you’re looking for work, check out these recent open positions, and check out the Slack group for the comprehensive list.

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If you’re familiar with the Cameo system – where people hire well-known folks for short video clips – then you’ll totally get Thinkers One. Created by my friend Mitch Joel, Thinkers One lets you connect with the biggest thinkers for short videos on topics you care about. I’ve got a whole slew of Thinkers One Cameo-style topics for video clips you can use at internal company meetings, events, or even just for yourself. Want me to tell your boss that you need to be paying attention to generative AI right now?

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Events I’ll Be At

Here’s where I’m speaking and attending. Say hi if you’re at an event also:

  • Lab Products Association, Nashville, April 2024
  • Society for Marketing Professional Services, Boston, April 2024
  • Society for Marketing Professional Services, Los Angeles, May 2024
  • Australian Food and Grocery Council, Melbourne, May 2024
  • MAICON, Cleveland, September 2024
  • MarketingProfs B2B Forum, Boston, October 2024

Events marked with a physical location may become virtual if conditions and safety warrant it.

If you’re an event organizer, let me help your event shine. Visit my speaking page for more details.

Can’t be at an event? Stop by my private Slack group instead, Analytics for Marketers.

Required Disclosures

Events with links have purchased sponsorships in this newsletter and as a result, I receive direct financial compensation for promoting them.

Advertisements in this newsletter have paid to be promoted, and as a result, I receive direct financial compensation for promoting them.

My company, Trust Insights, maintains business partnerships with companies including, but not limited to, IBM, Cisco Systems, Amazon, Talkwalker, MarketingProfs, MarketMuse, Agorapulse, Hubspot, Informa, Demandbase, The Marketing AI Institute, and others. While links shared from partners are not explicit endorsements, nor do they directly financially benefit Trust Insights, a commercial relationship exists for which Trust Insights may receive indirect financial benefit, and thus I may receive indirect financial benefit from them as well.

Thank You

Thanks for subscribing and reading this far. I appreciate it. As always, thank you for your support, your attention, and your kindness.

See you next week,

Christopher S. Penn

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