Trust Insights

I'm the resident AI person at Trust Insights. Got a marketing data, analytics, or AI strategy problem? I'll help you solve your mysteries.

I've built AI-powered attribution modeling (to know what's working and what isn't), predictive analytics for content marketing (to know what to publish and when), and digital customer journey mapping (to know what to say and where) - long before ChatGPT existed. In fact, I've been working in the AI field since 2013.

Today, I speak and teach around the world about how to make the most of the three classes of AI (including generative AI) for your business.

Co-Founder and Chief Data Scientist

Marketing Over Coffee

I'm the co-host of one of the top marketing podcasts, largely thanks to my talented co-host, John Wall. Each week we discuss old and new marketing, tips, tactics, methods, ideas, strategies, and much more to get more out of your marketing efforts. With over 700 episodes and a million downloads, it's one of the most popular marketing podcasts in the world.

Visit http://www.MarketingOverCoffee.com for more information and how to get the show for free.

Co-Host

Social Media Pulse

Member of the Social Media Advisory Board. I provide guidance to the team about social media trends, especially as they relate to marketing analytics, social media marketing analytics, social media and data science, and social media and artificial intelligence.

Board Member

The Order (Non-Profit)

The Order advocates for equitable treatment and representation of LGBTQ+ and female-led media and entertainment. Through strategic fundraising, public support campaigns, and advocacy, we aim to promote greater diversity, equity, and inclusion in the entertainment industry. Our vision is a world where all forms of media are celebrated and valued, regardless of creators' gender, sexual orientation, or background.

In my role as Head of Data Science for The Order, I:
- Led comprehensive data science initiatives, driving targeted advertising campaigns, analyzing advertising media landscapes, and conducting custom audience analysis.
- Developed and implemented advanced models and algorithms for audience inference, Twitter data processing, and propensity score risk assessment.
- Orchestrated the creation and management of custom software solutions for social media management, email marketing with integrated data, and media monitoring.
- Conducted extensive research on latent demand patterns, media consumption, and strategic acquisition opportunities, providing valuable insights for marketing strategies and decision-making.
- Produced captivating video ads and implemented innovative influencer marketing programs, expanding brand reach and driving engagement.
- Utilized predictive analytics to forecast demand patterns and develop propensity score risk models, optimizing resource allocation and decision-making processes.
- Crafted and executed public relations strategies, managing brand reputation and external communications.
- Oversaw survey data processing and reporting, generating actionable insights for marketing and business strategies.

Head of Data Science

SHIFT Communications

At SHIFT, I help clients understand how earned media and public relations impact their marketing efforts and demonstrating how to measure PR, marketing, and finding ROI in a big picture view. I run many of the inbound marketing and lead generation programs for SHIFT's own marketing, from CRM administration to Pardot marketing automation to Google Analytics and more. In the first 3 months, I exceeded my lead generation targets by 16x using proven, tested lead generation and content marketing strategies, implemented cutting edge data science and machine learning practices, and I've built a multimillion dollar business unit.

Learn more at http://www.shiftcomm.com

Vice President of Marketing Technology

National Speakers Association

I had the honor and privilege to address NSA about the future of public speaking, augmented by artificial intelligence. Feedback included:
"Your presentation was fantastic! Thank you for sharing a portion of your brilliance with us! #nsa18"
"@cspenn did a great job explaining how #AI will disrupt speaking! Wise speakers will take actions to leverage AI! #nsa18 #Speaker #disrupt"
"I loved the way you married great presentation style, data and analytics, and relevance to the group."

Speaker

Social Media Dallas

I had the honor and privilege to address Social Media Dallas about predictive analytics for social media marketers. Feedback included:
"Can you tell I was excited to be at #SMDallas? Thanks for the great presentation on predictive analytics @cspenn. "
"Thanks @cspenn and @SM_Dallas for a great presentation tonight!"
".@cspenn is blowing our minds teaching us about Predictive Analytics! #smdallas"

Keynote Speaker

Marin Software

Delivered the opening keynote at Marin Masters, New York City on cognitive marketing.

I spoke on the Rise of the Citizen Analyst, how the democratization of analytics tools is fueling the citizen analyst movement.

World of Watson 2016 Speaker

HubSpot

Delivered the track keynote on building a data-driven customer journey.

Track Keynote Speaker

Christopher S. Penn is an authority on analytics, digital marketing, marketing technology, data science, and machine learning. A recognized thought leader, best-selling author, and keynote speaker, he has shaped five key fields in the marketing industry: Google Analytics adoption, data-driven marketing and PR, modern email marketing, marketing data science, and artificial intelligence/machine learning in marketing. As co-founder and Chief Data Scientist of Trust Insights, he is responsible for the creation of products and services, creation and maintenance of all code and intellectual property, technology and marketing strategy, brand awareness, and research & development.

Mr. Penn is a 2024, seven-time IBM Champion in IBM Data and AI, a Brand24 Top 100 Digital Marketer, an Onalytica Top 100 AI in Marketing influencer, and co-host of the award-winning Marketing Over Coffee marketing podcast. Prior to co-founding Trust Insights, he built the marketing for a series of startups with a 100% successful exit rate in the financial services, SaaS software, and public relations industries. His work has served brands such as Twitter, T-Mobile, Citrix Systems, GoDaddy, AAA, McDonald’s, and many others.

Mr. Penn is an IBM Watson Machine Learning Certified Professional, a Google Analytics Certified Professional, a Google Ads Certified Professional, a Google Digital Sales Certified Professional, and a Hubspot Inbound Certified Professional. He is the author of over two dozen marketing books including bestsellers such as AI for Marketers: A Primer and Introduction, Marketing White Belt: Basics for the Digital Marketer, Marketing Red Belt: Connecting With Your Creative Mind, and Marketing Blue Belt: From Data Zero to Marketing Hero, and Leading Innovation.

Learn more about Christopher here:

https://www.ChristopherSPenn.com
https://www.MarketingOverCoffee.com
https://twitter.com/cspenn
https://www.trustinsights.ai

Important: If your first message after connecting is a pitch, then with regret I need to report your message as promotional/spam to LinkedIn and remove the connection.

You can no longer opt out of AI.

The biggest change that AI-enabled browsers makes isn't to the people using them, it's to everyone's data that's being seen by them.

Perplexity's Comet.

ChatGPT Atlas.

Google Gemini.

Take your pick of the AI-enabled browser of your choice because they all have the same general privacy provisions. They say that you, the user, have control over what data it logs, and that the browser will, with your permission, store the data that it uses for increased functionality, and of course, training.

But that's for the user of the browser. That isn't for everyone else.

In the screenshot shown, I was commenting on a post by Marcus Sheridan. Out of curiosity, I turned on Google Gemini and its integration into the Chrome browser. And I asked it to record all of the reactions to Marcus's post. It did. I then asked it for the LinkedIn profile URLs of everyone who reacted on Marcus's post. It did. And I asked it for a CSV file that I could download of everyone who reacted to the post. And it did.

And all that data normally invisible to Google is now on Google's servers for processing.

In another test, I had it transcribe all the comments on Rebecca Bultsma's post about AI ethics. (oh, the irony, right?)

The same thing works in ChatGPT Atlas and other browsers.

LinkedIn can't prevent this because the browser is literally reading the HTML that it has been sent. The same is true of ChatGPT Atlas or any browser because the AI tools are reading the HTML that has been sent to us, the humans, which has to be readable.

Did I opt into AI data collection? Yes, I did. Did the 292 people that engaged on Rebecca's post opt into AI data collection? Maybe, maybe not. But they are not given a choice and their data is being vacuumed up by AI-enabled browsers being used by others.

Like the humans in the Matrix, we are doing the machine's work for it. As we browse with AI-enabled browsers, we are transmitting enormous quantities of data that AI companies themselves might not be able to get access to because of things like paywalls or logins. Think of all the places you browse that a search engine can't normally go. Think of all the places people with AI-enabled browsers are going that are handing over massive amounts of data, potentially without the system owner's consent.

Should you use an AI-enabled browser? That's up to you. But recognize that your data is not the only data that it's taking.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

Christopher Penn

Co-Founder and Chief Data Scientist at TrustInsights.ai, AI Expert

If it doesn't work as a prompt, it won't work as an agent.

I toyed with OpenAI's new Agent Builder, which is like a watered-down N8N or Zapier. It's obviously locked to the OpenAI ecosystem, so you can only use their models or infrastructure.

First, to be clear, this launched on DevDay. A lot of folks frothing on social media about this are not developers, and are loudly complaining about how unintuitive it is. Yeah. It's for developers. Things like MCP calls, local vector stores, etc. are all intended for use by developers building agents. If you're not a developer, it's not for you.

That said, like Google Opal, it's a slick, simple workflow builder for building agents that requires no extra infrastructure on your part.

Now, the important part: at its core, it's a wrapper around an LLM. That means that if you want your agent to function well, it has to have a bulletproof prompt. I say this in my workshops and keynotes: if it doesn't work as a prompt, it won't work as an agent.

Before you type one character into the agent interface, make sure you have tested the hell out of your prompt in the regular system. Put it through a prompt optimizer. Test it and make sure it reliably works, because if it doesn't work in a chat, it will not work in an agent. It'll just not work at scale and cost you a lot of compute time/cost while not working.

For example, I built a super simple agent as a test to do media monitoring. Before I pasted even one line into the agent, I made sure it worked in regular ChatGPT. (spoiler: it took about 5 iterations to get it right)

Think of prompting like software development, like the dev version. Think of the agent like the production version. Don't rush a dev alpha into production unless you want a really bad time.

A good prompt becomes a better agent.

A bad prompt becomes a worse agent.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

At several events I've spoken at recently, I've been told by people that they feel they're beginning, intermediate, or advanced in AI.

Yet once the session starts, and we start digging in, it becomes abundantly clear that those labels are meaningless. One person's advanced is another person's basic.

This is especially challenging for those of us privileged and honored to teach others, to guide. It's hard to know what level to teach at when a person says one thing, but evidence shows another.

Here's how I define this more clearly:

- Beginning: just started using tools like ChatGPT (or similar) or haven't used it yet
- Intermediate: using ChatGPT (or similar) and getting good results, usable outputs
- Advanced: creating mini-apps (ChatGPT GPTs, Gemini Gems, Claude projects)
- Expert: building AI workflows in tools like Opal, Agent Builder, n8n, Make, Zapier
- Master: building and deploying AI-enabled code in Python or other high-code environments

Another way to do this, and we did this for our upcoming London generative AI workshop, is to list out tools in the ecosystem and see what people use on a regular basis. Someone who uses OpenAI Codex is going to have a different perspective on generative AI than someone who uses stock ChatGPT.

Definition is the precursor to clarity. By level setting what each label means, we are much more clear and other people can be much more clear about where they are. 

Meeting people where they are requires knowing where to meet them, and the only way to do that is to help them define those locations.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

Basic power tip:

If you use GMail, it automatically tracks what emails you're subscribed to and shows them all on one screen. Go in, and remove anything you don't want.

"I don't know what to post on LinkedIn!"

Just from your phone alone:

1. Turn on screen recording. Choose a hashtag for your topic.
2. Swipe through 30 seconds of your feed.
3. Save the video and open it in the genAI tool of your choice, like Google Gemini.
4. Have it transcribe all the posts you swiped through.
5. Turn on voice transcription and ask: "Of all these posts on the topic of {topic}, what's good? What's bad? What's missing? What's unnecessary?" Let it respond.
6. After it responds, follow up: "I am a leading expert on {topic}. From these Linkedin posts, identify 5 questions I can answer that executives interested in {topic} would have that these posts failed to answer."
7. After it responds, follow up: "Create 5 contrarian, controversial, adversarial questions based on these LinkedIn posts about {topic} that I can answer that these posts failed to answer, misled the audience, or willfully ignored."

Congratulations, you now have two weeks of content, assuming you actually know the topic and can answer the questions. Turn on your voice memos app, record your answers, extract the transcripts, clean them up, and you're good to go.

Here's an example of two of these questions, from the video:

The "Profit vs. Principle" Question: Everyone loves to talk about "trust" and "responsibility" until it has a cost. Let's be blunt: when an ethical choice—like de-biasing a model—demonstrably lowers predictive accuracy by 2% and costs the company millions in revenue, isn't that "ethics framework" the very first thing to be ignored? Can you name a single public company that has ever willingly chosen to make less money in the name of "responsible AI"?

The "Elitist Morality" Question: Alan Robertson's post asks who should have "moral authority"—builders or humanity? Looking at this feed, the answer seems to be "consultants, CEOs, and academics." Isn't this entire "AI ethics" movement just an elitist, anti-democratic attempt by a specific, privileged Western class to impose its own subjective moral framework on the rest of the world, all without any mandate or authority?

Tough questions. Tougher answers. But REALLY interesting, and a nice reaction to the topic overall.

The key here is not to have AI write content for you, but to have AI prompt YOU to write content only you can, by asking the toughest questions of you.

Background music generated in Suno.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

The future of work in an AI-forward world looks a lot like the future of agriculture work.

Pretend it's 1825. What is life like? 

It will be 6 years before Cyrus McCormick invents a horse-drawn mechanical reaper, so you're using a scythe to reap grain.

It will be 12 years before John Deere invents the steel plough. Iron ploughs exist, but clump and clog easily. The Pitts brothers will invent a threshing machine to separate wheat from chaff. Until then, you're doing that by hand.

It will be 24 years before chemical fertilizers are invented. Until then, you rely on literal 💩.

It will be 70 years before refrigeration is invented. Until then, crops spoil quickly once harvested.

And it'll be almost a century before tractors make plowing and reaping scalable. But once they are, one person can plow an entire field in a day or less.

What's the net effect? ~75% of the population worked in agriculture, directly on farms in 1825. Two centuries later, that's 1.2%. Yet the agriculture industry feeds a population substantially larger. Automation and mechanization make farming far more efficient and effective.

Where did the employees go? Into manufacturing, services, other industries, other fields. And it wasn't always a smooth ride - major disruptions like the Great Depression were part of that journey.

If you want a blueprint of what knowledge work will look like in an AI-forward world, it probably looks a lot like agriculture - far fewer people creating far more stuff. What does your industry look like with 98.4% fewer people working in it?

And borrowing from agriculture, little farms didn't go away. Home gardens didn't go away. People still grow things - but the way you make a living changed. Knowledge work, for a lot of people, will not be profitable work you can make a living on by itself. It'll be part of something else.

Photo taken at Mystic Seaport by me.

#AI #GenerativeAI #GenAI #ChatGPT #ArtificialIntelligence #LargeLanguageModels #MachineLearning #IntelligenceRevolution

In this week's In-Ear #Insights (the @TrustInsights #podcast) @katierobbert & @cspenn discuss the future of work at #MAICON25 and how generative AI is changing everything, recorded live on the show floor:

Join me at 2pm EST, November 13th, for the AEC Masterclass dedicated to AI for Strategic Planning.

You will learn to:
✅ Build and compare plan variants (best/base/worst case).
✅ Quantify risk and upside for each move (margin, hit rate, cycle time).
✅ Translate the chosen scenario into an execution roadmap.

Start building profitable, adaptive plans.

Registration link below.

#AEC #StrategicPlanning #AIStrategy #ActionableAI

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In this episode, you’ll learn:
-What is the new Claude Skills function
-How Claude Skills is different from a GPT or Gem
-Getting started with Claude Skills

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Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

So What? Getting started with Claude Skills

#ICYMI: The big takeaway from yesterday’s "So What?" on Claude Skills is that Anthropic is taking a major step toward making AI models truly modular.

Claude skills allows you to encapsulate custom instructions and data, then invoke that specific expertise right in the middle of any conversation, regardless of topic. This is a massive leap in utility and portability that surpasses the current limitations of GPTs.

Just be sure to watch your usage. A simple presentation skill can devour your compute budget in a hurry.

Full video on our YouTube channel

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