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

Trust Insights

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

We'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).

We administer and maintain clients' analytics and MarTech infrastructure, help get your marketing measurement strategy up to date and in order, and amplify the power of your social media, SEO, and digital advertising efforts.

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

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.

Something is missing from generative AI.

Well, from your usage of it.

Take a look at some of the "killer" prompts I've seen floating by on LinkedIn (these are paraphrased to avoid calling out any one person/company):

HEADLINE DYNAMO: Write a killer headline with our special awesomesauce prompt: "You're an award winning journalist, write an article headline about XYZ Company's new product release that is compelling and interesting."

EMAIL MASTER: Write four different email subject lines that will double our engagement and open rates. (insert email details here)

SHOW THE LOVE: Write a glowing customer testimonial based on the following customer feedback, making it convincing and compelling. (insert details here)

MAKE THAT MONEY: Write the ultimate persuasive call to action for this landing page. (landing page copy here)

What's missing from these "killer" prompts that "all the best marketers use"?

Besides being woefully inadequate as prompts in general (these will invoke very, very generic results), the one thing missing from all of these, and from nearly every marketing prompt I've seen is...

... the customer. This is something Katie Robbert and I spent an afternoon on recently. We sat down with our CRM data from our Hubspot instance. We extracted LinkedIn profile data of our top buyers. We combed through emails, we collected form submission data, we put all our customer data together and we fed it to a generative AI system (we used Gemini, but any large model will do).

What we ended up with was around a 10 page distillation of our ideal customer profile, the person who has bought from us in the past and the person we'd like to have buy from us in the future. We have demographics, firmographics, psychographics, needs, hopes, fears, the works. TEN PAGES.

Why? Because the above prompts are based on the generic dataset. If you combined them with an ideal customer profile based on REAL customer data? They'd work a lot better. For example, instead of "double our engagement", what if the email prompt went like this?

Based on our ideal customer profile (previously pasted), write ten different email subject lines that are most likely to resonate with and appeal to our ideal customer. For each subject line you generate, include an explanation of why this subject line will resonate with the customer.

You will absolutely get better results this way from any language model, even with mediocre prompts.

Invest the time and effort now to build rich, detailed data you can use with any generative AI system. It will pay dividends over and over again, and make AI work for YOU SPECIFICALLY.

Christopher Penn

Annual PSA: Tomorrow is April Fools. Whatever your natural skepticism dial is set to, turn it up overnight. And if you're in marketing, don't make any product announcements tomorrow if you want to be taken seriously. Wait a day.

And if you're reading this after April 1, be sure to check the date on everything you read for at least a week.

DEI = AI.

Or rather, DEI (diversity, equity, inclusion) = more proficient use of AI.

Here’s why. The results you get out of generative AI are contingent on what you prompt it with. Give it bad, generic, or bland prompts and you will get bad, generic, and bland results, every time.

AI is like the fabled genie in a lamp. You tell it what you want, and it gives it to you - even if what you want is objectively a bad idea.

So if you want the best outputs from AI, you have to have the best inputs going into it. Diverse, original, unique ideas become diverse, original, unique prompts, and create diverse, original, unique outputs.

AI models - the software that powers tools like ChatGPT - are nothing more than massive statistical libraries. They have no sentience, no self-awareness, no ability to step back and reflect on what they’re asked unless prompted to do so.

Which means that if you have a monoculture of people creating prompts, you will have a monoculture of results. If, for example, your team was all middle-aged Korean men like me, then your results from AI will all be biased to things middle-aged Korean men ask for. Unless your entire customer base is also all middle-aged Korean men, AI will generate suboptimal outputs.

If you have a highly diverse group of people with radically different life experiences prompting AI models, you will get highly diverse outputs.

Your success with AI depends on your success with DEI. The more diverse the people making the prompts, the more diverse outputs you will get from AI. And if you’ve dismantled your DEI efforts and returned to a monoculture of people, you also have a monoculture of ideas, and your AI results will become just as bland as the people making them.

Now is the time to invest MORE heavily in DEI, not less.

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

In today's newsletter, we'll tackle a common problem: how to build a strong ideal customer profile (ICP) even if you lack extensive data. You'll learn how to harness generative AI to create a powerful ICP using readily available, public information (for the demo, I use Bernard Marr). This technique unlocks new opportunities to target your marketing efforts strategically.  You'll gain the insights to customize your messaging and pitches, ultimately boosting your chances of success.

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

Christopher Penn on LinkedIn • 13 min read

Almost Timely News: Step By Step Building an Ideal Customer Profile From Scratch With Generative AI (2024-03-31)

I'm a terrible coder.

I've been going back through the code I've written over the past decade and feeding it into today's generative AI models which are - compared to me - superior coders.

I had good ideas. I just implemented them poorly. Error checking? Nope. Clean syntax? Nope. Comments and documentation? Nope.

Why didn't I do those things? Two reasons: partly because I'm so eager to get the idea out the door that I never slowed down to do proper software development, and partly because I never had any formal training as a software developer, so I didn't even know what I was missing.

And for a while, that became painful. As things broke, I couldn't remember why I wrote them to begin with. No documentation. And the things that broke shouldn't have broken, because proper coding practices like graceful failure weren't ever something I learned.

Generative AI has fixed a lot of that. This morning, I ran into a bug in our content curation software. Rather than try to fix it, I handed the code to a large language model and said, "help me understand why this is happening and what to do about it". It gave me not only a suggested fix, but the documentation to go with it.

And it now writes my requirements and documentation. This is an ideal use case for generative AI - not to come up with the ideas, but to make sure the ideas are fully baked and fully fleshed out. It will even, when asked, tell me more efficient, effective ways of doing the same thing. There used to be a ton of repetition in my code; on average, my code is now 30-40% SHORTER because generative AI looks at it and goes, "That's dumb, turn that into a function/object and stop repeating yourself."

You may or may not want to use generative AI to make things, but you sure should use it to critique the things you make and help you improve them.

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

A delightfully fun interview I did with Alaura Weaver 🌈♾️ and the team at Writer about AI, data science, and understanding the power of data, why I'm spamming Twitter, and what I'm coding to evaluate LLM outputs.

https://lnkd.in/ebHP6wgv

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

writer.com • 6 min read

How the nerds are leading the AI revolution with Trust Insights’ Christopher S. Penn

All value is relative to scarcity.

This is a photo of a very ordinary restroom. We would not expect to pay extra for it. 

Put the same size restroom in an airplane or a cruise ship and it comes at a premium cost that many folks are willing to pay for.

If something has value, moving it to an environment where it’s scarce increases its value. 

Which means if your business isn’t bringing in the revenue you want, there’s a chance the value you provide isn’t scarce enough in the context you offer it.

Sometimes the path to success isn’t more value or different value, but value in a different context.

In this week's issue, I'll take you on a guided tour of the most powerful AI model Google has to offer - Gemini 1.5. You'll learn how to harness this incredibly advanced technology to summarize huge amounts of information and turn it into actionable insights. If you're trying to master a new topic like Instagram marketing, this tool is a game-changer!

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

Summary generated by Gemini. Inception :)

Christopher Penn on LinkedIn • 16 min read

Almost Timely News: A Guided Tour of the Most Powerful Generative AI Model Google Offers (2024-03-24)

Ever read “Choose Your Own Adventure” books?

That’s how generative AI language models work. 

Except that instead of reading a few paragraphs and then turning to the appropriate page to continue the story, language models are choosing how the story continues after every single word.

But like a Choose Your Own Adventure, it keeps track of the story that’s already been told. There aren’t an infinite number of choices at the bottom of every “page” as it “reads” (predicts). There’s a handful of words that are most probable.

Suppose the story an AI is processing has read the following words so far:

I pledge alliance to the

What’s the next most likely word it will choose as it pursues its word-by-word Choose Your Own Adventure?

Probably flag.

Probably not rutabaga.

And it makes that choice based on probability, based on the number of previous stories it’s read (training data) where flag was almost always the next word.

So why do these models go off the rails? They go awry when they haven’t read enough story to choose the next word sensibly. Imagine you were reading a Choose Your Own Adventure book and the first page you read had the single word “Today”. Would you know what to choose for the next page? You’d have a ton of choices - even if you knew you wanted a romance or a thriller, it’s still too vague.

That’s why prompting well with detailed prompts is so important. Give a model enough of the story so far, and the next part of the story that it chooses will be much more sensible.

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

In this week's In-Ear #Insights (the @TrustInsights #podcast) @katierobbert & @cspenn discuss when #GenerativeAI is the wrong answer to the problem, despite being all the rage. Find out when this is the case and what to do instead.

https://lnkd.in/ezWtTzcJ

Memory changes everything.

It's difficult to overstate just how big a deal it is that today's language models have context windows in excess of 1 million tokens.

1 million tokens is roughly 700,000 words.

What does this mean? A context window for a model is its short-term memory. When you start a new session with any language model like ChatGPT, it has no memory of previous conversations. It's a blank slate, and from the moment you start submitting prompts, the short-term memory starts to fill.

To give you some context, if you were to talk non-stop for an hour, you'd accrue 9,000 words. The free version of ChatGPT has a short-term memory of roughly 10,000 words, give or take. That means that you could talk to it for an hour and then it would start forgetting what you'd said at the beginning of the hour - and that's without it responding.

With a short-term memory of 700,000 words, you could foam at the mouth non-stop for 75 hours and not exhaust the short-term memory.

When model memory gets that large, a few things change:

Some prompt engineering techniques are less important. Things like priming representations (a special kind of summarization) and re-prompting get less important as long as the model is capable of accurately recalling from big short-term memories.

Conversation history is meaningful. You can discuss bigger topics, from thousands of lines of code to entire books.

Reasoning gets better. Bigger memory means providing more context, greater explanations, and more nuance.

And what models can be used for changes, too. A model that has a short-term memory equivalent to an hour's conversation is useful for short conversations. If you tried to do something like therapy with it, it'd be unhelpful. It would keep forgetting what happened in the last therapy session.

IMPORTANT WARNINGS: Never use AI for therapeutic purposes without the supervision of a qualified human healthcare practitioner. Never use AI with healthcare data in an unsecured environment.

A model that can remember the last 75 hours? That's a year's worth of therapy sessions. If you're working in a secured environment, a human therapist could summarize the last 25 therapy sessions, big picture, and quickly get suggestions and guidance. Given the caseload a lot of therapists are carrying these days, that would be a handy tool if properly secured and administered.

As much as other technologies are advancing on the AI front, like AI agents, the ever-expanding short-term memory of models is a HUGE deal that's worth paying attention to. It's changed how I use AI, enabling much bigger projects and tasks than previously possible.

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

AI isn't just for marketing. It might save your rights.

Here's an example. Tennessee is contemplating the ELVIS Act to allow people to sue and pursue penalties if someone misuses their likeness with tech like AI.

Sounds great, right? Except that the current legislation is a bit vague - and vague legislation leads to unintended consequences. I fed the bill text into Gemini and asked it to summarize it, interpret which parts were vague, and then asked it the money question:

"Speculate on other ways the law could be willfully misused, including and especially disenfranchising already marginalized populations."

Gemini said:

Sadly, even well-intentioned legislation like the ELVIS Act can be turned into a tool of misuse, potentially exacerbating the disenfranchisement of marginalized groups. Here's some speculation on ways this could happen with the Act as currently written:

Selective Enforcement: Laws protecting likeness and voice could be selectively enforced based on race, gender, social status, or political affiliation. Authorities could turn a blind eye towards misuse against marginalized groups, while aggressively using it to curtail their expression or to stifle dissent.

Targeting Political Opposition and Critics: The ability to sue over the use of likeness or voice could be weaponized by powerful individuals or organizations. They could use it to suppress criticism and intimidate those with fewer resources who speak out against them.

Policing Creative Expression: Laws like this could discourage certain types of artistic expression within marginalized communities. Works such as documentaries, satire, and artistic exploration of identity could become risky endeavors, especially for those with less financial power to defend themselves in court.

Can you think of any politicians, past or present, who would be very interested in silencing dissent or targeting critics? I sure can.

This is the power of AI for good. It may not be a lawyer, but it knows enough about the law to help us illuminate it - especially BEFORE something becomes law.

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


When it comes to generative AI, your data is your success.

Data is one of the two things that will separate winners from losers as generative AI continues to evolve. Whoever has more, better quality data will be able to generate more, better outcomes.

Here's a simple example. Suppose you wanted to help someone build a LinkedIn strategy. You could just go and ask a generative AI system to write one. Maybe you would even give it a detailed, multi-paragraph prompt. That's a great start.

But we know LinkedIn's algorithm exists, and critically, the LinkedIn Engineering team has not been shy about disclosing how it works. In technical blog posts, in podcasts, in articles, in academic papers, they've given away all the goods. Pareto multi-objective optimization. Neural network graphs. Embeddings and vectorization. It's all out there.

The difference is, most of us except for the hardcore nerds have not read it.

Generative AI means you don't have to. Yesterday for fun, I took all the interviews, papers, blog posts, etc. I could find from LinkedIn engineering and fed them all to Gemini 1.5. Like Claude 3 Opus, it's one of the few models that can handle MASSIVE amounts of data as an input, and this was a massive input.

Once I did that, I told it to generate a series of protocols - tactics with explanations - for LinkedIn success USING THE TECHNICAL DATA. And it did a marvelous job of that, explaining each tactic and showing me which paper or post it referenced to derive a recommendation.

Spoiler alert: you already know the recommendations. Be active. Provide value. Don't be an ass. I'm sorry not sorry to say that there are no shortcuts or algorithm hacks, and anyone saying there are doesn't understand how machine learning models work.

What's the difference? I had more, better data than the average prompt. If you have a complicated question you want to answer, generative AI may be a tool to help you. Ensure you've carefully read the terms of service if you're working with proprietary, confidential, or sensitive data on the platform of your choice, but answers are now available to you in less than an hour that would have taken you months and months of work to obtain previously.

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

AI is an amplifier. 

Just like every technology prior. 

The wheel amplified our feet. We could travel greater distances, carry more stuff. 

The combine amplified our ability to harvest crops and feed more people.

The Internet amplified our voices. Suddenly everyone could become a publisher, for good or ill. 

Search amplified our knowledge. For any given topic, we suddenly had an outside brain to recall from. 

Smartphones enabled our very selves, creating digital twins online and bringing the online world into the offline one.

AI amplifies our ideas. Skill is less of a barrier to bringing our ideas to life. Our speed of creation is the speed of computation.

All technologies change us. The wheel saved us some back breaking labor. The combine allows us to support more of us. The Internet connects us to people we would likely never have met, at a scale that was impossible for the average person 40 years ago.

Search meant not having to remember things.

Smartphones meant not having to do a whole bunch of things. How many people under 30 outside of the military are skillful with a paper map and a compass?

AI will change us too, in ways we can’t reliably predict yet. But we are already seeing early signs. Immense, unlocked creativity. Accelerated work, higher quality work product. Layoffs and fee cuts. Deep fakes and disinformation.

All technology amplifies us. It makes the good into great and the bad into worse. AI is a huge leap, as huge as the Internet itself - and we have only to look at the last 30 years to see how that technology remade the world. It too made the good into great and the bad into worse.

What will the world of 2054 look like? No idea, but no one had any idea what today would really look like in 1994 except to say that this world is dramatically better AND worse.

The difference is, for many of us, we were not in charge in 1994. We are today. And big or small, we each play a part in laying the foundations now for what 2054 will look like.

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

In this week's In-Ear #Insights (the @TrustInsights #podcast) @katierobbert & @cspenn discuss the impact of AI on empathy. Can tech be compassionate? Should it be? Learn how we can shape the future of AI with ethics at the forefront. #AI #GenerativeAI #Ethics #Tech #Society

#ICYMI In this week’s episode of So What? John Wall, Christopher Penn, and Katie Robbert walk through the best ways to use generative AI to find marketing opportunities in your data.

Subscribe to our YT channel so you never miss an episode! https://lnkd.in/eZM2YWJk

#GenAI #Marketing #Business #Data #Analytics

#ICYMI In this week’s episode of So What? Katie Robbert, John Wall, and Christopher Penn discuss how to document your process in your agency to find efficiencies with generative AI.

Subscribe to our YouTube channel so you never miss an episode! trustinsights.ai/youtube

#GrowingYourBusiness #Marketing #BusinessConcepts #GenerativeAI

In this episode, you’ll learn:
-how to use the 5P framework to gather requirements
-how to extract insights from generative AI using your ICP
-how to identify marketing opportunities from your own data sets

Join our weekly #email newsletter:
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Discover how Foxwoods Resort Casino achieved a 29% increase in gross revenue with predictive analytics. Our latest case study reveals the power of data-driven decision-making and targeted marketing.

🔎 Why You Should Read:
- Learn successful strategies for boosting revenue.
- See how predictive analytics can transform your business.
💡 Partner with Trust Insights to unlock your business’s potential and drive revenue growth.
📥 Download the case study now and take the first step towards your success story: https://lnkd.in/eDfNAEuD
#PredictiveAnalytics #RevenueGrowth #CaseStudy #TrustInsights #DataDriven #SuccessStory

trustinsights.ai • 1 min read

Case Study: Predictive Analytics for Revenue Growth - Trust Insights

I have a question for you about the behavior of those around you - at home, at work, in your day to day life.

For the purposes of this poll, empathy is the ability to understand and share others’ feelings from their perspective. 

(Versus sympathy which is understanding and sharing others’ feelings from your perspective)

#empathy #emotionalintelligence

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