Almost Timely News: A Marketing Antidote for Large Language Models (2023-04-30) :: View in Browser
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What’s On My Mind: A Marketing Antidote for Large Language Models
This week, let’s talk about a specific aspect of large language models when it comes to marketing. Let’s dig into being notable and whether or not a large language model like GPT-4 knows who you are. Here’s a bit of background. I had the pleasure of guest teaching at Harvard Business School this week at the invitation of my friend and colleague Christina Inge. Christina’s a force in her own right; her marketing analytics textbook is one of the standards for universities to use for teaching analytics to students in America and beyond.
During the class, I mentioned how large language models like GPT-4 and interfaces like ChatGPT and Bing will impact SEO, that they will consume a lot of unbranded search and informational queries. As part of the exercise, we did a quick search for her on Bard, Bing, and ChatGPT. Bing successfully found her, but Bard and ChatGPT came up empty. I’ve done similar tests on myself; Bard assembled a garbled and deeply incorrect version of who I am, while Bing and ChatGPT successfully identify me and my background.
Why? What’s the difference? The difference is in content mass. How much content mass you – yourself, your company, your brand – have determines how well a large language model does or doesn’t know you. This is one of the new battlegrounds for marketers to deal with in the age of conversational AI and generative AI – how well are we known by the machines that will be taking more and more search tasks on?
If you’re notable, the machines know you. They recommend you. They talk about you. In many ways, it’s no different than classical SEO, except that there are even fewer ways to earn referral traffic from large language models than there are classical search engines.
But what if you’re not notable? What if the machines don’t know who you are? Well, the answer is… become notable. I realize that’s a bit oversimplified, so let’s break this down into a recipe you can use. First, large language models are trained principally on text. This can be text in regular content like blog posts, newsletters that are published on the web, and what you’d expect from common text, but it also can include things like Github code, YouTube subtitles, etc.
We know from published papers that the training dataset named The Pile, published by Eleuther.ai, contains a wide variety of text sources:
The common crawl – Pile-CC – contains much of the public web, especially things like news sites. Books3 is a database of published books. YouTube Subtitles, unsurprisingly, is a large corpus of YouTube subtitles. There’s also academic paper sites like ArXiv and tons of other data sources. This dataset is used to train Eleuther.ai’s models like GPT-J-6B and GPT-NeoX-20B as well as the newly-released StableLM model. OpenAI’s GPT models almost certainly use something similar but larger in size.
Do you see the opportunities in here to be found? Certainly, having content on the public web helps. Having published academic papers, having books, having YouTube videos with subtitles you provide – all that helps create content mass, creates the conditions for which a large language model will detect you as an entity and the things you want to be associated with.
In other words, you want to be everywhere you can be.
So, how do you do this? How do you be all these places? It starts with what you have control over. Do you have a blog? Do you have a website? Do you have an account on Medium or Substack that’s visible to the public without a paywall? Start publishing. Start publishing content that associates you with the topics you care about, and publish anywhere you can that isn’t gated. For example, LinkedIn content isn’t always visible if you’re not logged in, so that wouldn’t be a good first choice. Substack? That allows you to publish with no gating. Obviously, be pushing video on YouTube – with the captions, please, so that you’re getting the words published you need to be published.
Second, to the extent you can, reach out and try to be more places. Someone wants you as a guest on their podcast? Unless you have a compelling reason to say no, do it. Someone wants you to write for their website? Write for them – but be sure you’re loading up your writing with your brand as much as you’re permitted. Got a local news inquiry from the East Podunk Times? Do it. Be everywhere you can be. Guest on someone’s livestream? Show up with bells on.
You don’t need to be a popular social media personality with a team of people following you around all day long, but you do need to create useful, usable content at whatever scale you practically can.
The blueprint for what that content looks like? Follow YouTube’s hero, hub, help content strategy – a few infrequent BIG IDEA pieces, a regular cadence of higher quality content, and then an avalanche of tactical, helpful content, as much as you can manage. Again, this is not new, this is not news. This is content strategy that goes back a decade, but it has renewed importance because it helps you create content faster and at a bigger scale.
For example, with Trust Insights, my big hero piece this quarter has been the new generative AI talk. That’s the piece that we put a lot of effort into promoting.
The hub content is stuff like our ChatGPT Prompt Guide.
And our help content are the endless pieces of the blog, podcast, and newsletter. That’s an example of the plan in action. The same is true for my personal stuff. The big talks are the hero content, which are on YouTube. The hub content is this newsletter, and the help content is the daily video content.
Finally, let’s talk public relations. Public relations is probably the most important discipline you’re not using right now, not enough. If you have the resources, you need someone pitching you to be everywhere, someone lining you up for media opportunities, for bylines, for anything you can do to get published as many places as you can be. If you don’t have the resources, you need to do it yourself. But the discipline of PR is the antidote to obscurity in large language models, as long as it’s done well. We know, without a doubt, that news and publications comprise a good chunk of these large language models’ training data sets, so the more places you are, the more they will associate you and your brand with the topics and language you care about.
What if I’m wrong? What if this doesn’t work?
Oh no, you’re literally everywhere and on people’s minds! That’s the wonderful thing about this overall strategy. It works for machines, but it also works for people. Even if it literally has no impact on the machines (it will, because we know how they train the machines), it would STILL benefit you and your business. In fact, focusing on mindshare, on brand, on being everywhere you can be will help you no matter what.
At whatever scale you can afford, be as many places in public as you can be. That’s how you’ll win in large language models, and win in marketing.
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ICYMI: In Case You Missed it
Besides the newly-refreshed Google Analytics 4 course I’m relentlessly promoting (sorry not sorry), I recommend the livestream from this week where we demoed how to fine-tune a large language model like GPT-3.
- So What? Fine-tuning large language models (LLM)
- You Ask, I Answer: Content for Influencer Audiences?
- You Ask, I Answer: Managing Brand Expectations for Influencers?
- You Ask, I Answer: Brand Collaboration Requirements for Influencers?
- You Ask, I Answer: Short or Long Term Influencer Partnerships?
- You Ask, I Answer: Building Partnerships with Influencers?
- Almost Timely News, April 23, 2023: The Dawn of Autonomous AI
- Now with More Turntable Live Music!
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.
- ⭐️ The Marketing Singularity: How Generative AI Means the End of Marketing As We Knew It
- Powering Up Your LinkedIn Profile (For Job Hunters) 2023 Edition
- Measurement Strategies for Agencies
- Empower Your Marketing With Private Social Media Communities
- Exploratory Data Analysis: The Missing Ingredient for AI
- How AI is Changing Marketing, 2022 Edition
- How to Prove Social Media ROI
- Proving Social Media ROI
- Paradise by the Analytics Dashboard Light: How to Create Impactful Dashboards and Reports
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.
- Data Engineer at Canva
- Director, Product Marketing at Datadog
- Director, Social at Figma
- Field Marketing Manager at Datadog
- Growth Manager, Strategy And Insights at Asana
- Head Of Analyst Relations at Asana
- Head Of Corporate Messaging at Asana
- Head Of Global Customer Marketing at Asana
- Head Of Marketing Operations at Dataiku
- Lead Marketing Manager at Asana
- Lifecycle Marketing Manager at 1Password
- Marketing Technology And Operations Manager at 1Password
- Partner Marketing Manager at Datadog
- Senior Business Intelligence Analyst at Canva
- Senior Data Analyst – Product, Features, & Growth at Canva
- Senior Manager, Demand Generation at Datadog
- Senior Marketing Operations Manager at Asana
- Sr Data Scientist at Dataiku
- Sr Seo & Aso Marketing Manager at 1Password
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What makes this course different? Here’s the thing about LinkedIn. Unlike other social networks, LinkedIn’s engineers regularly publish very technical papers about exactly how LinkedIn works. I read the papers, put all the clues together about the different algorithms that make LinkedIn work, and then create advice based on those technical clues. So I’m a lot more confident in suggestions about what works on LinkedIn because of that firsthand information than other social networks.
If you find it valuable, please share it with anyone who might need help tuning up their LinkedIn efforts for things like job hunting.
What I’m Reading: Your Stuff
Let’s look at the most interesting content from around the web on topics you care about, some of which you might have even written.
Social Media Marketing
- TikTok Shares Key Creator Collaboration Tips for Brands in New Guide via Social Media Today
- Could Bluesky Supersede Twitter as the Key Real-Time Social App? via Social Media Today
- Publishers pull marketing budgets away from Twitter under Musk‘s ownership, changes to verification via Digiday
Media and Content
- A Home-Run for Humanizing B2B Content: Why Generative AI Can Only Get Your Business to First Base
- Decision distress: Drowning in data, business leaders are struggling to steer companies in the right direction via Agility PR Solutions
- EU sets deadline for Google, Meta, Twitter, Amazon, Bing, TikTok and more to comply to DSA content regulation rules via IT World Canada News
SEO, Google, and Paid Media
- What Are E-E-A-T and YMYL in SEO & How to Optimize for Them
- Eco-Friendly Search Engines: Making A Difference One Search At A Time
- 2023 Forecast: SEO & Content Marketing Trends
Advertisement: Google Analytics 4 for Marketers (UPDATED)
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What makes this different than other training courses?
- You’ll learn how Google Tag Manager and Google Data Studio form the essential companion pieces to Google Analytics 4, and how to use them all together
- You’ll learn how marketers specifically should use Google Analytics 4, including the new Explore Hub with real world applications and use cases
- You’ll learn how to determine if a migration was done correctly, and especially what things are likely to go wrong
- You’ll even learn how to hire (or be hired) for Google Analytics 4 talent specifically, not just general Google Analytics
- And finally, you’ll learn how to rearrange Google Analytics 4’s menus to be a lot more sensible because that bothers everyone
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If you already signed up for this course in the past, Chapter 8 on Google Analytics 4 configuration was JUST refreshed, so be sure to sign back in and take Chapter 8 again!
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Tools, Machine Learning, and AI
- Embracing AI Skills Amidst Job Market Turbulence
- AI for security is here. Now we need security for AI via VentureBeat
- Exploring the 2nd order effects of generative AI in marketing and martech via Chief Marketing Technologist
Analytics, Stats, and Data Science
- Bing Chat To Show Referrer Analytics Data In Coming Weeks
- R tutorials: Learn R programming for data science via InfoWorld
- Unlocking the power of real-time analytics: 5 key considerations via InfoWorld
All Things IBM
- 4 steps to improving your ESG risk management to increase financial performance via IBM Blog
- Sharing a reliable sustainability podcast via IBM Blog
- IBM debuts automated, AI-powered platform QRadar Security Suite to accelerate threat detection and response via SiliconANGLE
Dealer’s Choice : Random Stuff
- Disney sues DeSantis over theme park takeover | AP News
- Zstandard – Real-time data compression algorithm
- Toolkit for Sleep – Huberman Lab
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How to Stay in Touch
Let’s make sure we’re connected in the places it suits you best. Here’s where you can find different content:
- My blog – daily videos, blog posts, and podcast episodes
- My YouTube channel – daily videos, conference talks, and all things video
- My company, Trust Insights – marketing analytics help
- My podcast, Marketing over Coffee – weekly episodes of what’s worth noting in marketing
- My second podcast, In-Ear Insights – the Trust Insights weekly podcast focused on data and analytics
- On Twitter – multiple daily updates of marketing news
- On LinkedIn – daily videos and news
- On Instagram – personal photos and travels
- My free Slack discussion forum, Analytics for Marketers – open conversations about marketing and analytics
Events I’ll Be At
Here’s where I’m speaking and attending. Say hi if you’re at an event also:
- B2B Ignite, Chicago, May 2023
- MAICON, Cleveland, July 2023
- ISBM, Chicago, September 2023
- Content Marketing World, DC, September 2023
- MarketingProfs B2B Forum, Boston, October 2023
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.
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.
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
You might also enjoy:
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- You Ask, I Answer: Google Tag Manager and Google Analytics Integration?
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