Almost Timely News: How To Pilot an AI Deployment (2023-10-08) :: View in Browser
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What’s On My Mind: How to Pilot an AI Deployment
This past week, I had the pleasure and the privilege of speaking at the MarketingProfs B2B Forum in Boston, Massachusetts. One of the questions that consistently comes up time and time again when I’m doing my talk about artificial intelligence is how to get started using artificial intelligence, how to pilot an AI project. So today let’s look at the three-step process for piloting an AI project at your company, organization, or team.
Step 1: Understand The Use Case Matrix
The first part of developing a pilot project for AI is having an idea of even what kinds of tasks you’d want AI help with. You can’t undertake a pilot successfully if it’s solving a problem no one has; solutions in search of a problem never go well. So let’s start here, with the Use Case Matrix:
What have here is a straightforward matrix with two axes – internal vs external, and innovation vs optimization. First, internal vs external: for any given task, is it internal or external, meaning within your organization or customer-facing? This is an important consideration because, at least when it comes to AI, customer-facing tasks tend to be higher priority and the aversion to risk is (sensibly) higher.
Second, innovation vs optimization: for any given task, is the task one in which you want to make incremental optimizations, or something net new? For example, if you’re an insurance company, a large language model that can answer customer questions would be innovation; a large language model to scan in claims and categorize them for speeding up claim prioritization would be an optimization.
Think through all the problems that your company is facing right now, and see where they fit in. For example, the other week, Katie and I were discussing some shortcomings in Hubspot’s built-in reporting. I used ChatGPT’s code generation capabilities to write new code that performed the reporting tasks exactly the way we wanted them done. That is an example of an optimization that’s internal. Customers won’t see it, and it’s not breaking new ground, but it does make an existing internal process much better.
Sit down with your stakeholders and jot down all the processes which are problems you face with your company onto this 2×2 matrix so that you can start to assess which ones AI could help you with.
Step 2: Understanding The Use Cases
One of the challenges of artificial intelligence, particularly generative AI, is that generative AI uses language and imagery. In turn, that means any task which uses language and imagery could potentially be a task suited for generative AI. Think about it for a moment. Can you name a single function in your company that does not use language or imagery as part of the core tasks that you perform? I certainly can’t.
So a part of the challenge of determining where to pilot AI is to look at the categories of use cases for generative AI. I break them up into six broad categories: generation, extraction, summarization, rewriting, classification, and question answering. Let’s talk through these relatively quickly.
Generation is very straightforward. Everyone understands generation; write me a blog post, write me an email, create an image of a dog on a skateboard – generation is intuitive for us and doesn’t require a lot of explanation.
Extraction is the process of taking data out of provided data. For example, if I give a generative AI system a PDF that has some tables in it, I can use large language models to extract those tables from the PDF and convert them into a CSV file for Microsoft Excel.
Summarization is when we take big text and turn it into small text. Take a transcript from a conference call and extract out the meeting notes and action items, take a long YouTube video and convert into a bullet point summary, etc. We summarize things all the time and language models are capable of summarizing things quickly, and very capably.
Rewriting is equally straightforward. Take this English language paragraph and rewrite it in Swahili, explain the concept of quantum superposition in terms of pizza, convert this profanity-laced diatribe into a professional memo – that’s rewriting.
Classification is when we apply language models to understanding a body of text and what categories it fits into. Think about a pile of blog posts from your company blog; a large language model could automatically assign topics and categories for every post so you wouldn’t have to do that manually.
Finally, question answering is when we ask language models questions from a body of knowledge we want answers to. For example, imagine loading up an RFP response to a language model and then asking it the five conditions you care about most, and whether or not the RFP meets those conditions. That’s question answering.
Once we understand the core use case categories, we can examine all the ways we’d like to apply AI and see if the tasks which make up our use case fit in these categories or not. This is an essential step because it helps us to understand whether generative AI is the right fit or not; if a task doesn’t fit in one of these six use case categories, either you haven’t broken down the task enough into its component tasks, or you have a task that isn’t suited for generative AI.
So you would take the results of your 2×2 Use Case Matrix, and then tag each of the tasks with one of the six use case categories. If a task doesn’t fit into a use case category, then AI probably isn’t the right choice and it should be removed from the matrix.
Step 3: Applying User Stories
Once you’ve laid out your use cases from your matrix and tagged each use case with which of the six use case categories are the best fit, the final step is to assess priority. Assessing priority isn’t just a gut feeling; we want to clearly articulate the use case’s solution so that the priority becomes evident. We do this through user stories.
Here’s the basic template for a user story:
As a {role} I need to {task} so that {result}.
In the example above, Katie’s user story would be:
As a CEO, I need to know what prospects in our Hubspot CRM haven’t interacted with us in 30 days so that I can commission an outreach process for reactivating prospects to increase the sales pipeline.
In this user story, it’s clear what the ask is, what the outcome is, and how the outcome matters to the company. This use case is all about revenue generation, and it would be wise for us to prioritize if it we want more sales pipeline.
Your next step would be to write out clear user stories for each of the tasks in the Use Case Matrix, as clearly as the one above. We want that clarity so that we can prioritize and organize all the ways we COULD use AI into a coherent list of what we SHOULD use AI to accomplish.
The final step in this example would be for the stakeholders to review all the user stories in detail and decide, based on what those stories focus on, which tasks you should pilot AI with first. If you follow these steps, you’re much more likely to see positive and meaningful results from generative AI than if you just wing it or create solutions in search of a problem.
And shameless plug, my company, Trust Insights, does exactly this kind of evaluation for companies. From basic strategic consultation to workshops to having us sitting in the room with you, guiding you through more advanced versions of this exercises, if you want help with this, let us know.
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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 piece on how generative AI will reshape marketing.
- You Ask, I Answer: How Generative AI Will Reshape Marketing?
- You Ask, I Answer: How Will AI Impact Direct Mail?
- You Ask, I Answer: Advice for Print Companies in the Digital Age?
- Almost Timely News, October 1, 2023: How Large Language Models Work
- You Ask, I Answer: Who To Hire For Large Language Models?
- Now with More Large Multi-Modal Models, and Taylor Swift
- In-Ear Insights: Generative AI Governance Strategies for Leaders
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.
Premium
- π Google Analytics 4 for Marketers
- π Google Search Console for Marketers (π¨ just updated with AI SEO stuff! π¨)
Free
- βοΈ 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
Advertisement: Bring My AI Talk To Your Company
πΊ Click here to watch this ad in video format on YouTube
I’ve been lecturing a lot on large language models and generative AI (think ChatGPT) lately, and inevitably, there’s far more material than time permits at a regular conference keynote. There’s a lot more value to be unlocked – and that value can be unlocked by bringing me in to speak at your company. In a customized version of my AI keynote talk, delivered either in-person or virtually, we’ll cover all the high points of the talk, but specific to your industry, and critically, offer a ton of time to answer your specific questions that you might not feel comfortable asking in a public forum.
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“No kidding, this was the best hour of learning or knowledge-sharing I’ve had in my years at the Firm. Chris’ expertise and context-setting was super-thought provoking and perfectly delivered. I was side-slacking teammates throughout the session to share insights and ideas. Very energizing and highly practical! Thanks so much for putting it together!”
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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.
- Digital E-Commerce Analyst at Holland America Group Careers
- Ecommerce Analyst at Henry Schein
- Marketing Assistant at Henry Schein
- Omnichannel Customer Marketing Manager at Henry Schein
- Scrum Master Business Analyst at Holland America Group Careers
- Senior Engineer – Marketing Platform at Confused.com
- Senior Ppc Manager at Confused.com
- Senior Social Media Executive at Confused.com
- Staff Data Engineer at Crisis Text Line
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
- How To Create A Social Media Marketing Strategy In 11 Steps
- Organic vs. Paid Social Media: How To Align Your Strategy
- Ethical AI in Social Media Marketing: What Agencies Need to Know
Media and Content
- How Often to Update Website Content (& Best Practices)
- Transparent Labeling for AI-Generated Content
- The Power of Reputation: How PR Shapes Public Trust in Healthcare Institutions
SEO, Google, and Paid Media
- Google Confirms Indexing Bug – New Content Delayed In Search
- Study: Google Update Decreases Search Result FAQs By 37% via Portent
- How to Find & Rank for Bottom of the Funnel Keywords
Advertisement: Business Cameos
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?
πΊ Pop on by my Thinkers One page today and grab a video now.
Tools, Machine Learning, and AI
- Your assumptions can change how an AI bot responds to you, new study suggests
- When Hordes of Little AI Chatbots Are More Useful Than Giants Like ChatGPT
- Artists Are Losing the War Against AI via The Atlantic
Analytics, Stats, and Data Science
- Introduction to HNSW: Hierarchical Navigable Small World
- What are the Data Scientist Qualifications in the USA?
- Retail Season Planning
All Things IBM
- Fertility care provider Ovum Health gives patients information using chat and scheduling tools with IBM watsonx Assistant via IBM Blog
- Common Grounds: Unleashing innovation and growth through partnership via IBM Blog
- Achieve your AI goals with an open data lakehouse approach via IBM Blog
Dealer’s Choice : Random Stuff
- Over 6,100 gaming jobs have been cut in 2023 (so far) via VentureBeat
- Apple’s Talks With Bing & DuckDuckGo Revealed in Google Antitrust Case
- We Finally Have Proof That the Internet Is Worse via The Atlantic
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 Threads – random personal stuff and chaos
- 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
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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:
- Content Jam, Chicago, October 2023
- SMPS AEC AI, DC, October 2023
- Humanize Your Brand, Online, October 2023
- SiteImprove, Online, October 2023
- DigitalNow, Denver, November 2023
- AImpact, Online, November 2023
- Social Media Marketing World, San Diego, February 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
You might also enjoy:
- You Ask, I Answer: Retrieval Augmented Generation for Tax Law?
- Almost Timely News, February 11, 2024: How To Evaluate a Generative AI System
- Mind Readings: Generative AI and Addition vs Substitution of Jobs
- Almost Timely News, Febuary 18, 2024: From Comment to Content
- You Ask, I Answer: Retrieval Augmented Generation vs Fine-Tuning?
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