INBOX INSIGHTS, October 8, 2025: Lost the Plot on Planning, AI For Data Analysis, Part 1 - Trust Insights Marketing Analytics Consulting

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INBOX INSIGHTS: Lost the Plot on Planning, AI For Data Analysis, Part 1 (2025-10-08)

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We’ve Lost the Plot on Planning- Part 1

I’ve been in a lot of planning meetings lately. And I mean a lot.

Here’s what I’m noticing: everyone’s talking about AI. How to use AI for planning. How AI will revolutionize their processes. How they need an AI strategy.

I get it. AI is powerful. It’s transformative. But somewhere between “We need to leverage AI” and “What’s our AI roadmap?” we’ve completely forgotten to ask the most basic question:

What problem are we actually trying to solve for our customers?

The Planning Problem We’ve Created

Planning has become an internal exercise. We sit in conference rooms (or Zoom calls) and talk about:

Operational efficiencies
ROI metrics
Resource optimization
Process improvements
Technology adoption

These things matter. Of course they do.

But when was the last time you heard someone lead a planning session with: “What does our customer actually need, and how do we make their lives easier?”

Where We Went Wrong

The shift happened gradually. Planning became about:

What we want to achieve instead of what our customers need to accomplish.

How we can work smarter instead of how we can serve better.

What technology should we use instead of what problems we should solve.

And AI? It’s just amplified this problem. Now we’re adding another layer of internal focus: “How do we use AI in our planning?”

Why This Matters Right Now

Here’s the thing: when planning becomes disconnected from the end user, a few things happen:

You build things nobody wants. You’ve optimized processes that don’t actually address customer pain points.
Your team loses direction. Without a clear customer-focused purpose, every priority feels equally important (which means nothing is actually a priority).
You waste resources. All that efficiency you’re planning for? It doesn’t matter if you’re efficiently building the wrong thing.
You miss opportunities. While you’re focused inward, your customer is telling you exactly what they need—and you’re not listening.

The Real Cost of Complicated Planning

I see organizations with 47-slide strategy decks. Detailed roadmaps that require a decoder ring. Planning frameworks so complex that no one can remember them, let alone use them.

And at the end of all that planning? Teams still don’t know what to do on Monday morning.

Meanwhile, the customer is still struggling with the same problem they had six months ago.

Getting Back to Basics

This isn’t about throwing out AI. It’s not about ignoring efficiency or ROI.

It’s about remembering the point of all this planning in the first place: to serve your customers better.

Everything else—the AI, the optimization, the efficiencies—those are tools to achieve that goal. Not the goal itself.

In Part 2, I’ll walk through how to refocus your planning using Trust Insights’ 5P Framework. It’s straightforward; it keeps the customer at the center, and it actually helps your team know what to do next.

Because here’s the truth: simple planning that focuses on your customer will always outperform complicated planning that focuses on your internal operations.

Are you overcomplicating your strategic planning? Reply to this email or join our free Slack group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss scaling Generative AI past basic prompting and achieving real business value.

You will learn the strategic framework necessary to move beyond simple, one-off interactions with large language models. You will discover why focusing on your data quality, or “ingredients,” is more critical than finding the ultimate prompt formula. You will understand how connecting AI to your core business systems using agent technology will unlock massive time savings and efficiencies. You will gain insight into defining clear, measurable goals for AI projects using effective user stories and the 5P methodology. Stop treating AI like a chatbot intern and start building automated value—watch now to find out how!

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we took a surprising tour through the complex world of Microsoft Copilot. Catch the episode replay here!

This week on So What?, we’ll be investigating whether your data is AI-Ready or not. Are you following our YouTube channel? If not, click/tap here to follow us!

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In this week’s Data Diaries, let’s talk about using AI intelligently with data analysis. We’ve shared many times, including on last week’s livestream, about how tools like Google Colab can execute exceptional data analysis tasks like regression, correlation, and many others.

There’s no functional limit now to the kinds of data analysis you can perform, from basic linear correlation up through gradient boosting to deep learning on your data. But most people aren’t going to do this.

Not because their data doesn’t support it, but because of a far more limiting reason: they don’t know to ask.

A huge part of what makes generative AI so valuable is its scope – its broad knowledge of nearly any field. It knows more about every subject than any living human could, even if it doesn’t know the subject as deeply as a single human expert inside their domain.

That means it’s aware of al the ways we could try to solve a problem, ways we might not even know exist. Recently, I was teaching a workshop on how to use AI for SEO and search marketing, and the topic of keyword analysis came up. I put the sample data into Google Gemini and gave it this prompt along with a keyword list from the AHREFS SEO tool:

Here’s a spreadsheet of some keyword data. Don’t code. Don’t write code. Instead, examine the first couple of rows of the spreadsheet. I’m particularly interested in the relationship between Traffic Potential and the other categorical and continuous variables. Traffic Potential is my dependent variable, my outcome. What statistical, mathematical, or machine learning techniques could give me interesting, action-oriented insights about what might have a causal effect on Traffic Potential? Be wary of collinearity, especially multicollinearity, and be sure to include ways to handle it. Make 3-5 recommendations in descending order of effectiveness for exploring Traffic Potential with different techniques.

What comes back is a fascinating exploration of the statistical possibilities for this data, ways to work with it that we might not have had the vocabulary to even ask for.

I can then take the recommendations into Google Colab to have it write the actual code and provide the analysis.

The key takeaway here is that we can use generative AI to do more than just blindly follow our directions. We’ve talked in the past about the Rumsfeld matrix:

The known knowns. You know what you know.
The known unknowns. You know what you don’t know.
The unknown knowns. You don’t know what you know.
The unknown unknowns. You don’t know what you don’t know.

Generative AI helps us solve for the last, most difficult category – we don’t know what we don’t know, and thus valuable solutions may be out of our reach simply because we don’t know to ask for them.

Almost every AI course is the same, conceptually. They show you how to prompt, how to set things up – the cooking equivalents of how to use a blender or how to cook a dish. These are foundation skills, and while they’re good and important, you know what’s missing from all of them? How to run a restaurant successfully. That’s the big miss. We’re so focused on the how that we completely lose sight of the why and the what.

This is why our new course, the AI-Ready Strategist, is different. It’s not a collection of prompting techniques or a set of recipes; it’s about why we do things with AI. AI strategy has nothing to do with prompting or the shiny object of the day — it has everything to do with extracting value from AI and avoiding preventable disasters. This course is for everyone in a decision-making capacity because it answers the questions almost every AI hype artist ignores: Why are you even considering AI in the first place? What will you do with it? If your AI strategy is the equivalent of obsessing over blenders while your steakhouse goes out of business, this is the course to get you back on course.

👉 Take this course now to become an AI leader

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Where can you find Trust Insights face-to-face?

SMPS, Denver, October 2025
MAICON, Cleveland, October 2025
Generative AI for B2B Marketers, London, October 2025
MarketingProfs B2B Forum, Boston, November 2025
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Imagine a world where your marketing strategies are supercharged by the most cutting-edge technology available – Generative AI. Generative AI has the potential to save you incredible amounts of time and money, and you have the opportunity to be at the forefront. Get up to speed on using generative AI in your business in a thoughtful way with our workshop offering, Generative AI for Marketers.

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