How a Data-Centric Product Playbook Keeps AI Marketing Aligned
- Chris McLellan
- Oct 3
- 5 min read
Updated: Oct 4
Capturing product research and frameworks in a concise multi-tabbed spreadsheet is a powerful way to fuel AI marketing and turbo-charge deliverables while reducing informational drift and document chaos.
At a Glance
Product Marketing is critical for aligning product, marketing, sales, and customer success teams, but it often produces scattered PDFs, slides, and documents that go unused. The result is wasted effort and poor alignment.
This post introduces a data centric Product Playbook captured in a spreadsheet format that serves as a consolidated and collaborative knowledge base.
Unlike scattered documents that often duplicate or conflict key information, a spreadsheet-based Product Playbook is a consistent, collaborative source that is readily usable by Generative AI tools such as ChatGPT Projects, NotebookLM, and Custom GPTs.
By structuring Product Marketing research and frameworks in one place, the playbook makes it easier for AI to generate accurate deliverables including campaign plans, growth initiatives, customer journey maps, product launches, and content drafts.
In short, a data-centric Product Playbook template like the one developed by Chris McLellan at Friends Electric, the AI marketing consultancy, transforms fragmented Product Marketing docs into structured tables that teams can collaborate on and AI systems can act on, enabling faster execution, stronger alignment, and better business outcomes.
Too Many Documents, Not Enough Action?
At its core, Product Marketing drives go-to-market strategy for a specific product, product line, or category. It acts like a compass, aligning product, marketing, sales, and customer success teams around a shared objective, ensuring what is built meets real market needs, resonates with buyers, and drives outcomes like product-market fit, product launches, demand-gen campaigns, pricing, and sales enablement and training.
It’s also one of the most analytical and customer-centric disciplines in the marketing function.
Despite its name, Product Marketing is less about the product itself and more about developing a deep understanding your customers (you know, the frustrating, fallible, and sometimes irrational humans who buy your products) through research frameworks such as personas, value propositions, objection handling, and jobs to be done (JTBD).
I think of Product Marketing like a Rubik’s Cube, where each turn moves you forward, and each side represents a key aspect of the customer experience. The more sides you solve, the clearer the full picture becomes.
But it comes with a cost: Doing it well requires time, coordination, and resources.
As a result, it can represent a "bridge too far" for many marketing teams. They know they should be doing it, but unless there's someone with "Product Marketing" in their job title, it often gets neglected or executed only in bits and pieces, here and there.
This isn’t just anecdotal. Marketers today are dealing with a tsunami of operational data, yet according to a 2024 survey by the Content Marketing Institute, 35% say their content isn’t even data-driven, and nearly 40% admit it isn’t aligned with the customer journey.
That disconnect is exactly the problem I set out to solve by developing a template for a data-centric Product Playbook.
The Data-Centric Product Playbook
By incorporating a data-centric mindset, marketing teams can compound efficiencies and scale outcomes. This approach is particularly useful for startups and small businesses, where a single marketer (or a very small team) is often responsible for everything from content, branding, advertising, events, customer experience, and more.
A Product Playbook captured in a spreadsheet helps turn deep strategic thinking on Product Marketing into a compact and versatile source of information for multiple customer-facing use cases, including AI marketing
By working hands-on with clients, I've been iterating on a spreadsheet template for a Product Playbook to help make these assets simpler and more useful, particularly in an AI marketing context.
I started by employing the ROSES prompt framework to create a Custom GPT on what the tabs and columns in this worksheet would look like.
The result is a multi-tabbed spreadsheet that captures the full-range of Product Marketing information in a compact format.
The result is a unified marketing knowledge base designed for simple management and team collaboration while allowing Generative AI systems to easily understand and act on the insights it contains.
Analysis Without Action = Growth Paralysis
In a perfect world, every marketing team would have the time and resource to connect their dozens (or even hundreds) of SaaS apps to a Data Warehouse or CDP and generate actionable reports and insights.
But that's a situation enjoyed by relatively few marketers; mainly those working in enterprise environments.
One way we can start to bridge the gap is to pair smaller more nimble data assets like Product Playbooks with Generative AI to scale deliverables without escalating budgets or workloads.
There's a long list of marketing deliverables that can be enhanced and accelerated by adding the Product Playbook to the knowledge base of Generative AI tools like NotebookLM, ChatGPT Projects, and Custom GPTs:
Growth Initiatives
Product Launches
Campaign Plans
Content Calendars
Event Plans
Pricing Plans
Sales Training Decks
Product Guides
Customer Journey Maps
Product Video Scripts
Drafts of Content (posts, ads, scripts, landing pages)
What's Inside the Data-Centric Product Playbook
My Product Playbook template is a Google Sheet that includes tabs for the following research and frameworks:
GTM Checklist
Product 360
Positioning 360
Persona 360s
SWOT
Competitor Intelligence
Market Intelligence (via news, reports)
Customer Insights (via Customer Feedback Loops)
Channel Insights (via app analytics)
Customer Journey Maps
Jobs To Be Done
Objection Handling
Value Propositions
Messaging Framework
Hooks and Storylines
It's like an "informational stock cube" that's packed with insights and ready to be dropped into any marketing recipe to add context, depth, and guardrails.
I've been using it with clients to support their ongoing marketing function and the response has been consistently positive.
Single Source of Product Truth
A spreadsheet-based Product Playbook works best as the single source of truth because it is structured, collaborative, and AI ready. But not every audience wants to work in spreadsheets.
Executives prefer narrative documents, sales teams need training decks, and external partners expect polished PDFs.
By keeping the playbook in a spreadsheet and then using Generative AI to create doc or slide versions, you maintain one consistent master while producing tailored formats for different use cases, without duplication or conflict.
Collaboration For The Win
If you’re using AI tools for Product Marketing and not feeding it structured information from a Product Playbook, in my opinion, you’re leaving productivity gains on the table. That said, a key challenge with any data-centric undertaking is keeping it up-to-date.
Some tables (e.g. Positioning, Personas, Messaging) require only quarterly or annual updating. But others, such as Competitor Analysis and Customer Insights, can benefit from weekly or even daily updates.
One way to manage this is to open up the tables for comments from teams with a vested interest in improving the customer experience, such as BDRs, account managers, customer success reps, customer support reps, and finance.
But however you approach it, structured inputs = better outputs.
Every time.
I’m Chris McLellan
I’m a Certified Chartered Marketer and the Principal at Friends Electric, my personal marketing consultancy that combines foundational marketing, product marketing, and AI marketing approaches to help marketing teams and businesses do more with less and punch above their weight.
Get in touch if you'd like a guided tour of the template and how I use it to accelerate marketing outcomes. 👍
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