Hi Reader,

My website has just over six hundred articles, all new since January of this year.

That may sound like a lot, because it is.

They cover AI adoption and the daily work of architecture, engineering, and construction firms (my ideal client profile).

On a recent call, a prospective client asked how much content a company needs before it can get found through Google and AI chat.

The intent behind the question was whether they needed an overwhelming number of articles before any of this would work.

Here's the thing: there isn't a simple answer.

The number depends on the questions buyers ask before they hire you or buy from you. A company with one focused service may answer its most important questions with 20 pages, while a company with several audiences, services, and complicated buying decisions may need considerably more.

I want to show you how to break this down and find the number of pages and topics that make sense for you.

This is the third issue in my series on getting found through AI chat. In the first issue, I covered where to publish and how to choose a format your team can sustain. Last week, I shared three prompts for turning one transcript into a source note, article briefs, and a plan for the missing information.

Today, we'll build the buyer-question map I use to decide which briefs deserve priority and how much content a company may need. By the end, you'll have a practical map of thirty questions to work from.

Along the way, you (hopefully) will learn a bit and get some reps in using AI to assist in the process.

1/ The questions buyers ask

Start with real questions your team has heard from prospective buyers:

• Where could AI save our team the most time?
• What information can employees safely put into AI tools?
• How do we create an AI policy people will follow?
• Which workflow should we improve first?
• How do we train senior staff without wasting their time?
• How can we tell whether adoption is improving?
• Should we build something custom or use an existing tool?
• Who should own AI inside the company?

Each question can point to a different part of the buying decision. Someone may be naming the problem, comparing approaches, estimating risk, building internal support, or deciding whom to hire.

If your website only describes your services, buyers have very little help with the decisions that come first. AI chat also has less evidence of how your company thinks about those problems.

2/ Your buyer-question map

There are many ways to gather the raw material. Pick the one that fits what your company already has. Here are two:

Path 1: The people who talk to buyers

Gather two or three people who regularly talk with buyers. Give everyone fifteen minutes to write down the questions they remember hearing during sales calls, discovery conversations, proposal reviews, and client meetings.

Use the words the buyer used whenever you can. Those words often reveal the decision behind the question.

Path 2: The last few months of calls

If your team records sales and discovery calls, the questions are already sitting in the transcripts. Your team will remember the questions that stuck with them. Transcripts also catch the ones that came up again and again without anyone noticing.

Pull the last three months of buyer calls and let AI do the reading. Check your client agreements and privacy policy first, and strip names and identifying project details if that is what your policy requires.

Copy/paste prompt: Pull the buyer questions out of your call transcripts

You will know the list is working when your team recognizes the questions as ones they have heard on real calls. If the output reads like generic industry questions, either the calls were mostly your team talking, or you pasted the transcripts in without enough context about what you sell.

Group what you found

No matter how you got them, you now have a raw list of questions in the buyer's words. Next, group them into six parts of the buying process:

1. Understanding the problem. What is happening, why does it matter, and what could happen if the company leaves it alone?
2. Understanding the options. What approaches are available, and when does each one make sense?
3. Evaluating readiness. What needs to be true inside the company before the work begins?
4. Comparing providers or tools. What should the buyer look for, and what tradeoffs should they expect?
5. Planning the work. What happens first, who participates, how long might it take, and what tends to go wrong?
6. Measuring the result. What changes should the company expect, and how will it know whether the work helped?

You can hand that grouping to AI as well.

If you tried last week's prompts, place each article brief under the buyer question it answers. If you're joining the series here, you can start with the questions and add source material as you find it.

Copy/paste prompt: Organize the buyer questions

Review the table with the people who talk to buyers. Choose thirty questions based on how often they hear each one, how important it is to the buying decision, and whether it fits a service your company wants to grow.

3/ How much content do you need?

The map gives you a reason for every piece you publish. It shows which buyer questions your website already answers, which answers need work, and which ones are missing.

Suppose you come up with thirty questions. You may already have a strong page for some of them. BUT some pages may need better examples or a clearer answer. Others may overlap enough to need to be combined. And still others may need new source material and a new article.

Once you have the questions, you can count how many pages to keep, improve, combine, or create.

4/ What each page should do

The map also helps you decide what each page should give the buyer.

When someone asks AI a question, it relies on what it can find on the internet (or in its training from the internet) to answer that question.

A clear, well-supported answer gives search engines and AI chat something useful to cite. Some pages can also give the reader a useful reason to continue with you:

• Original research or proprietary data
• A diagnostic or assessment
• A calculator or planning tool
• A detailed comparison
• A template the reader can use
• A case study with enough context to guide a decision
• A point of view grounded in real experience

For example, an article can explain the dimensions of AI readiness. An assessment can then help a leadership team see where its own company stands (see pacemark.ai). The article answers the question, and the assessment helps the buyer apply the answer.

5/ Your publishing plan

After AI organizes the questions, review the table with your team. For each of the questions, record:

• The strongest page you currently have
• The internal source material that could support a better answer
• The person who knows the subject best
• The next action: keep, improve, combine, or create

You can also have AI do this, which is fast and helpful.

Once you have completed those steps, you have the beginnings of a publishing plan. You will know which pages to keep, which ones to improve or combine, what you still need to create, and who can help supply the missing expertise.

In the next and final issue, I'll show you how to make those pages accessible to search engines and AI chat, and how to measure whether buyers are finding them.

As always, reply with your questions. It's complex. But it doesn't need to be complicated. So let me know if there's more you want to know about!

Keep building,

- Dan

P.S. If you want help deciding which buyer questions your company should answer and what content it will take, book an AI strategy call. We can look at what buyers are asking, what you already have, and where to begin.