Write a why-people-buy document from the calls that closed

1. The case: the buyers' words, put back into the selling

It is offered as a very recent case study. One business used AI to analyze a great many of its sales calls, hunting for the pain points. It studied the people who bought and the patterns in the language they used at the moment they made a purchase, then pulled out the phrases they used. Those phrases went into the ads, a new video sales letter and the sales script. The work was summed up in a document on why people buy from them.

What followed, reportedly, showed up across the board: more leads were reached, more calls were booked, and inbound revenue rose. The people who came in were of better quality, and they said the ad had resonated with them strongly; it was drawing exactly the people it was meant to draw. This page gives no figure for any of these changes.

That business's sales process reportedly already converted at a pretty high rate before the change, which is why the gain is called pretty significant at that level. The point of the case: however skilled or seasoned you are, there is always more to find, a deeper way. Sometimes you lose the thread because you have not written copy for a while, and coming back to it you just need a refresher. The claim, offered as a guarantee, is that openings like this already sit inside your existing sales process.

The reason for raising it: a gain like that can come simply from changing your words so that they are more accurate. What follows is the shift behind the change.

2. Talk more about the pain than about the promise

The big shift, in that case, was this. The messaging had talked a lot about what people want. What someone wants more deeply is to get out of pain. It had been saying more about the promise and less about the pain, so the business flipped it: more pain, less promise. Which of the two is more motivating and, as a side note, which is more compliant? The answer is pain aversion.

The compliance point. Set the two messages side by side. One says: this is everything that is wrong in your life, and I can help you be rid of it. The other promises how much you will make on the upside. The first, on one reading, is the more compliant. That is a claim, carried here as a reading, not shown. Advertising law, the rules on income claims and ad platforms' own ad rules are not covered on this page.

Where the marketer's mind goes. In a great mood, a marketer thinks upside: scale, big dreams, big possibilities, changing the world. Then comes the question: why does someone buy?

What pain language sounds like. The example buyer is a business owner, who buys because:

• they have not had a vacation in a year;
• they cannot be with their kids while notifications from Slack keep popping up;
• they carry a deep fear that the business will never make money unless they work themselves too hard (meant figuratively);
• they cannot picture a world in which someone else could run it and they could maybe switch off, even on vacation, and be present.

It is not even about leaving. What they want is to put the business down emotionally or mentally, so there is room to relax. Many of the entrepreneurs this page is for, it is claimed, have gone years without a vacation. They might have traveled somewhere in body, yet gone without relief from stress for a stretch that seems to them a decade long, or several decades. That problem, and solving it, is what gets people to buy.

The word for it. Talk about the pain. What motivates a purchase? The answer: deprivation. The bad part, and the move out of pain and on to the good. Making an offer at the point of greatest want is on SOP 57 — Compute the payback period and shorten it, section 5.

3. Three ways to find out why people buy

There are three, in this order, ranked, kind of, as good, better and best: one, two, three.

3.1 The first way: listen to the calls that closed

This is the way in if you have no AI tech team to do the work for you.

• Listen to 20 or 30 calls, and only calls where the person bought. Skip the ones who did not buy.
• On those calls, listen for the words people use about the pains that come up.
• Look for what is consistent across them.
• Start weaving those pains into your messaging: the ads, your video sales letters, and the start of your scripting.

Questions to ask of what buyers say. One practice here asks of the buyer: what they fear, what value they hold to, what they blame, and what they want control over. What people claim to want can differ from what they say on a call. In one example, the ads that brought customers in talked about automating work; on the calls, buyers wanted their internal systems to scale, and to understand why a key team member had left.

A second view: study the lost deals too. One practice here treats lost deals as the best data there is: work out why each one was lost, and read the weaker ads as closely as the winners. The objections from buyers who hesitated, did not buy on the first call, or did not buy the top offer become material for the ads. This section listens only to calls where the person bought; the second view studies the losses as well. This page does not settle which reading is right.

3.2 The second way: reviews, and an AI tool's weighted list

This one is aimed especially at those who run e-commerce companies. Look at reviews; the reviews need not be about your own product.

Then there is the question one practice here puts to an AI chat tool (ChatGPT or any other): it should list the main pain-based motivations behind people's buying. The tool is asked to weight each by how likely it is, as a percentage, to be the primary reason for a purchase. It comes back with a big list.

One way to run it. One practice here hands the reviews, testimonials and call notes to the tool together, and asks it to pull out, quoted exactly and counted by how often each comes up: the pain buyers had before they came to you; what made them start looking; the outcome they got; and how they would describe you to a friend. Then ask where your copy misses, and for the one thing you can say that no competitor can. Tell it to invent nothing, and to say so where the evidence is thin.

Each weight then decides how long your pitch spends on that pain. In the example figures, if one pain accounts for 47 percent of buyers and another for 32 percent, then 47 percent of the time in your video sales letter or sales pitch goes on the first. If only 10 percent buy because of a pain, it gets only 10 percent, a very quick mention in passing. Then, it is claimed, you get that 10 percent lift.

3.3 The third way: transcribe every call and let AI read them

This one fits, probably, businesses that are a little more advanced.

• Take all of your sales calls.
• Transcribe every one; most sales recording tools already transcribe.
• Let the AI analyze them and reach those conclusions itself.

Quick checks beside the three ways. One practice here adds these:

• Ask your last ten customers the main reason they bought, and use their exact words, in quotes, as the copy. In one example, thousands of messages were tested and none worked; the customers' own quoted words became the best performer. In that view, an AI tool sometimes cannot write your best ad; it can only analyze the data you already hold.
• Record yourself talking about the business, the way you would to a friend, and keep that wording. Owners, in that view, explain their business far better on a call than their ads do.

4. Write it down: why people buy

Make a document and title it why people buy our [what you sell], for example our HVAC services: a Why People Buy document for whatever your thing is. Then put it to work across the whole of your sales process.

The places named along the way: ads, video sales letters and the beginning of the script (the first way); the share of a video sales letter or a pitch each pain gets (the second way); and, at the close, the whole sales process. In the case in section 1, the phrases went into the ads, a new video sales letter and the sales script.

5. What this page does not decide for you

• Whether the reviews go into the AI tool for the weighted list. In the second way, reviews and then the AI tool's list are named, one after the other. One practice that hands them to the tool together is in section 3.2; whether the weighted list itself is drawn from them: Not established on this page.
• What goes into it. Beyond why people buy, and the pains behind it, what goes in your document and how it is laid out: Not established on this page.
• How far the results moved. This page gives no figure for the gains in the case in section 1.

6. The checklist

Step	What to do
1	For the first way, listen to 20 or 30 calls, only ones where the person bought
2	Note the words buyers use about the pains that come up, and look for what is consistent
3	For the second way, look at reviews, and ask an AI chat tool to list the main pain-based reasons for buying, each with a percentage likelihood of being the main one
4	Give each pain a share of the pitch in line with its weight
5	For the third way, transcribe all your sales calls and let AI analyze them
6	Ask of what buyers say: what they fear, what they value, what they blame, what they want control over
7	As quick checks, ask your last ten customers the main reason they bought, and record yourself explaining the business; keep both wordings
8	Write a document titled why people buy our [what you sell]
9	Give the pain more of your words than the promise
10	Put what you find into your ads, your video sales letter and the start of your script, and use your document across the whole sales process

7. Where this sits

• Using their words rather than yours, with the case of a team that had AI review all its sales calls for the pains that came before a purchase: SOP 195 — Put the marketing principles ahead of the tactics, section 5.
• A first script made out of closed calls, which you transcribe and hand to a GPT: SOP 238 — Open every call the same way and keep the script short, section 5.
• Who your best customers are, and what they did before and after buying: SOP 219 — Find the right customers, screen for them and capture data, sections 3 to 5.
• A pain-driven hook, as the kind that people who know they have a problem typically respond to: SOP 118 — Write hooks for each level of awareness, section 4.
• Building your video itself, with pain among the parts of its opening: SOP 207 — Build a video sales letter. Where your video goes before each conversation: SOP 247 — Put a video sales letter before every conversation.
• Raising pain on the call before the ask: SOP 239. The pain cycle: SOP 240.
• Reading won and lost calls for the objections to drill: SOP 108 — Drill a team on closing, section 3.

8. What this page does not cover

The best-customer profile is SOP 219, sections 3 to 5. Making a video sales letter is SOP 207. The pain questions on a live call are SOP 239 and SOP 240. Advertising law is not covered on this page.