Buying Committee Mapper

Maps everyone who can say no to a purchase, and what each of them is privately afraid of.

When to run it

Before any campaign aimed at a purchase more than one person has to agree to.

What to feed it

The client's website, two or three competitor sites, a clear definition of the target customer, their review profiles and any published case studies. Optionally, the output of the Positioning Researcher.

What it found

From a recent run on a specialist lender. Company details removed.

1
The people who paid never signed.
The loan was repaid from the beneficiaries' share of the estate, and they didn't have to be asked. One person signed, and a professional adviser chose the lender. The marketing spoke only to the person signing.
2
The biggest competitor was free.
A free government payment scheme is the standard route, and advisers look at it before any lender. The website never mentioned it.
3
The website was talking to people who couldn't buy.
The main product page addressed individuals, but the small print required a professional to be involved. The person who actually decided was barely addressed.

The recommendation was one change, and it would cut enquiries while improving them. Knowing whether that trade-off is right is the part a prompt cannot do.

The prompt

AGENT 2 - BUYING COMMITTEE MAPPER

Run when: before any campaign aimed at a purchase more than one person has to agree to.

Feed it: the seller's website URL. Two or three competitor URLs. A clearly defined target customer segment, or two or three named target customer organisations. Live job adverts from those target customers. Public review profiles and published customer stories. Optionally, the output of Agent 1, Positioning Researcher.

---

You are mapping who can say no to this purchase, and what each of them is privately afraid of. The person who benefits, the person who pays and the person who chooses are frequently three different people, and marketing that addresses only one of them stalls late.

FIRST, DEFINE ROLES BY WHAT THEY CAN STOP.

Do not assume this resembles a software purchase. Test for, and discard where they do not exist:
- the person who benefits from the outcome
- the person who authorises the money
- the person who chooses the supplier
- the gatekeeper who can veto on risk, compliance or regulation
- the introducer or referrer who controls access to the decision
- a party outside the core decision who is consulted only near the end

For each role that exists, give what they are measured on, what triggers them to engage, what evidence they need before saying yes, what they are privately afraid of getting wrong, and what happens to them personally if the decision goes badly.

Then it works through

1
SECOND, WHO SITS OUTSIDE THE BUYING ORGANISATION.
Then it answers one question directly: is the person who pays the person who chooses?
2
THIRD, TEST THE MAP AGAINST PUBLIC EVIDENCE.
Every role is labelled evidenced or inferred, with what would confirm or kill it.
3
FOURTH, NAME THE OBJECTION THAT ARRIVES LATE.
The objections that kill deals at the end are rarely about price.
4
FIFTH, MAP THE CURRENT MARKETING AGAINST THE COMMITTEE.
It recommends one decision, not a content plan.
5
FINALLY.
It flags everything it could not verify, and closes with the questions only an insider can answer.

The full prompt is sent by email. Request it below.

What it got wrong

Corrections found after running this agent on live client work.

1
It mapped the seller instead of the buyer.
Every input described the business doing the selling, but the committee sits with the customer. It now needs a defined target customer, and treats the customer's own job adverts as the best evidence of who owns the budget.
2
It tried to map three products at once.
One company sold three loans, and each had a different committee. The result was a blur. The agent now maps one offer per run.
3
It implied it had checked things it couldn't reach.
Some sources were blocked, but the output read as if they had been reviewed. The agent now lists every source it could not access, and never implies a check it didn't make.
4
It ranked objections by feel.
Two objections could be equally fatal with no rule to separate them. The agent now ranks by how fatal each one is, and where two are equal, the one that arrives later ranks higher.

How I read the output

The first three things I check before trusting what comes back.

1
Check it looked for the payer and the chooser separately.
If the output says one person pays, chooses and signs, it has usually stopped looking.
2
Check the late objection isn't about price.
Deals that die at the end usually die over blame. If price tops the list, the map is too shallow.
3
Check the recommendation costs something.
One decision with a named risk is useful. A list of content ideas means it avoided making the call.

Those are the first checks. The rest depends on knowing who actually signs, which is the part a prompt cannot do.

Have me run this on your business

I'll map who can say no to your sale, find the objection that kills deals late, and give you the one change that moves the most volume.

Or get the full prompt

I'll email you the complete prompt, and let you know when the next agent lands.

Neil HenryFractional CMO, Marketing Converted

I run these agents on live client work first, then publish what needed correcting.