Examples of the questions buyers ask an AI assistant before they decide: which option fits what they need, how it compares, whether it is available where they are, and where to buy or book it.
Being found is step one. Being chosen is the job.
People now ask AI assistants for recommendations and comparisons, not just links. Before they decide, they check what fits, what it costs, whether it can be trusted and whether they can actually get it. Miss that answer and you lose quietly. Get described wrongly, or recommended to the wrong buyer, and you lose loudly.
Four things have to go right
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Found
You show up for the questions your buyers actually ask.
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Understood
Your offer is described accurately: what it does, who it is for, what it costs.
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Chosen
You are recommended to the buyers you genuinely fit — and not to the ones you don't.
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Reached
The purchase, booking or enquiry actually works.
What we do
Three parts of one job.
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Find what's in the way
We build a focused set of the questions your buyers bring, from your sales conversations, support and customer research. Then we check how relevant AI answers describe and recommend you today: where you are absent, mis-described, or recommended to the wrong buyer.
- Buyer questions
- Answer baseline
- Priority fixes
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Fix the information behind the answer
On your own site: pages that are easy to access and read, facts that are accurate and consistent, comparisons that answer real buying questions. Beyond it: the independent sources and catalog data those answers draw on — where evidence is missing or wrong, we work out how to earn it or get it corrected.
- Verified facts
- Useful pages
- Evidence gap list
- Clean catalog data
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Make the next step work
A recommendation only counts if the buyer can act on it. We check that the offer fits the buyer and that the route to a purchase, booking, quote or demo works, then review what happened using the analytics you already have.
- Offer & action checks
- Outcome review
- Next priorities
Find the missing piece.
Every recommendation has to survive the buyer’s real requirements.
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The buyer asks
“A charger that can power my 65 W laptop, delivered to my region.”
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What the answer can find
The page says “fast charging” but never states the wattage. And the seller does not ship to that region.
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What we do
Verify the specification and publish it plainly. Check delivery eligibility. If this seller cannot deliver there, look for a channel that can. If none exists, the right answer leaves it out — for that buyer.
- Fixable · unstated wattage
- Not a wording problem · no delivery there
Better wording can fix missing information. It cannot create delivery coverage that does not exist. A recommendation has to fit the buyer, and that is the standard we work to. Same logic for a software plan that lacks a feature, or a service that does not cover an area.
Hands-on work. Clear evidence.
A focused scope, one named lead and an agreed set of priorities. We work alongside your team and write down the decisions as we go.
Scope and baseline
Agree buyers, offer, market and outcome.
Fix the priority gaps
The strongest evidenced problems first.
Verify the changes
Did the answers and outcomes move?
Keep improving
The next work, chosen from evidence.
Three results, reported separately.
What we changed
On your site, in your data, and in the sources we could correct.
What the answers did
How the AI answers we sample describe and recommend you, checked the same way each time.
What buyers did
Qualified enquiries, bookings or sales, read from the numbers you already have.
Each is reported as measured, estimated or not yet known — never blended into one number.
Let's talk.
A first conversation has one purpose: to work out which gaps are worth investigating and what a sensible first scope would be. Bring three things:
- What you sell
- Who should choose it
- Where you want to grow