“Will this work with our existing tools?” “Is it too expensive for a small team?” “Why wouldn't we just use the product we already have?”
Your sales team hears questions like these every week. They're a useful starting point for deciding what to monitor in AI answers, because they describe decisions a buyer needs to make.
The trick is to preserve the need while removing the sales pitch. Turn the objection into a neutral research question, then check whether it belongs in a discovery, comparison, or brand-fact group.
Which objections belong in your question set?
Start with recurring themes in sales notes, support conversations, and lost-deal reviews. Look for the job the person wanted to do, the constraint they faced, and the uncertainty that slowed them down.
You don't need to paste a transcript into a writing tool. A short, anonymized note is usually enough: “Small agencies need client reporting, but worry that setup will take too long.” Remove names, contact details, private budgets, and anything that would identify the customer.
Group similar objections before writing prompts. Ten phrasings of the same setup worry shouldn't automatically count as ten separate opportunities. Give each theme an owner who can explain why it matters to the intended audience.
Some objections belong in product work or sales enablement rather than an AI tracking project. If buyers are reporting a broken integration, fixing it comes before monitoring how an assistant describes it.
Turn the need into a neutral question
A useful discovery question leaves room for an answer that doesn't recommend you. “Why is our platform the best choice?” measures a different task from “What tools help a small agency send client reports?”
Here are three hypothetical transformations:
- Objection: “We don't have time for a complicated setup.” Question: “What should a small agency consider when choosing a client reporting tool that's easy to set up?”
- Objection: “We need this to work with our CRM.” Question: “How can a marketing team connect client reporting with its CRM?”
- Objection: “Our current software already does some of this.” Question: “When is a dedicated reporting tool useful alongside an existing analytics platform?”
These examples are suggestions for research, not evidence that people type those exact sentences into ChatGPT. Check the wording with sales colleagues and customer language before making it part of a long-term report.
Keep the important constraint. Remove unnecessary detail. A prompt so specific that only your product fits can produce a flattering but unhelpful result.
Separate discovery from questions about your company
Discovery asks what options exist. Comparison asks how options differ. Brand-fact checks ask whether an assistant describes a particular company accurately. Keep those groups apart so one doesn't hide weakness in another.
For example, “Does ExampleCo connect to our CRM?” is a branded capability check. “Which reporting tools connect to our CRM?” is a discovery question. Both may matter, but they answer different business questions.
Add a note beside each prompt explaining its purpose. Record the audience, decision, source theme, and what a useful answer would contain. That makes the question set easier to review when your positioning or product changes.
If you need a refresher on the broader process, our AEO guide explains how content and visibility work fit together.
Define what you'll count before the first run
Decide whether you're checking brand mentions, product recommendations, linked citations, or factual accuracy. Don't treat them as interchangeable wins.
An assistant may cite your educational guide while recommending another product. It may recommend your company but describe a feature incorrectly. Save the full answer so those differences remain visible.
Track the wording, tool, available mode information, date, and relevant language or location settings. Use a fresh conversation for a consistent manual check, and document what your automated method does. Compare like with like.
WildSEO lets teams monitor tracked prompts and inspect stored answers. Its AI share of voice is one way to summarize brand mentions. Read our measurement walkthrough before comparing it with an answer-presence rate or a citation count.
Use the answers to improve a real buying decision
Review the responses by objection theme. If assistants repeatedly misunderstand a setup requirement, check your documentation. If they explain a genuine limitation accurately, improve the product or help buyers understand the tradeoff.
Ask whether the website gives someone enough information to make the decision. A clear requirements page, honest comparison, or tested integration guide may help more than another broad article about the category.
Google's people-first content guidance asks whether readers leave with a satisfying answer. That's a useful editorial test here too: would the person who raised the objection find this page helpful?
Keep reviewing the question set as your business changes. Add newly important needs, retire irrelevant ones, and record changes so the trend remains interpretable. You want a focused view of the decisions that matter, with a clear path from an observed gap to better information for the buyer.
