Objection prompts: the follow-ups that test your brand
Prompts that raise price, trust, fit, switching and support objections with AI assistants, for software and consumer goods. Copy them to test your brand.
Last updated by Vouch
Objections come in the third stage of a buying conversation with an AI assistant. After Discovery and Shortlist, the buyer looks for reasons not to buy. In a Vouch Thread that is the Objection stage, and it is where a brand can be dropped, because the assistant answers from reviews, forums and complaint threads that the brand does not control.
These prompts cover five common kinds of objection: price, trust, fit, switching and support. Use them after a Discovery and a Shortlist question, in the same chat, and point them at your brand or at the option the assistant put first. Note which objection makes the assistant stop naming you and recommend someone else. That follow-up is your killer question: killer questions explains how to find it and what to publish to survive it.
Ask each one a few times, because answers vary from run to run. The methodology explains how Vouch asks these follow-ups for you three times a week, and the buyer conversation prompts cover all six stages.
Price
The buyer questions what the brand costs and whether the price holds up against the alternatives.
Why is it so much more expensive than the other tools you mentioned? Are there hidden costs, like extra users, add-ons or setup fees? Does the price go up a lot after the first year? Is the free plan enough, or will we have to upgrade straight away? Which cheaper tool does most of the same things?
Why does it cost more than the other brands? Is it just the name? Is it ever on sale, or should I wait for a discount? Would a cheaper brand last just as long? What do I actually get for the extra money?
Trust
The buyer asks whether the brand is reliable, honest and well reviewed by people who have used it.
Is the company stable, or is there a risk it shuts down or gets bought? Have they had security problems or data breaches? What do real customers say in reviews, good and bad? Is their uptime reliable, or do users report outages?
Are the reviews for this brand genuine? Does it really last, or does it break after the warranty runs out? Do they honour their warranty without a fight? Is this brand known for quality problems?
Fit
The buyer checks whether the product suits their situation, size, skills or use.
Is it too complicated for a small team without a technical person? Does it integrate with the tools we already use? Is it built for companies our size, or for much bigger ones? Will it work for our industry, or is it made for someone else?
Is it suitable for a beginner, or is it aimed at experts? Will it suit someone of my height and build? Does it work in a small flat with no garage? Is it a good choice for everyday use, or only for special occasions?
Switching
The buyer weighs the effort and risk of moving from what they use today.
How hard is it to move our data across from our current tool? Can we leave easily and take our data with us if it does not work out? How long does it take a team to get used to it? Is it worth switching if our current tool mostly works?
I have always bought the bigger brand. Why should I switch? Can I return it easily if I do not like it? Will it work with the accessories I already have? What would I miss if I switched from my current brand?
Support
The buyer asks what happens after the sale: help, repairs, service and how problems get solved.
How good is their support? Do you get a real person? Do they offer onboarding or training for new teams? What support do you get on the cheaper plans? How fast do they fix bugs that customers report?
Is their after-sales service reliable? Where can I get it repaired, and how long does it take? Can I get spare parts easily? How do they handle complaints when something goes wrong?