Sample AI Customer Report
See what a paid AI Customer Report looks like.
This sample shows an AI Customer Report for Solahart, using the customer job: “Get a quote for solar panels for my home.”
We ran the same job across Solahart, Origin and SolarQuotes to see what an AI agent could find, understand, choose and actually do.
This is a sample of the A$195 + GST AI Customer Report. No live quote or enquiry was submitted.
The customer job
Get a quote for solar panels for my home.
What the customer needed
- Start a quote Can the agent find and start the solar quote process?
- Provide the details Can the agent provide the information needed to progress the quote?
- Reach the final step Can the agent get through the process to the point where a real customer would submit the request?
Prepared for
SolahartRace summary
Find → Understand → Choose → Act
Origin
DivertedSolarQuotes
Reached last stepEvidence trail
What the agent encountered
Comparison
| For this job | Solahart | Origin | SolarQuotes |
|---|---|---|---|
| Start a quote | ✓ | ✓ | ✓ |
| Provide the details | ✓ | No | ✓ |
| Reach the final step | ✓ | No | ✓ |
In this race, all three businesses provided a path towards a solar quote, but the journeys worked differently. Solahart kept the journey on its own site and reached a robot check. Origin handed the quote journey to SolarQuotes. SolarQuotes allowed the agent to progress to the final submission stage.
This does not tell us which business has the best website overall. It tells us what happened when one agent attempted one commercially relevant customer job.
Findings
1. Solahart reached a robot check before submission
What we observed. The agent found Solahart’s solar assessment, completed the available fields using dummy details and reached a reCAPTCHA before submission.
Why it might matter. An AI agent cannot independently complete this path if human verification is required. Whether this represents a meaningful commercial issue depends on how customers and agents actually use this journey.
What we’d look at next. We would check how important this online quote path is to Solahart, how often customers reach this point, and whether agent-assisted enquiries are commercially valuable before recommending a change.
2. The initial Solahart form collects limited quote information
What we observed. The first Solahart form asked for name, email, phone and postcode. It did not ask for further household details on that page.
Why it might matter. That may be enough for Solahart’s process after submission, or it may not. We do not know what they collect later, or what their sales process needs. SolarQuotes asked for more before the last step. That is a difference, not proof that Solahart is missing something.
What we’d look at next. We would ask what information Solahart actually needs to quote, and whether any of it belongs on this first form.
3. Origin hands the quote journey to SolarQuotes
What we observed. Origin’s solar quote page directs customers to SolarQuotes for the next stage.
Why it might matter. This means the transactional part of the journey happens outside Origin’s website. This could be intentional and commercially sensible.
What we’d look at next. We would want to understand the commercial relationship, customer hand-off and desired outcome before treating this as a problem.
Where we’d look first
The most interesting point in this race is the final part of the journey.
Solahart kept the quote journey on its own site but the agent encountered human verification before submission. Origin deliberately moved the journey to another provider. SolarQuotes allowed the agent to reach the final submission stage.
Before changing anything, we would want to understand how important these journeys are commercially, how real customers currently use them, and what role AI-assisted customers are likely to play.
The Race tells us where to look. It does not automatically tell us what to build.
Is there something worth investigating?
Yes. The race found a clear point worth investigating.
An AI agent could find Solahart, understand the quote journey and progress through most of it. The interesting question is what happens at the final stage, and whether improving agent access there would create meaningful commercial value.
We would validate this against real customer behaviour and the importance of online quote enquiries before recommending investment.
One race is evidence from one run, not a complete assessment of the business.
Need to look more broadly?
An AI Customer Report looks at one customer job.
A Useful Machines Review looks across the wider customer journey and the business behind it.
We work with you to understand how customers find, compare, choose and do business with you, where AI could genuinely help, and what is actually worth investing in.
Review A$1,950 + GST. Report fee credited if you book within 30 days.
Talk to usGet your own AI Customer Report
See what happens when an AI agent tries your site.
We’ll run one real customer job across your business and two competitors, show you what the agent encountered, and identify where we think it is worth looking more closely.
AI Customer Report · A$195 + GST
One customer job. Three sites. Evidence from one race. We use dummy customer details and stop before submitting a live quote, booking, enquiry or payment.