Use AI to investigate the handoff between a visit and an inquiry
Follow one visitor journey from its original promise through the form and confirmation. Use AI to organize the evidence and choose a focused improvement to test.
A visitor arrives, reads your page, and leaves without making an inquiry. The numbers show where activity changed, but they rarely explain the whole experience. To investigate, follow the path the person was asked to take.
Choose one source, one landing page, and one inquiry route. Collect the wording people see at each step, along with the information you have permission to use. AI can help organize those materials and identify questions worth checking. You remain responsible for deciding what the evidence supports.
Trace the promise through the journey
Start with the ad, search result, post, or referral that brings someone to the page. What does it lead them to expect? Then read the headline, offer explanation, main button, form, and confirmation message in sequence.
In a fictional example, a post invites people to receive a short website review. The landing page describes several services, the button says “Let's talk,” and the form asks for a detailed project budget. Each step could be reasonable on its own. Together, they leave a visitor unsure whether they are requesting a review or beginning a large project.
Give AI a bounded review task
Provide the exact copy and ask for a comparison. Request a table with four columns: the step, the expectation it creates, the evidence visible on the page, and the question that needs checking. Ask it to quote the relevant wording so you can trace each observation.
Fictional practice instruction: Review this sample journey from a website-review post to its inquiry confirmation. Identify changes in the promise or requested effort. Use only the supplied copy. Separate observations from possible explanations. Suggest one change we could test, and say what information is missing.
This creates a reviewable starting point. It does not establish why real visitors left. A confusing phrase is a hypothesis to investigate alongside form behavior, audience fit, device issues, and the quality of the original traffic.
Check the handoff yourself
Read the page on a phone. Follow the main button. Check required fields, error messages, and what happens after submission using your approved testing process. Confirm who receives the inquiry and what the visitor is told to expect next.
Keep test submissions identifiable so they do not become apparent sales leads. Remove personal information before using inquiry examples with an AI tool, and work within the permissions your business has agreed.
Choose one change and one useful measure
You could make the button describe the actual next step, explain what the review includes, or clarify when a person will respond. Choose the change that best addresses the evidence you found. Record the starting state and the date you change it.
Track completed inquiries and whether they fit the service, alongside visits and form starts. A higher number of submissions may still need investigation if fewer are relevant. Allow for small samples and changes in traffic before attributing an outcome to your edit.
The same review can become a recurring team workflow: gather the journey, compare the promise, check the experience, and select a test. Explore Waymaker Agency's AI Teammate Workshop if you want help learning that process with your team. Custom bookings are available; the public cohort currently accepts expressions of interest without an announced date or price.