A Practical Way to Connect AI Search Visibility to Local Leads

AI citation clicks account for about 1% to 2% of calls for CallRail's customers, a number that has roughly doubled since January. Sean McCrohan, CallRail's VP of Technology, shared this figure during SEJ Live 's second session on August 26, revising a slide that put growth at 65% over six months in his own presentation.

He and Steve Wiideman, an SEJ contributor advising multi location brands, discussed the gap between what AI assistants are doing for local businesses and what is reflected in reports. Catch the full session for free on demand.

2 Signals Are Trackable, And Both Are Small

McCrohan shared that CallRail has observed a common pattern: people often start their research with an assistant before moving on to a branded search. Interestingly, what you can measure looks just like a typical search, even though the. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

The reporting question is whether this signal changes a decision. If it only creates another number in a dashboard, it adds noise. If it helps separate profile activity, website visits, calls, bookings, and direction requests, it can make local performance easier to understand.

AI Traffic Arrives Later Than Ordinary Web Traffic

CallRail has historically seen that about half of website traffic comes outside regular business hours, according to McCrohan. With AI search, that number rises to nearly two thirds. It's not uncommon for people to start browsing with an. The strategic issue is whether automated visitors can understand, trust, and complete the same journey a human visitor can. Agent readiness is partly technical, but it is also about clear tasks, accessible flows, and reliable evidence.

The risk is usually hidden in the execution layer. A page can look fine to a human and still fail for an automated visitor if the form, call to action, rendering path, or confirmation step is not accessible enough for the agent to complete the task.

Server Side Number Swaps Work, In Browser Swaps Don't

McCrohan points out that giving a separate phone number for an AI crawler instead of Googlebot does work. However, this change needs to be made on the server side, which can be a bit technical. He explains, "The crawlers that AI agents are. Local visibility depends on whether the details across pages, profiles, categories, reviews, photos, and service descriptions reinforce the same answer for a specific location based query. This connects with AI Search Cites Reddit when the same signal needs a clearer operating decision.

The operational question is whether the public business data is complete enough to support the query. Hours, categories, services, reviews, photos, and page content need to reinforce each other so Google can understand the business in a specific situation, not only as a generic listing.

Prompt Libraries Only Work As A Trend Line

Wiideman recommends starting with semantic triples, which are the specific claims a business wants to be recognized for. He suggests putting one in quotes, searching for it, and expecting to find few other sites stating it directly. These. For search teams, the important part is not the headline movement by itself. It is whether the shift changes which communities, forums, video surfaces, or publisher pages now satisfy the query better than the old ranking pattern.

Your Customers' Words Are Already On Your Call Recordings

Call transcripts capture the actual words customers use to describe their problems, which might be different from the words on your website, McCrohan explained. When there's a disconnect between the two, your business might miss chances to. The practical question is what this changes in the system: the page structure, the evidence presented, the measurement habit, or the way the topic is connected to related work.

The practical value is in connecting the idea to an observable signal. That means deciding what should be checked, what would prove the issue is real, and where the team should make the smallest useful improvement first.

Ratings And Reviews Still Feed The Recommendation

Wiideman encourages businesses with multiple locations to train each location to ask customers for reviews on the other platforms they already use, not just Google Business Profile, like Reddit, TripAdvisor, and Yelp. He notes that Yelp. For search teams, the important part is not the headline movement by itself. It is whether the shift changes which communities, forums, video surfaces, or publisher pages now satisfy the query better than the old ranking pattern. A useful companion note is What AI Says About Your Locations, because it looks at a nearby part of the same system.

Governance Beats Ranking Signals At Scale

No matter if a brand has 40 locations or 4,000, Wiideman emphasizes how important it is to have centralized control. The corporate team takes care of the schema, data feeds, and tracked phone numbers, which helps prevent issues like rogue. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

The useful check is whether this improves the system behind search performance, not only the words on the page. Internal links, crawlable content, clear entities, current evidence, and a sensible page structure all help the recommendation become easier to trust.

Looking Ahead

Wiideman expects agents to verify a contact number and offer to make the call, all while the customer never needs to visit the site. Both speakers landed on the same note. "It is an exciting new world, but it is not a 100% new world,". The strategic issue is whether automated visitors can understand, trust, and complete the same journey a human visitor can. Agent readiness is partly technical, but it is also about clear tasks, accessible flows, and reliable evidence.

Join Us For Our Next Webinar!

Introduction AI citation clicks account for about 1% to 2% of calls for CallRail's customers, a number that has roughly doubled since January. Sean McCrohan, CallRail's VP of Technology, shared this figure during SEJ Live 's second session. For search teams, the important part is not the headline movement by itself. It is whether the shift changes which communities, forums, video surfaces, or publisher pages now satisfy the query better than the old ranking pattern.

AI Cites Your Brand. Now What? Turn AI Visibility Data Into Actions

Join Constance Tan of Ahrefs to learn which AI visibility metrics matter, how to prioritize your next steps, and which tactics win more citations in AI answers. The practical read is that brand signals need to be consistent enough for both people and AI systems to form a stable view of the company, its expertise, and its trust signals.

What the visibility signal actually changes

What the visibility signal actually changes: a Practical Way to Connect AI Search Visibility to Local Leads should be treated as a visibility signal, not a standalone headline. Introduction AI citation clicks account for about 1% to 2% of calls for CallRail's customers, a number that has roughly doubled since January. Sean McCrohan, CallRail's VP of Technology, shared this figure during SEJ Live 's second session on August 26,.

What the visibility signal actually changes: the practical question is whether the page, brand evidence, and surrounding content make the answer easier to trust. If that support is weak, search systems can still understand the topic but fail to connect it confidently to the brand. The same pattern also shows up in We Earned 1, where the practical question is how the signal becomes visible.

What the visibility signal actually changes: that is why the response should begin with an audit of the evidence already on the site before creating a new asset. The fastest improvement is often a clearer page, a better internal link, or a stronger explanation of why the brand belongs in the answer.