OnyxAI Studio
AI Operations Review
Lead capture configurator

Countertop Estimate Tool

A premium countertop estimate flow that turns casual website visitors into structured quote requests before the showroom visit.

Countertop Estimate Tool visual system diagram

Proof depth

What this case study proves operationally.

The strongest proof is the workflow shape: what the visitor or staff member gives the system, what the business receives, and what follow-up becomes possible.

What this proves for granite and countertop shops

A countertop buyer rarely arrives with every quote detail ready. A guided estimator can collect material interest, approximate size, edge preferences, sink and backsplash context, and contact information before the shop spends showroom or callback time. The proof is not a final price promise; it is a cleaner intake path.

Expected lead record

The useful output is a structured quote request: contact details, selected material category, project size, upgrade interest, notes, source page, and follow-up status. That record can feed email, Supabase, a CRM view, a callback task, or an internal assistant summary.

First build recommendation

For the 30-day beachhead, the first implementation should be a quote-intake system tied to the AI Operations Review. Reception and internal assistant work can follow after the intake questions, handoff rules, and follow-up process are clear.

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Material options

Page/widget

Embed modes

Quote path

Business role

The Challenge

Countertop shops often ask buyers to call, send a vague form, or visit the showroom before the customer understands surface options, project size, edge details, and upgrades.

The Solution

The estimator gives the shop a branded guided quote path with materials, kitchen size, edge profiles, upgrades, estimate reveal, savings framing, and lead capture.

The Result

The demo shows how a service-business website can become an interactive sales tool, customized to the shop's theme, catalog, pricing boundaries, lead flow, and preferred format.

Stack and service links

The useful details stay connected.

Case studies should feed service pages, and service pages should point back to relevant proof.

Next step

Have a similar operation that needs structure?

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