QueryMint/Case Studies/Restaurant Tech Platform
Case Study

B2B Restaurant Tech Platform: 1,200-Keyword Universe and BOFU Engine

FormatEnterprise B2B SaaS
RegionUS Market
EngagementKeyword Architecture + Content
SurfacesGoogle · AI Search
"Clustered our entire keyword universe by funnel stage and shipped a hub-and-spoke architecture in weeks — not a strategy deck that sat on Notion."
1,200
keywords clustered into one funnel-staged universe
Weeks
from audit to a shipped hub-and-spoke architecture
BOFU
a bottom-of-funnel engine built to turn intent into demos

The Challenge

An enterprise B2B restaurant-tech platform had a sprawling keyword universe and no structure connecting it to revenue. Terms were tracked in spreadsheets and strategy lived in a Notion doc, but nothing was shipped — there was no map from a search query to the page that should own it, and no prioritization by where a buyer sat in the funnel.

The Strategy

We clustered the platform's entire ~1,200-keyword universe by funnel stage — top, middle, and bottom — so investment could follow intent instead of volume. From those clusters we designed a hub-and-spoke architecture: pillar hubs for each core topic, supporting spokes for the long tail, and a deliberate internal-linking model so authority compounded toward the pages that convert.

What We Shipped

How We Measured

Progress was tracked against coverage of the funnel-staged universe and movement on bottom-of-funnel terms — the queries tied to demos and pipeline — rather than raw traffic to top-of-funnel content.

Anonymized at the client's request — the engagement is real; the brand name is withheld.

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