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Named · with consent

4 to 34 AI-Overview citationson the top 50 commercial queries.

Northern Hydraulics is an industrial hydraulics distributor with ~8,500 SKUs. On the top 50 commercial queries, AI Overviews were citing its manufacturers, not its own pages, so it sat in AI answers exactly 4 times. Six months of product-schema and answer-shaped page work took that to 34 AIO citations (×8.5), making the distributor the citable source instead of its suppliers.

Client
Northern Hydraulics
Scale
~8,500 SKUs
Services
AI Search & GEOCatalog AI
Engagement
2023 · 6 months

  • 4 → 34

    AI Overview citations on the top 50 commercial queries

  • ×8.5

    Growth in AIO citations over the six-month window

  • 50

    Top commercial queries tracked weekly

  • ~8,500

    SKUs covered by the product-schema rewrite

The situation

Where they started.

Northern Hydraulics sells hydraulic fittings, adapters, and assemblies. JIC, NPT, the full lineup. Roughly 8,500 SKUs across 150-plus categories, sold to engineers and MRO buyers. The site ranked fine in the classic blue links. But the engineering queries that used to land on its category pages were getting answered above those links, inside AI Overviews.

On the top 50 commercial queries, Northern Hydraulics showed up in AI Overview responses exactly four times. The citations went to the manufacturers instead. Their spec sheets were the cleanest structured source around, so the engines pulled from them and named them. A distributor sat downstream of its own suppliers in the one place buyers were now reading first.

The constraint

What made it hard.

The manufacturers had the structural advantage by default. Their product data was machine-clean. Northern Hydraulics ran the same manufacturer-supplied descriptions every competitor used, with product schema full of gaps. Engines had no reason to pick the distributor’s page over the source it was quoting from. To get cited, the catalog had to give the engines something better to assemble an answer from than a spec sheet. And it had to do that across 8,500 SKUs, not a handful of hero pages.

What we ran

The work, phase by phase. What shipped, and when.

  1. Months 1–2

    Product schema rewrite

    Full structured-data rebuild across the ~8,500-SKU catalog — product, offer, and spec properties exposed at a depth that gave engines a complete, parseable source at the distributor level.

  2. Months 2–4

    Answer-shaped category pages

    Reworked 150+ category pages so the answer sat up top: direct-answer blocks, spec tables a machine can read, and manufacturer spec data folded in alongside stock, pricing, and cross-compatibility the manufacturer page never carries.

  3. Months 3–6

    Engineering-query answer hubs

    Dedicated hubs for the questions buyers actually type — thread identification, pressure ratings, sizing, JIC-to-NPT conversion — written to be the citable source AI Overviews assemble answers from.

  4. Months 1–6

    Citation tracking from day one

    Tracked the top 50 commercial queries against AI Overview responses every week, watching which pages got named so the next round of work targeted the gaps still going to manufacturers.

This is what a AI Search & GEO engagement at this scale looks like in practice.

Why it worked

The mechanism. What actually moved the number.

AI engines cite whichever page makes the answer easiest to assemble. The manufacturers won because their spec data was structured and the distributor’s was not. The schema rewrite closed that gap, and the answer-shaped pages went one better. They carried the spec data plus the things a manufacturer page never has: live stock, pricing, cross-compatibility, and the application context an engineer is actually asking about.

So when an engine built an answer to a thread-sizing or pressure-rating query, Northern Hydraulics now held the more complete, more citable source. The citations moved from the supplier to the distributor. That visibility is what fed the qualified-lead growth, which is reported on the full-engagement anchor study. This cut claims the AI-search visibility only.

What happened

The results. As measured, dips included.

The shift was gradual, not a step change. The schema work shipped first and citations barely moved for weeks, because engines re-crawl and re-evaluate on their own clock. The slope picked up once the restructured category pages and answer hubs went live and the engines had a better source to pull from. Across the top 50 commercial queries, AI Overview citations went from 4 to 34 over six months. ×8.5.

Some queries stayed with the manufacturers, usually where the question was about a raw spec the manufacturer genuinely owns. Most of the gain came on application and selection queries (sizing, compatibility, identification) where the distributor’s added context made it the better thing to cite. This cut is one part of the full Northern Hydraulics engagement. The qualified-lead growth that visibility helped drive is claimed on the anchor study, not here.

The number that mattered

×8.5

AI-Overview citations, top 50 commercial queries

4 → 34 · 6-month engagement

AI Overviews used to send our buyers straight to the manufacturer. Now the answer cites us, and the engineer who clicks through already knows what they need.
Operations Director, Northern HydraulicsIndustrial hydraulics distributor · ~8,500 SKUs

Measurement notes

How these numbers were measured.

A metric without a source is an assertion. Every number on this page is listed below with how it was counted.

AIO citations 4 → 34
A fixed set of the top 50 commercial queries, checked weekly against live AI Overview responses with a citation tracker. A citation counts when an AI Overview answer names or links a Northern Hydraulics page. Baseline 4 is the month-one actual on that query set, before any schema work shipped; 34 is the six-month read on the same 50 queries.
×8.5
34 ÷ 4 on the identical query set, start to end of the six-month window. Same queries, same definition of a citation throughout — no change to the tracked set mid-engagement.

Attribution. Published with the client’s sign-off. Metrics are as measured in the sources listed above.

Part of a bigger engagement

The rest of the Northern Hydraulics engagement.

  • Full engagement

    Industrial hydraulics distributor~8,500 SKUs

    Named · with consent

    +43.5%

    Qualified leads a month, across the full engagement

    2022 – 2025 · client CRM

    1,840 to 2,640 qualified leads a month. The full-stack rebuild behind it.

    Northern Hydraulics is an industrial hydraulics distributor — ~8,500 SKUs of JIC/NPT fittings, adapters, and assemblies sold to engineers and MRO buyers. Over a three-year relationship (2022–2025) we ran the whole growth function: brand and design, a Magento 1 to headless replatform, AI-search and technical SEO, an AI-assisted catalog rewrite, pillar content, paid ads, and cold outbound. Qualified leads went from 1,840 to 2,640 a month, up 43.5%.

    Full Growth OwnershipWebsite DevelopmentAI Search & GEOEditorial AuthorityOutbound Email2022 – 2025

  • Industrial hydraulics distributor~8,500 SKUs

    Named · with consent

    8,500

    SKUs replatformed off Magento 1

    6 months · schema-complete from day one

    8,500 SKUs off Magento 1, onto a storefront AI can read.

    Northern Hydraulics ran an 8,500-SKU catalog on Magento 1, which hit end-of-life with no security patches and product markup AI search engines couldn't parse. Over 6 months we replatformed the whole catalog to a headless Next.js storefront on Shopify Hydrogen, schema-complete from day one, and carried the JIC/NPT spec quote flow across intact. Mobile category-browse INP dropped from 600ms+ to under 200ms. This was the web-dev cut of the full engagement; the qualified-lead growth is reported on the anchor study.

    Website DevelopmentAI Search & GEO2022

  • Industrial hydraulics distributor~8,500 SKUs

    Named · with consent

    ×2

    Organic sessions from informational & pillar pages

    6-month pillar-and-cluster build

    Pillar content that out-writes the manufacturers. Informational sessions, doubled.

    Editorial cut of the Northern Hydraulics engagement (2022–2025). Over six months, senior subject-matter pillar-and-cluster content on the core fitting categories roughly doubled organic sessions from informational and pillar pages, and pushed Northern's pillars to the top of AI-Overview answers for six category terms the manufacturers used to own. This was one discipline inside the full engagement; the qualified-lead growth is reported on the anchor study.

    Editorial Authority2023 – 2024

  • Industrial hydraulics distributor~8,500 SKUs

    Named · with consent

    12%

    Reply rate, cold outbound to a built distributor list

    8-week run · engineered sender reputation

    A 12% reply rate to a cold distributor list. Deliverability, engineered first.

    Cold outbound email to a built list of hydraulics distributors and OEM buyers, run over 8 weeks as one part of the full Northern Hydraulics engagement. Deliverability came first: SPF, DKIM, and DMARC set up, sending domains warmed, then a tight 5-touch sequence to a researched list. The list returned a 12% reply rate.

    Outbound Email2024

More case studies

Other distributors. Same standard of proof.

  • Industrial hydraulics distributor~8,500 SKUs

    Anonymized · NDA

    +43.5%

    Qualified leads per month, on the August baseline

    Aug 2024 – Jan 2025 · client CRM

    1,840 to 2,640 qualified leads a month. No new ad spend.

    An ~8,500-SKU hydraulics distributor was stuck at 1,840 qualified inbounds a month. AI Overviews were citing its manufacturers, not its own category pages. Six months of catalog and AI-search work later, January closed at 2,640. That’s +43.5% over the August baseline, and we didn’t add a dollar of ad spend.

    Catalog AIAI Search & GEOAug 2024 – Jan 2025

  • Industrial automation distributor~12K SKUs

    Anonymized · NDA

    ×8.5

    AI Overview citation count, top 50 commercial queries

    4 → 34 citations · 6-month engagement

    4 to 34 AI Overview citations in six months. One Standard retainer.

    A mid-market automation distributor with ~12K SKUs was ranking well and still bleeding organic share, because AI Overviews were eating the click-through on informational queries. Six months on the Standard editorial retainer took its AI Overview citations on the top 50 commercial queries from 4 to 34. Organic leads from informational pages doubled.

    Editorial Authority2025

  • Industrial hydraulics distributor~8,500 SKUs

    Anonymized · NDA

    8,500

    SKUs replatformed in six months

    Magento 1 → Next.js + Shopify Hydrogen

    8,500 SKUs off Magento 1, onto a storefront AI engines can read.

    The same hydraulics distributor’s commerce stack was at end-of-life. Magento 1, schema AI Overviews couldn’t read, and 600ms-plus INP that was killing add-to-cart on mobile category browsing. A six-month replatform moved all 8,500 SKUs onto a headless Next.js + Shopify Hydrogen storefront, with a complete schema graph live on the first deploy.

    Website DevelopmentAI Search & GEO2024

Your catalog, same standard

Want a number like these for your catalog?

Held to the same standard as the studies above: we measure where you stand today — organic and AI-search visibility across your top categories — and show you the baseline before we propose a thing.

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