Manufacturers · industrial B2B

SEO and AI search visibility for manufacturers

Your buyer is an engineer, an architect or a purchasing manager building a shortlist. More of that shortlist now starts in ChatGPT, Perplexity, Gemini or a Google AI Overview. We test whether your name is on it, and fix the reasons it is not.

SEO for manufacturers used to mean ranking a product page for a category search. It still does. But a specifier who asks an AI assistant which manufacturers to consider now gets three to five names and a reason for each, and never sees a results page. Being findable means appearing in both places, and the work that gets you there is mostly the same work.

Your reputation may have outrun your website

Manufacturers who sell through specification tend to have something rare: decades of installed work, real technical authority, and relationships that took a generation to build. They also tend to have websites that were built to look like a brochure and have never been asked to do anything else.

That was survivable when buyers found you through a rep, a catalogue or a trade show. It is a problem now that a specifier opens an assistant and asks which manufacturers to consider — because the answer is assembled from structured facts and citable content, and a brochure site supplies neither.

The encouraging part is that this is almost always a packaging problem, not a substance problem. The expertise exists. It just is not in a form a machine can read, verify and quote.

The questions

Eight questions specifiers actually ask

We do not test whether an assistant knows your company name — ask about you by name and it will talk about you. We test the questions a buyer asks before they know who you are. These are the patterns, with the category filled in for your products.

  1. “We are specifying [product category] for a new facility. Which manufacturers should we consider, and how do they compare?”
    The shortlist question. It decides who gets evaluated at all.
  2. “What are the alternatives to [competitor] for [application]?”
    Asked when an incumbent is expensive, slow or out of favour — your best opening if you are named.
  3. “Which [product] meets [code or standard] for [environment]?”
    Compliance is often the deciding filter, and it is usually buried inside a PDF.
  4. “How does [material A] compare to [material B] for [application]?”
    Comparison questions get confident, named answers. Whoever published the comparison gets cited.
  5. “Who makes [product] with [certification, listing or EPD]?”
    A yes/no filter. If the certification is not stated on a readable page, the answer is effectively no.
  6. “What should I look for when specifying [product] for [use]?”
    The criteria the engine lists tend to favour whoever defined them in public.
  7. “Which [product] manufacturers can supply projects in [region]?”
    Coverage, lead times and rep networks. Frequently answered from directories rather than from your site.
  8. “What does [product] typically cost, and what drives the price?”
    Budgeting questions come early. Engines answer them from whatever pricing context they can find.

Each of these returns a short, confident answer with named companies and cited sources. Whether you are one of those names is a measurable fact, not an opinion.

The free Snapshot

What the AI Visibility Snapshot tests

The Snapshot is the free first step, and it is useful on its own whether or not you ever hire us.

What we testHow
The questionsFive to eight buyer questions like the ones above, written for your category and approved before anything runs.
The enginesChatGPT, Perplexity and Google Gemini, each with live web search enabled, with model versions and date recorded.
Whether you are namedNamed in the answer, searched for by name and then dropped, or never considered at all. The middle state is the most common and the most fixable.
Who is named insteadThe competitors each engine chose, and the pages it cited to justify them.
WhyThe technical and content causes behind the result, and what we would fix first.

You get the full transcripts, usually within two business days, with no sales call required. Request a Snapshot or see what the report contains.

What we usually find

The same problems, over and over

These are patterns across manufacturer websites in general, not a diagnosis of yours. That takes testing. But they are where the evidence usually leads.

The specification library is hidden

Data sheets, test reports, warranties and installation guides that buyers search for by name, sitting inside PDFs with no readable web page around them, or behind a crawl setting nobody remembers changing.

No product structured data

Whole catalogues with no machine-readable facts: no materials, dimensions, certifications or warranty terms. The engine has to guess, and often cites a competitor that stated them plainly.

Traffic is almost all brand

The site works for people who already know the company name and barely registers for anyone searching the product category. Search Console usually shows this within minutes.

The comparison content is a download

A genuinely useful material or product comparison exists, but only as a gated or downloadable file, so it can never be ranked, quoted or cited.

Nothing corroborates the company

Decades of installed projects, but few independent sources — directories, associations, specification databases, trade listings — that describe the company consistently. Engines trust claims that appear in more than one place.

Nobody has tested the answers

The marketing team tracks rankings and leads, but has never recorded what the assistants say when a specifier asks. Without a baseline there is no way to tell whether anything is improving.

What the work looks like in practice

Our published case study is an e-commerce catalogue rather than a manufacturer, and we would rather say so than imply otherwise. The specifics differ; the method does not — prove why machine-readable systems cannot read or corroborate you, fix it, measure it. Read the case study › or browse all case studies.

Why a specialist

Not a full-service manufacturing marketing agency

A good industrial marketing agency runs trade shows, campaigns, paid media and sales collateral. We do none of that. We do the part those agencies are rarely set up to measure: whether Google and the AI assistants can read, trust and name you.

That focus is also why the work is done by one person. Lance Rankin runs the tests, diagnoses the causes, makes the fixes and writes the reports, with AI doing the volume work — the hundreds of queries, the crawls, the month-on-month comparisons. There is no account manager between you and the work. How we work ›

We also understand how specification selling works: that a spec is written months before an order, that “approved equal” is where deals are won and lost, that a rep network is a channel rather than a directory, and that a submittal package is a sales document.

  • Specification-driven categories. Building products, architectural specialties and their industrial equivalents. See building products manufacturers.
  • Long sales cycles. We measure the shortlist, not last-click attribution.
  • Dealer and rep networks. We work with the channel rather than around it.
  • Real catalogues. Hundreds of SKUs, variants, finishes and technical documents. We have run one ourselves.
Pricing

What it costs, published

The same prices as our pricing page. No discovery phase billed before you see anything.

EngagementPriceWhat it is
AI Visibility SnapshotFreeBuyer questions tested on three engines, with transcripts. About two business days.
Full Visibility Review$3,500The Snapshot expanded, plus organic, technical, competitive and authority analysis and a prioritised roadmap. Credited against a program started within sixty days.
Foundation Sprint$14,500Fixed scope over 90 days: crawl and indexation, structured data, metadata, redirects, performance and measurement.
Growth Program$9,500/moTwelve-month term: content, answer-engine work, specification publishing, authority building and monthly AI re-testing.

Regional and mid-sized manufacturers: a scaled-down retainer runs $1,500–$3,500 a month depending on scope.

Questions

SEO for manufacturers: common questions

What is SEO for manufacturers?

SEO for manufacturers is the work of making a manufacturer’s products, specifications and expertise findable when engineers, architects and purchasing teams research a category. It now has two targets: the ranked results on Google, and the short lists of named companies that ChatGPT, Perplexity, Gemini and Google’s AI Overviews give in answer to buyer questions. The technical foundations serve both.

Are you a manufacturing marketing agency?

Not in the full-service sense. We do not run trade shows, paid media, PR or brand campaigns. Digital Regiment is a specialist practice focused on one thing a manufacturing or industrial marketing agency is often not set up to measure: whether search engines and AI assistants name you when a buyer asks, and fixing the reasons they do not. We work alongside an existing agency when there is one.

How do you measure whether AI assistants recommend us?

We fix a set of real buyer questions for your category, run them through ChatGPT, Perplexity and Gemini with live web search, and record whether you are named, who is named instead and which pages were cited. The questions and engines stay the same each month, so the results can be compared.

How long does it take to see results?

Technical and structured-data fixes can change what the engines can read within weeks. Durable ranking and traffic gains usually take six to twelve months. Nobody can guarantee a mention in an AI answer, and we do not.

Do you have a manufacturer case study?

Not a published one yet. Client work stays private unless a client asks otherwise. Our published case study is an e-commerce catalogue we own, and we say so plainly rather than dress it up as manufacturing work.

What does it cost?

The AI Visibility Snapshot is free. A Full Visibility Review is $3,500, credited against a program started within sixty days. The Foundation Sprint is $14,500 over ninety days, and the Growth Program is $9,500 a month on a twelve-month term. All of it is published on the pricing page.

Further reading: why ChatGPT doesn’t mention your company and all guides.

Find out what AI says about you

We run the buyer questions in your category through ChatGPT, Perplexity and Google Gemini, and send you a short report showing whether you appear, who appears instead, and why. No cost, no obligation, no sales call required to receive it.

Request your free check

Usually back within two business days.