Manufacturing marketing: 9 guiding principles [2026 update]

This previously published article was updated on Aug. 28, 2026.

It’s time for the role of marketing for manufacturers to change.

And my goal for this in-depth article is to empower you to be that agent inside of your company.

I originally wrote this in August 2023. And boy has a lot happened since then. So I went through and did a complete overhaul of the article — integrating new insight, new strategies and new ways for manufacturers to win in 2026 and beyond.

I’ll start by providing some context before diving deep into the following nine manufacturing marketing principles to understand, embrace and put into motion this year:

1. Recognize the power shift from seller to buyer
2. Understand who makes up the buying committee
3. Create value to earn attention and trust
4. Turn the knowledge of your experts into assets
5. Capture demand where it already exists
6. Create demand among the rest of your audience
7. Communicate regularly with your sales team
8. Measure results (but exercise patience)
9. Use AI to compound what your company knows about what works in marketing

The core principles of what makes good marketing haven’t really changed since we first published this page. What’s changed is the world they operate in. So along the way, I’ll show you where AI-assisted buying now touches each one, and where the best practices of 2023 quietly became table stakes in 2026.

Shifting the mindset from expense to revenue engine

If I’ve learned anything from more than a decade as a manufacturing marketing consultant, it’s this:

Manufacturers are traditionally not marketing-driven companies.

Largely, what you have instead are hard-working second-, third- or even fourth-generation family-owned businesses who have built their success on the backs of loyal, repeat customers and referrals.

And the manufacturers who have developed more active business development functions have tended to lean sales-heavy (rather than marketing-heavy).

In fact, when the word “marketing” is spoken inside the walls of many OEMs, custom manufacturers or contract manufacturers, it’s often in the context of an expense.

You know — necessary evils like:

• Making the trade show booth look snazzy
• Designing printed materials for the sales team to leave behind after meetings
• Updating the website with new features and benefits
• Adding new SKUs to the product catalog
• Posting photos from the company picnic (or of Suzie’s cute new puppy) on LinkedIn

Meanwhile, in places like the B2B technology sector, you have marketing-driven organizations that treat marketing programs as the revenue engine of the company: funded, staffed and measured like marketing is the key revenue engine of the company (which it is).

There’s a big gap here

I have a unique look at manufacturing marketing. I consult with manufacturing marketers every week as co-founder of Gorilla 76, an agency that almost exclusively works with manufacturers and industrial companies. I also speak with manufacturing leaders (CEOs, vice presidents, directors) as host of The Manufacturing Executive podcast (300+ episodes and going strong!).

And from where I’m sitting, I see a big gap in how manufacturers look at marketing — and how they need to look at it to turn it into the revenue engine it could be for their business.

When manufacturers reach out to us, the first ask is almost always a tactic. Across 32 recent sales conversations I analyzed, the opening request was usually one of three things:

1. “How do we show up in AI search?” (or: “How do we become the company ChatGPT recommends?”)
2. “We need a better website!” Often paired with traditional SEO fixes to show up in Google.
3. “We need more leads!” Through inbound, paid search or LinkedIn.

Some digging usually reveals that the tactic they’re naming isn’t the real problem. The real problem is that marketing, as it’s currently structured in their business, isn’t moving the needle in the ways that are important to them.

To some, that might mean driving direct revenue growth. To others, that might mean enabling their distributors with a clear sales story and positioning so they can sell their products more effectively. And yet to others, it’s about strengthening their brand and building credibility through thought leadership and strong storytelling.

And the root issues of why they can’t achieve those outcomes often come down to fuzzy positioning, no defined ideal customer, no education for the market, thin proof or no connected path from a stranger’s first website visit to a qualified opportunity for sales. And overall, the lack of a cohesive strategy to get them from where they’re at, to where they need to be — and how they’ll gauge success along the way.

Marketing works for manufacturers when it operates as a connected system that turns the right prospects into buyers. It stalls when it’s bought as a pile of disconnected tactics.

The first eight principles below represent the mental model I’ve developed for how to close the gap between what manufacturers think they need (tactics) and what they actually need (a connected system that generates results) after more than a decade of work in the trenches transforming marketing for this industry.

The ninth principle is newer. It’s how we at Gorilla 76 think AI empowers manufacturers to squeeze more value out of every single piece of work your marketing team does. This principle will break down what’s possible today that simply wasn’t back when I first wrote this guide in 2023.

Ready? Let’s get into it.

1. Recognize the power shift from seller to buyer

Transport yourself back in time 20-some years.

You’d probably be sitting in front of a big clunky off-white computer monitor, waiting on your AOL dial-up connection to lock in before you could Yahoo whatever you were looking for.

Now come back to the present day. So much has changed, and so fast.

Think about how easy it is to collect information about anything now. Whether you’re starting the search for a new car, deciding which Yeti cooler you want to spend your entire next paycheck on or simply looking for a list of birthday present ideas for your mom, the buying power is in your hands. Not the seller’s.

You even have a personal AI concierge to walk you through all major decisions!

So, what’s that mean for you as a manufacturing organization?

• Your prospects are actively looking for answers to their questions using traditional Google search and AI chatbots.
• They’re receiving completely personalized recommendations to their very specific questions, problems and concerns from an AI agent they’ve fine-tuned to their exact preferences.
• They receive a shortlist of company and/or product names that meet their exact requirements.
• They’re then comparing their options by asking extremely specific follow-up questions directly in AI search.
• They’re able to price out potential solutions (before they’ve ever spoken with a salesperson).
• They’ve decided exactly which product or service meets their exact needs, and gotten buy-in from the purchasing committee based on detailed research and pro/con lists.
• Then, they’re revealing themselves to your sales team — just to go through the formalities of buying the dang thing.

One manufacturing leader walked us through exactly how they buy:

1. Ask the AI tool for a list of options
2. Contact the companies on the list.

Ask a question, get a recommendation, make the calls. No trade directory, no page-by-page Google crawl, and no awareness of the excellent supplier that never showed up in the answer.

The stakes are real:

If your company isn’t on the list generated by AI, you won’t get the call. Do not pass go, do not collect $200.

That’s the 2026 version of the buyer-seller power dynamic that’s been shifting for two decades. The buying power sits with the buyer now, and every new research tool hands them a little more of it.

So while a majority of manufacturers are busy tasking their marketing managers with print brochures and product catalogs, the smart ones are out in the digital world answering questions, comparing methodologies, teaching about timeline to ROI and total cost of ownership — and sharing success stories that make it all tangible. And doing all of that in a format that AI can retrieve when your buyers are asking very specific questions to ChatGPT, Claude, Perplexity or Gemini.

The smartest ones are recognizing something harder to swallow. Reputation, repeat business and referrals won’t cut it anymore. At least not on their own.

They’re adapting to how buyers buy right now, and meeting those future customers where they are, including inside the AI answers those buyers increasingly trust.

2. Understand who makes up the buying committee

I say this often:

If your first touch is with procurement, you’re already too late.

Look all the way to the left in this graphic.

These people are physically using your product day in and day out.

Look in the middle.

These people are trying to solve problems on the plant floor, with your customers and throughout your organization.

Look to the right.

These people are ultimately writing the checks (but only after those to the left of them have weighed in).

If you can learn what matters to each of these key buying process influencers and earn their attention and trust by helping and guiding them, they’ll be your advocates when the buying process eventually does move into procurement’s hands.

But if you only focus on the far right, you’ll brand your company as an interchangeable commodity and find yourself in a race to the bottom on price time and time again.

One more 2026 wrinkle worth naming: It’s usually the early-stage influencers (the engineers and problem solvers) who are first to ask an AI tool for answers. You need to show up on the shortlist when they are asking how to solve a problem, the best replacement to an aging piece of equipment or when they’re looking for an alternative to a service provider who has dropped the ball.

3. Create value to earn attention and trust

Next, let’s talk about what it means to create value for your audience through your marketing.

Look back at the buying committee we just mapped. We could do one of two things in our communications with them:

1. Try to sell them stuff
2. Earn their attention and trust by being their best resource

Don’t get me wrong. Number one is the end goal!

And we need to get your sales team to that place. But right now we’re talking about marketing for manufacturing companies. And marketing is not the same thing as sales.

Think for a moment about those early-stage influencers in the buying process (often engineers or other technical professionals).

Then ask these questions:

1. What challenges are they facing that your experts know how to solve?
2. What questions are they trying to get answered?
3. What do they need to know to advance the buying process?

All of this should form the foundation of your content strategy.

The best sales professionals connect with the pains and desired future states of their prospects. The same goes for marketing.

If you talk all about yourself first, no one listens.

But if you talk about what your prospects care about, genuinely help them and demonstrate thought leadership along the way, you’ll then earn the right to talk about yourself.

There are many ways to deliver that help:

• Written blog content (educational in nature)
• Videos of your experts talking about key topics
• Webinars where you’re actively teaching and answering prospects’ questions live
• Audio content (a podcast of your own, or guesting on industry podcasts)

Choose channels based on the resources and skill sets at your disposal, plus what you know about how your audience prefers to consume information.

AI has made it easier than ever to publish a high volume of slop — and the companies that are winning right now ask themselves one question before they hit “publish”:

Could a generic AI tool have written this without your company’s experience and POV?

If the answer is yes, don’t put it out in the world. Your buyers can get that answer straight from a chatbot, and the chatbots themselves have no reason to cite your piece over the rest of the garbage out on the internet.

What earns attention now is the thing only your team could have written:

• The failure you diagnosed last month
• The spec tradeoff your engineers argue about
• The original research you conducted yourself from the data only your company has

You can point an AI tool at the transcripts of your actual sales calls and ask:

• What questions came up more than once this quarter?
• Which objections stalled deals?
• What words do buyers use for the problem we solve?

We do this with our own sales calls. The three most common opening requests I listed at the top of this article aren’t a hunch. They came out of a review of the last six months of recorded sales conversations. The buyer questions in this article’s FAQ also came from real customer questions.

Your equivalent is sitting in your call recordings right now, and it answers the two questions every content strategy stumbles on: what to improve in the content you already have, and what new content to make first.

4. Turn the knowledge of your experts into assets

The best content comes from the brains of your company’s subject matter experts.

We’ve already identified the challenges, common questions and desired future states of your prospects, and the tactical forms your content can take. So how do you actually create those assets?

After all, when’s the last time you met an engineer who’s gung-ho about spending a full day writing a 1,000-word blog post?

From my perspective, the job of a marketer in the content creation process is to be the facilitator — to extract their knowledge through an interview they didn’t have to prepare for. Here’s how we get it done with our own clients.

Written content

We’ll identify the SME (subject matter expert) in our client’s organization, then book a 30-minute interview to extract that person’s key insights around the topic.

Ahead of the interview we do the prep work, so we’re asking the right questions instead of starting from ground zero. Afterward, we’ll research to clarify points, follow up with the SME where needed and send a draft for our client to review.

Notice where the insights come from: the brain of the SME. That’s what matters.

The 2026 upgrade is what happens before that interview. We now have AI scan everything that already exists — past interviews with that expert, sales-call transcripts, published content, what’s already ranking and getting cited on the topic — and answer every question it can from the record.

The 30 minutes with the engineer get spent only on what research can’t answer: their judgment, their war stories, the tradeoffs only they know.

Less of your expert’s time, more of their expertise on the page.

Video content

Like with written content, we prep an outline by doing the upfront legwork. Then we set up a camera, lights and audio on site. Because this is a bigger production, we always batch content creation. The goal is to record a variety of content from a variety of SMEs that can be used for months and remain evergreen. The final product is the SME on camera, teaching.

Here’s the part that’s new since this page was first written: named human expertise now does double duty.

Buyers have always trusted a named engineer over an anonymous brand. Now the AI tools assembling supplier shortlists lean the same way — the pages that get retrieved and quoted tend to carry a named author, first-hand specifics and visible evidence that a real practitioner stands behind the claims. Your SMEs are the one marketing asset a competitor can’t copy and an AI can’t compose. Put their names on the work.

5. Capture demand where it already exists

A majority of your total addressable market is not in buying mode at this exact moment in time.

Let that sink in for a moment.

If there are 1,000 companies that could conceivably be your customers, maybe 10 to 25 are actively looking for a solution today (or let’s say this week). That number likely climbs the closer your product approaches commodity status. Conversely, that number likely shrinks the more specialized, complex and bigger-ticket your product is.

Regardless, when those active buyers are looking for a solution, they go to places like:

• Search — traditional Google and AI chatbots like ChatGPT, Perplexity, Gemini, Claude and Copilot
• Their network
• Industry resources or organizations

We may not know exactly which organizations are buying right now, but we want to make sure they know you.

We call this “capturing existing demand.”

Winning in search — both traditional Google search and AI chatbots. Buckle in for the acronyms. SEO, GEO, AEO, LLMO — whatever you want to call it (and we break down all of these terms here), the goal is the same:

Buyers are asking about things you sell in Google and AI search (ChatGPT, Claude, Perplexity and more), and you want to get recommended.

Treat these as one discipline; under the hood they mostly are. Here’s how the two are similar:

• Both reward the same foundation. Genuinely useful content, clear site structure and credible sources pointing at you.
• Both read the same pages. AI chatbots lean heavily on search indexes and on what your site actually says in plain text.
• Both punish inconsistency. On one audit we ran, an electrical-equipment manufacturer stated one capacity rating on its homepage and a different one deeper in the site. An engine reading those pages just sees a company that contradicts itself, and has less confidence passing either number off to the searcher.

And here’s what’s different:

• The questions got longer. Nobody types “custom gearbox supplier Ohio tolerances lead time” into Google. But a buyer will absolutely ask ChatGPT: “Which suppliers can build a custom gearbox to these tolerances, ship inside six weeks and support installation in the Midwest?” AI search unlocked questions buyers could never ask a keyword box — which means your content can now win on specifics that never had a search volume.
• The answer is a synthesis, not a list. Traditional Google search hands back 10 blue links and lets the buyer judge and click around to do their own research. AI chatbots compose one answer, often recommending a short list of companies. Positioning clarity stops being a brand nicety and becomes retrieval infrastructure: if your own site can’t state plainly who you’re for, what you do best and what proves it, the engine can’t either — so it names someone whose site can.
• Results vary by engine, so measure before you assume. That same equipment manufacturer was the top recommendation on ChatGPT, Claude and Perplexity for its most profitable category — and nearly invisible on Gemini for the identical question. There is nearly infinite variance in answers between AI tools and sessions (we explain why there’s so much variability in AI search, and what to do about it, here).

But for all of the differences between traditional Google search and AI chatbots, the same type of work makes a meaningful difference in both places.

Companies that have already spent years generating genuinely helpful content that answers real buyer questions will, generally speaking, perform decently well in AI search.

We audited a specialty materials manufacturer that has worked hard to rank for key terms on Google, and now gets consistently recommended by AI tools for its niche applications — because its handful of genuinely good, spec-dense technical pages are exactly what an engine wants to quote.

What’s changed since I last updated this article is how people search — and how search engines (including Google) present results. A growing share of searches now end without a click on any website. Google increasingly answers the question right on the results page, and its AI Overviews answer more of them every quarter.

Ranking well still matters. Being quotable enough that the answer engines lift your explanation and recommend your product/service matters more.

For a full breakdown on how to win in AI search, read this.

Paid search buys you time — and it now includes AI platforms. The complement to organic — and in many cases, a faster path to direct sales — is paid. With Google Ads, you’re essentially paying for website traffic by selecting and bidding on keywords.

It’s very easy to waste money on pay-per-click (PPC). The most strategic advice I can offer is to focus your PPC spend on high-intent keywords. For Gorilla, we’d rather bid on “industrial marketing agency” than “industrial marketing strategy.” Those searching for an agency are exhibiting buying intent; those searching for strategy are probably trying to learn. We love both visitors, but we’d rather earn the learners’ attention organically.

And before you spend a dollar, mine the cheapest strategy document you own: your own campaign history.

Here’s how we drove cost per lead from $682 to $214 for an industrial startup:

1. We exported every paid-search lead they’d ever generated.
2. We discovered that, although they’d been bidding on — and paying for — hundreds of keywords, only a handful had ever produced a meaningful lead.
3. Then we turned off every keyword that had never generated a lead, and rebuilt the entire campaign around the nine keywords that had led to real qualified leads.
4. We put effort into creating a seamless experience for those nine remaining keywords: message-matched ads and landing pages (message-matched = the ad and page actually contain the keyword), along with clearer positioning and storytelling.

One quarter into that rebuilt program, right-fit inbound sales requests were up 195.83%. Deliberately imperfect campaigns, launched fast, built to get smarter every day they ran. That beat waiting for perfect.

The newest entrant is advertising inside ChatGPT itself. We started testing ChatGPT ads on our own account in May 2026, within days of the platform opening up, so these lessons are first-hand:

• The platform is young and moody. Settings change without notice, minimum budgets moved mid-test (now $25 a day), and campaigns occasionally pause themselves. Budget pacing on lifetime campaigns is aggressive. Go in expecting beta behavior.
• Targeting is prompt-based, not keyword-based. You describe who you’re for and what you do — we fed ours from our positioning docs and ideal-client profile — and the platform decides which conversations your ad fits. Clear positioning literally becomes your targeting.
• The conversions objective won our test across CTR, cost per click and CPM (our conversions campaign ran a 1.23% CTR at about $2.45 a click), even though conversion volume itself was too small to judge. Reach was cheap on impressions but weak on clicks.
• Creative real estate is tiny. A clean logo outperformed conventional ad creative for us.
• Reporting is thin. No job titles, no company names, no sub-national geography yet. Treat it as awareness spend with click efficiency, not a lead machine — at roughly $750 a month minimum, it’s a test worth running if your buyers live in these tools.

6. Create demand among the rest of your audience

Now let’s come back to our hypothetical total addressable market of 1,000 customers that we described at the beginning of the last section. If 10 to 25 of those 1,000 might be active buyers at this moment in time, that means 975 to 990 companies that fit your ideal customer profile.

These organizations are not in buying mode right now.

Many of them will be in a week or a month or a year.

But right now, they’re not.

So how do you think a “Buy Now” message resonates with that vast majority of your audience?

It doesn’t.

They’re ignoring you. Or worse, they’re writing you off because you’ve done nothing but blast unwelcome sales messaging in their ears for weeks or months or years.

Most manufacturers (and frankly, most companies in general) fail to acknowledge that just because someone in your audience isn’t buying right now doesn’t mean they’re a “bad” prospect or lead.

So let’s bring this back around to the concepts we’ve already talked about:

• Knowing who the buying process influencers are
• Understanding what matters to them
• Creating amazing content that will earn their trust and attention

Now it’s time to go actively distribute this content to them to assure that the messaging is actually consumed by the right people from the right companies.

This strategy is called demand generation.

Most manufacturing organizations don’t have the luxury of sitting back and waiting for future customers to show up at their doorsteps.

They need to proactively get out into the world, build personal connections and earn trust. Read: GENERATE demand.

For most, these are sales activities.

But marketing has a major role to play here as well.

Content distribution can take on many forms. Here are a few worth noting:

• Paid social. Target people with specific job titles at specific types of companies in specific regions, and tell LinkedIn: Show this article to these people; after they’ve seen it, show them this related video; then show them the case study that puts it all in context.
• Email. Stop treating email as the channel for announcing you’ll be at booth 33 next week. Treat it as the medium for distributing the genuinely helpful resources you’re creating.
• YouTube. Turn your channel into a library of tutorials and resources around your expertise.
• Guest podcasting. Have your SMEs appear on niche industry podcasts to teach the same topics you’re writing about and filming. There’s a second payoff here: every credible show that names your company and your experts adds to the public record AI tools read when they decide who belongs in an answer. A mention on someone else’s trusted platform is worth more to the machines than another page on your own.
• Trade shows and events. Still where much of this industry builds relationships face to face. The shift worth making: Treat the show as a content engine, not just a booth. The questions you field there are next quarter’s articles, and the talk your SME gives is next quarter’s video series.

And bring back PR. I mean that seriously. Public relations spent a decade as the forgotten line item in industrial marketing budgets, and it’s suddenly one of the highest-leverage things you can do — because both people and AI engines weight what other credible sources say about you far above what you say about yourself.

The old PR playbook pays off big in the age of AI:

• Do genuinely newsworthy things. Original research is the most repeatable version: publish a real number nobody else has (a benchmark, a survey of your buyers, data from your own operations) and you become the source other publications — and the engines reading them — have to cite.
• Put your experts where journalists look. One of our clients’ subject-matter experts was quoted once in a national business publication. Within weeks, three other publications reached out to the same person — AI-curated search had started surfacing him as the credible, neutral voice on his topic. One well-placed quote became a compounding asset.
• Show up organically where your buyers already spend attention. Consistent, useful LinkedIn presence from your named experts; guest spots on the shows your buyers trust. People discover you through people they already follow — and the engines watch the same trail.

Every article, video, podcast appearance and industry mention you put into the world is also part of the record AI tools read when they decide which companies belong in an answer. The company that’s been teaching in public for three years has left exactly the footprint those tools look for. The company that refuses to publish specifics (pricing, specs, etc.) online and saves everything for the sales deck is invisible twice: to the buyers and to the machines they ask.

Capture demand among those who are buying. Generate demand among those who aren’t yet. When they enter a buy cycle, you’re the first one they call.

7. Communicate regularly with your sales team

This one may sound like a no-brainer, but I’ve looked inside dozens of manufacturing organizations over the past decade, and very few have created any meaningful alignment between their marketing and sales personnel.

The core of the problem is where this article started: Manufacturers are traditionally not marketing-driven companies. If a manufacturer’s sales team has always viewed marketing as the folks who make brochures and post on Facebook, what motivation do they have to spend hours of their week with the marketing people?

So if you’re on board with the principles laid out so far, it’s time to get sales on the bus too. Start by shifting the dialogue from tactical to strategic:

• What are the new sales targets for this year (or quarter)?
• Where do the biggest growth opportunities lie?
• Where can the company be most profitable?
• What does the current sales pipeline look like?
• Where are future customers getting stuck?
• How are they tracking deals in the CRM?

As these conversations become productive, make them recurring. Set an agenda, learn from each other, develop strategies together.

And mine the calls. Your sales team hears the market’s real questions every single day — the objections, the confusions, the exact words buyers use. That’s your content engine’s fuel. The questions and quotes threaded through this very article came from our own sales calls; yours are sitting in your CRM and your reps’ heads right now.

Think about what’s actually sitting in that archive. The 100+sales calls your team had in the last six months with real, qualified buyers contain every question that stalled a deal, every objection that came up three times, every phrase buyers use for the problem you solve. In the old world, that insight died in reps’ memories and CRM notes nobody reread. What AI changes is retrieval: transcribe the calls, keep them in one place and the archive becomes something you can interrogate. Ask it which questions recur. Ask it what language buyers use for a capability you’re about to launch a page on. Ask it which objection your content has never once answered.

That’s the difference between guessing what the market wants to hear and knowing.

8. Measure results (but exercise patience)

Here’s the harsh reality:

You don’t grow an effective marketing program from the ground up overnight. In fact, the number one ingredient missing from most manufacturing marketing programs is this:

Patience.

Ultimately, marketing success should be measured on contribution to pipeline. But remember: A majority of your total addressable market isn’t actively buying at this moment. There will be low-hanging fruit, and you should go get it (see Principle 5).

But throwing 100% of your marketing resources at next quarter’s revenue will fail for most companies.

Effective marketing for manufacturers is a process: incrementally generating awareness, building trust through real thought leadership, capturing demand where it exists while building it where it doesn’t and analyzing your KPIs to improve continuously.

Here’s what to watch, and what each measure actually tells you:

Early numbers like traffic, visibility and rankings are often dismissed as “vanity metrics,” and as endpoints they are. As barometers, they’re how you confirm you’re moving in the right direction while pipeline catches up.

How to measure AI search visibility specifically. Rankings don’t exist in AI answers in the same firm way they did in traditional Google searches, so build the manufacturer’s equivalent: a fixed set of real buyer questions, asked the same way on a schedule. Write down 10 to 20 questions your actual buyers ask (pull them from the sales calls in Principle 7 — never from a keyword tool alone), then run them monthly across the tools your buyers use like ChatGPT, Perplexity, Gemini, Claude, Google’s AI Overviews. For each, record two separate things: were you named in the answer, and was your site cited as a source? Expect variance between platforms and between runs — that’s normal, and it’s why the trend matters more than any single answer. The North Star stays, of course, is having qualified leads tell you an AI is how they heard about you. We cover the full measurement setup in our AI search guide and in this post about how to get your company recommended by ChatGPT.

We also use purpose-built tools (like Peec AI and others) to gain a more comprehensive understanding of your visibility across dozens of prompts run every single day. But running prompts yourself on your own device is a great starting point, and costs nothing.

And one small, concrete move to make this week: Add “How did you hear about us?” as a free-text field on your contact form. When someone mentions they heard about you through an AI chatbot, have your sales team ask what specifically they searched. Keep a list of those questions, and then use that as a map for which content to prioritize updating and creating.

How long does this actually take?

Honest answer: Expect leading indicators before revenue, and expect quarters, not weeks.

And when it compounds, it looks like this:

• Davron, an industrial oven manufacturer, built this kind of system with us and attributed $9 million in sales pipeline to it.
• The Korte Company, a design-build construction firm, grew monthly contact generation 650% in two years after rebuilding around education-first marketing.

Those results took sustained investment over years, and both companies’ programs started with the same principles you just read.

Without patience, companies stay trapped in what I’ve long called the endless hamster wheel of marketing mediocrity.

9. Use AI to compound what your company knows about what works in marketing

There are two ways to think about AI:

1. Use it to do everything as quickly as possible. Content published from a single prompt. The same spam email sent to everyone on your list.
2. Use it to do more powerful, more ambitious stuff than was ever possible before.

We think No. 1 is the wrong way to think about AI. More blog posts, faster, cheaper. That’s a race to produce the exact content Principle 3 told you earns nothing — the stuff a generic tool could have written, that buyers skim past and engines never cite. If your AI strategy is “same marketing, less effort,” you’re going nowhere — you’re just doing it at a faster clip than before.

We’re much more interested in No. 2 — and we’ve been working hard at building systems that allow us to tackle bigger problems, at a greater scale, than was possible before.

Specifically, we’re building a system that draws from a database of everything we know about a company (from positioning workshops to strategy calls to interviews with engineers, past campaign performance, spec sheets and more) into every recommendation we give, and every bit of content we make on behalf of a client.

We built this for ourselves before we built it for any of our clients. We loaded transcripts from 61 sales calls, five-plus years of published content and LinkedIn posts, and hundreds of podcast episodes into a single knowledge base our AI tools can query. Now, when we plan content, we don’t ask “what should we write about?”

We ask the system:

• Which questions came up on the most calls this year?
• What did real buyers say, in their words?
• What have our experts already answered on a podcast that never made it to the website?

We’re building the same thing for clients: every sales conversation transcribed and captured, technical docs and specs loaded in, conference talks and past interviews included.

Ask a generic AI to write about your product and you get confident garbage. Ask a system grounded in ten years of your experts’ actual conversations, and the first draft starts from what your company knows — with your marketer steering, fact-checking and asking the follow-ups.

Then close the loop. This is the part that turns a content operation into a compounding asset, and it’s where I’ll borrow an idea from the advertising world: ad titan Rory Sutherland has long argued that you can’t reliably predict which marketing move will work, so the winning strategy is to increase your exposure to luck — run more small, cheap, real tests than your competitors can.

Our AI system allows us to bring the performance data from every bet into every future set of recommendations, so we focus more of our energy on the stuff that’s working and let failed bets die.

Basically, we’ve built a self-improving loop that leverages a company’s total context:

Most marketing programs run the first three steps and let the fourth evaporate — the learnings live in a slide deck nobody reopens, and next year’s plan starts from scratch. A well-built AI system lets your marketing develop a memory. That’s the system we now run at Gorilla 76 — every recommendation we make is built on the back of every past bet’s recorded performance, the ones that worked and the ones that didn’t.

The honest boundary. None of this replaces the first eight principles. A learning system pointed at fuzzy positioning learns faster that your positioning is fuzzy. AI is an accelerant: pour it on a real fire — clear positioning, genuine expertise, a connected path to pipeline — and it compounds. Pour it on a pile of disconnected tactics and you just get faster, cheaper versions of what wasn’t working.

In an AI-search world, the companies that learn fastest about their buyers beat the ones that simply publish the most.

Frequently asked questions

What is the role of marketing in a manufacturing company?

Marketing’s role is to build a system that finds the right future customers, educates them until they trust you and hands sales conversations that are already halfway won. At most manufacturers it has historically been treated as a support expense: brochures, trade show booths, website updates. The manufacturers outgrowing their competitors treat it as a revenue function with its own pipeline contribution target.

How much should a manufacturer spend on marketing?

It depends on your situation, but a good rule of thumb is to reinvest three to five percent of sales into growing your company through effective marketing. That percentage might scale up depending on how lofty your growth goals are.

How long does manufacturing marketing take to work?

Leading indicators (rankings, traffic, engagement, early conversations) typically move within the first two to three quarters. Pipeline contribution follows as trust and awareness compound. Anyone promising meaningful pipeline in 90 days is describing paid lead generation, not a marketing system — and usually one that stops the day the spend stops.

Should we hire a marketing agency, build in-house or both?

It depends on what you’re solving for, and the honest answer is sometimes “don’t hire us.” A capable in-house marketer wins on proximity to your experts and your customers; a specialized agency wins on pattern recognition across dozens of similar companies and on skills you’d struggle to hire for one seat. The most common working model we see succeed: a strong internal owner who knows the company, paired with outside specialists for strategy and execution capacity. If you can’t yet articulate your positioning and ideal customer, fix that first (with whoever helps you do it) before buying any tactical capacity anywhere.

How do we show up when buyers ask ChatGPT or other AI tools for supplier recommendations?

Be the company whose pages the AI can read, trust and quote: Answer real buyer questions directly, publish proof with names and numbers, keep data in text and tables rather than images and PDFs and build a consistent footprint of expertise across the web. It’s the same trust-building this whole page describes, made machine-readable. Our guide to AI search for manufacturers covers the specifics step by step.

Is SEO still worth it for manufacturers?

Yes. Buyers still search Google in volume, and the demand data on our own site confirms it every month. What’s changed is that ranking is no longer the whole game: The same qualities that earn rankings (genuinely useful content, credible proof, clean structure) are also what earn citations in AI answers. Build the page once, win on both surfaces.

Need some help?

I recognize this was a lot to digest. But hopefully it has you thinking differently already.

If you could use some advice about where to get started, consider requesting a consultation, and we can talk strategy. We’ll tell you honestly what we see — including if what you need first isn’t us.