Industrial Marketing Agency

Industrial Marketing Agency for Technical Manufacturers

Engineering-first growth systems that diagnose revenue leaks, optimize AI visibility, and accelerate pipeline for £50M–£500M industrial B2B companies.

The industrial revenue leak

The industrial revenue leak no one is talking about

Most industrial companies aren't losing pipeline because of weak marketing. They're losing it because buyers (and AI) can't understand what they do.

Today, engineers, R&D teams and procurement committees evaluate vendors through AI first. ChatGPT, Claude, Perplexity and Google AI Overviews form the initial shortlist before any human conversation happens. If your pages, PDFs and technical surfaces aren't AI-visible and engineering-clear, you're eliminated long before Sales knows the opportunity existed.

We fix this by identifying the revenue leaks no one else sees — AI invisibility, technical clarity gaps, BOFU friction, journey breaks, PDF black boxes, CRM decay — and then installing a growth system that compounds week after week.

This is not an agency. This is industrial GTM rebuilt for the agentic era.

Lead Generation

Industrial Lead Generation

Most agencies "generate leads" through campaigns and content volume. We eliminate the industrial revenue leaks that prevent qualified demand from ever reaching your pipeline.

What this looks like in practice

Industrial buyers don't respond to generic lead generation tactics. They evaluate vendors through a multi-stage technical validation process that happens largely invisible to your Sales team:

  • Initial AI-powered research (ChatGPT, Perplexity, Google AI Overviews)
  • Engineering team evaluation of technical content and specification clarity
  • Procurement committee comparison of capabilities across spec sheets and case studies
  • R&D validation of application fit and technical credibility
  • Committee consensus building across multiple stakeholders

If any surface in this journey is unclear, AI-invisible, or technically imprecise, you're eliminated before Sales knows the opportunity existed. Our diagnostic identifies exactly where your funnel leaks qualified demand, then we systematically plug those leaks.

The industrial difference

Generic lead generation assumes buyers follow linear funnels and respond to marketing touches. Industrial buyers move through non-linear, committee-driven evaluation journeys where technical clarity matters more than marketing polish. They need:

  • Specification-level detail presented with engineering clarity
  • Application notes that demonstrate understanding of their process challenges
  • Case studies from similar technical environments
  • Proof of capability at their required scale and complexity
  • Clear articulation of implementation risk and support structure

We optimize for this reality, not for SaaS marketing playbooks that fail in industrial contexts.

Why traditional approaches fail

Most agencies optimize for traffic volume or generic "MQLs" that waste Sales' time. Industrial B2B requires precision over volume — fewer, better-qualified opportunities that actually convert. This means:

  • Rewriting BOFU surfaces for engineering-grade clarity
  • Fixing weak CTA architecture that creates unnecessary friction
  • Making PDF content AI-extractable and model-comprehensible
  • Mapping technical journeys across all evaluation surfaces
  • Identifying hidden demand trapped in CRM decay
  • Converting overlooked pages into pipeline-generating assets

Lead generation in industrial B2B isn't a campaign. It's the result of removing friction from every technical decision surface your buyers touch.

Content Marketing

Technical Content Marketing for Engineers

Your technical buyers don't want marketing. They need clarity. And in 2025, that means content that both AI systems and human engineers can understand, extract value from, and use in technical evaluation.

What we transform

We rebuild dense, engineering-led content into technical narratives that drive decisions:

  • Application notes that demonstrate process understanding
  • Specification sheets with clear comparison architecture
  • Data sheets optimized for both human scanning and AI extraction
  • Complex product pages simplified without sacrificing technical accuracy
  • Whitepapers structured for progressive revelation of technical depth
  • Technical PDFs converted from AI-invisible black boxes to searchable, extractable assets
  • Engineering blog content that establishes domain authority
  • R&D documentation that supports committee evaluation

Why this matters now

Engineering buyers have changed how they consume technical content. They no longer download 40-page PDFs and read them linearly. Instead, they:

  • Ask AI to summarize vendor capabilities and extract key specifications
  • Use search to find specific answers to technical implementation questions
  • Scan pages looking for quick pattern matches to their requirements
  • Share content with committee members who need different levels of detail
  • Evaluate clarity as a proxy for execution competence

If your content doesn't serve these behaviours, you're invisible regardless of how technically accurate it might be.

What makes our approach different

We don't "pretty up" content or add marketing fluff. We structurally rebuild it with engineering discipline so that:

  • AI systems can extract entities, specifications and relationships accurately
  • Engineers find the technical depth they need without wading through filler
  • Procurement committees can compare your capabilities against alternatives
  • R&D teams can validate application fit quickly
  • Multiple stakeholders can consume the same content at different depth levels

We're led by a former CTO with 20+ years in advanced materials, polymers, aerospace and industrial technology. We speak engineering, not marketing-to-engineers. If the models can't understand your narrative, your buyers won't trust it either.

SEO & Digital Marketing

Industrial Digital Marketing & SEO

SEO for technical manufacturers is no longer keyword optimization. It's AI visibility + semantic clarity + domain authority from technical correctness.

The search landscape has fundamentally changed

Traditional SEO focused on ranking for keywords through backlinks and on-page optimization. That still matters, but industrial buyers now encounter your brand through:

  • AI Overviews that synthesize multiple sources and display zero-click answers
  • Perplexity and ChatGPT that cite sources based on content structure and entity clarity
  • Google's specialized search features (featured snippets, knowledge panels, comparison tables)
  • Voice search and AI assistants that need structured, extractable content
  • Procurement copilots that evaluate vendors through automated content analysis

If your content isn't optimized for these AI-first discovery channels, you're losing 40-60% of your potential pipeline before humans ever see your site.

What we optimize

Our approach combines traditional SEO fundamentals with AI-era visibility requirements:

  • AI Overview and AEO optimization - structuring content for AI extraction and citation
  • Semantic entity mapping - ensuring technical products, capabilities and applications are correctly understood
  • Clear value articulation - rewriting for engineering audience comprehension without sacrificing technical accuracy
  • Intent-matched CRO - optimizing conversion paths for industrial buying behaviour
  • Internal linking architecture - building clear technical journey pathways
  • Multi-lens scoring - evaluating every page across 40+ commercial dimensions through Katelyn
  • Model comprehension testing - verifying AI systems can accurately extract and represent your capabilities
  • High-intent search capture - targeting queries that indicate active evaluation and committee research

Your competitive advantage

Most industrial competitors are still optimizing for 2015 search behaviour - keywords, meta tags, backlinks. You'll be optimized for the AI-first evaluator that actually determines which vendors make the initial shortlist. This creates a 12-24 month advantage window as the market catches up to this reality.

Trade Shows

Trade Show & Event Marketing

Industrial trade shows remain critical relationship-building opportunities, but 80% of the potential ROI disappears because teams don't optimize the full lifecycle. Most companies treat shows as standalone events instead of pipeline multiplication systems.

The complete lifecycle approach

Before the show:

  • Create AI-visible pre-show content that establishes your presence in event-related searches
  • Build technical landing pages for key product showcases with clear CTA architecture
  • Target engineering and procurement decision-makers through focused outreach
  • Develop clear narrative compression for fast technical evaluation at the booth
  • Prepare handoff assets that Sales can use for immediate post-show follow-up

During the show:

  • Deploy systematic capture frameworks that qualify leads efficiently
  • Use clarity-first booth propositions that engineers can evaluate in 3-5 minutes
  • Create narrative compression tools for Sales to communicate value quickly
  • Gather technical requirements and application details for precise follow-up
  • Identify committee composition and decision timeline

After the show:

  • Execute automated follow-up pathways personalized by conversation context
  • Build BOFU re-engagement flows that address specific technical questions raised
  • Create AI-visible summaries of show announcements and product launches for Sales enablement
  • Convert booth conversations into structured CRM data that drives pipeline forecasting
  • Measure actual pipeline impact, not just "leads collected" vanity metrics

Why most trade show ROI is lost

Companies invest £50K-£200K in booth presence, travel and materials, then lose 80% of potential value through:

  • No pre-show visibility building to drive qualified booth traffic
  • Weak booth messaging that fails the "what do you do" test in 30 seconds
  • Poor capture processes that generate unqualified contact lists
  • Slow or generic follow-up that doesn't reference specific technical conversations
  • No systematic path from conversation to opportunity in CRM
  • Missing AI-visible content that supports post-show research and committee evaluation

We fix the entire system so trade shows become pipeline multipliers, not expensive lead collection exercises.

Website Development

Manufacturing Website Development

Your website isn't your homepage. It's the collection of all evaluation surfaces that buyers and AI systems use to determine if you're qualified for their shortlist.

What industrial websites must serve

In 2025, your website must simultaneously serve three audiences with different needs:

Engineering buyers who need:

  • Specification-level technical detail without marketing fluff
  • Clear application fit evidence for their specific use case
  • Fast answers to implementation and integration questions
  • Proof of capability at required scale and complexity
  • Evidence you understand their process challenges

AI evaluation systems that need:

  • Structured content with clear entity relationships
  • Extractable specifications and capabilities
  • Semantic clarity around technical terminology
  • Comprehensive coverage of product applications
  • Explicit value propositions and differentiation

Procurement committees who need:

  • Clear comparison frameworks against alternative approaches
  • Risk mitigation evidence and support structure clarity
  • Pricing and commercial model transparency
  • Implementation timeline and resource requirements
  • Reference customers in similar technical environments

Most industrial websites fail all three audiences because they're built around company org charts instead of buyer evaluation journeys.

Our website rebuild approach

We reconstruct your website around:

  • Engineering-grade clarity - technical accuracy with zero marketing fluff
  • AI-readability - structured content that models can extract and cite accurately
  • BOFU optimization - conversion paths designed for long-cycle, committee-driven decisions
  • Technical storytelling - progressive revelation from overview to specification depth
  • Specification pathway continuity - clear journeys from product pages to detailed technical resources
  • CRO for industrial behaviour - friction removal and clarity enhancement, not SaaS conversion tactics
  • Industrial UX patterns - navigation and content architecture that matches technical evaluation behaviour
  • AI-first content structure - headings, lists and formatting optimized for model comprehension

The technical difference

We're not a creative agency making industrial websites "prettier." We're led by a former CTO who has built systems for advanced materials, polymers, aerospace and industrial technology companies. We understand the technical evaluation process because we've lived it on both sides - as buyers and vendors.

This is the website industrial buyers and AI copilots expect in 2025, not a 2019 corporate brochure adapted for mobile.

Account-Based Marketing

Industrial Account-Based Marketing (ABM)

Industrial deals aren't closed by one person. They're won by persuading multi-stakeholder technical committees where each member evaluates different aspects of capability, risk and fit.

The industrial buying committee reality

A typical technical B2B purchase involves 6-10 stakeholders with different evaluation criteria:

  • R&D / Engineering - technical capability, specification fit, integration complexity
  • Procurement - commercial terms, risk mitigation, support structure
  • Operations / Manufacturing - implementation timeline, training requirements, disruption risk
  • Quality / Compliance - certification, regulatory fit, audit requirements
  • Technical Management - strategic fit, vendor relationship, long-term roadmap
  • Business Line Owners - ROI justification, competitive impact, resource allocation
  • Finance - total cost of ownership, payment terms, budget approval

Traditional ABM treats these stakeholders as individual targets for personalized campaigns. That fails in industrial contexts because committee members share information, compare notes and build consensus collectively.

Our committee journey design approach

We build ABM as systematic committee alignment, not campaign tactics:

Stakeholder journey mapping:

  • Identify committee composition and decision influence patterns
  • Map information requirements for each stakeholder role
  • Build content pathways that serve progressive depth needs
  • Create comparison frameworks that support consensus building

Technical proof architecture:

  • Develop evidence structures that address role-specific concerns
  • Build specification-level detail for technical evaluators
  • Create commercial clarity for procurement and finance stakeholders
  • Establish implementation confidence for operations teams

AI-evaluable comparison surfaces:

  • Structure content so AI tools can extract and compare capabilities accurately
  • Build clear differentiation frameworks that committees can use
  • Create decision support content that reduces evaluation friction

Cross-surface narrative continuity:

  • Ensure consistent story across website, PDFs, presentations and conversations
  • Maintain technical accuracy while adapting depth for different stakeholders
  • Connect dots between initial awareness and final evaluation

Outcome clarity for low-risk adoption:

  • Demonstrate clear ROI frameworks committee members can defend internally
  • Address implementation risk and resource requirements explicitly
  • Provide reference evidence from similar technical environments

This is ABM designed for technical buying committees - not SaaS campaign automation ported to industrial contexts.

Why Industrial Teams Choose Graph Digital

CTO-led technical credibility

You're not working with marketers trying to understand engineering. You're working with a former CTO (20+ years) who has built systems for:

  • Advanced materials (graphene, carbon fiber, 2D materials)
  • Polymers and composites
  • Aerospace-grade manufacturing
  • Industrial technology platforms
  • Medical and scientific instrumentation
  • Engineering-heavy B2B environments

Engineers trust us because we speak their language. We've been on both sides of technical evaluation - as buyers assessing vendor capability and as vendors communicating complex differentiation.

Diagnostic precision through Katelyn

This is the real differentiator. Katelyn is our proprietary diagnostic engine that audits your entire digital estate across 40+ commercial dimensions:

  • AI visibility and overview appearance probability
  • Technical clarity and engineering comprehension
  • Intent alignment across buyer journey stages
  • Funnel leakage identification and quantification
  • Editorial gap analysis for category authority
  • CRO diagnostics with position-weighted impact
  • Semantic coverage and entity completeness
  • Proof architecture and credibility signals
  • Persona fit across committee stakeholder types
  • Content structural integrity and scannability

Every week, Katelyn returns your next 3 highest-impact moves with evidence, expected uplift and implementation guidance. This converts GTM from random acts of marketing into a systematic, compounding growth engine.

AI-native GTM for the agentic era

We don't just acknowledge AI - we've rebuilt industrial GTM for a world where AI systems do initial vendor evaluation before humans get involved. This means optimizing for:

  • AI Overview appearance and citation probability
  • LLM extraction accuracy and entity recognition
  • Model comprehension of technical content
  • Procurement copilot evaluation frameworks
  • Voice search and conversational query patterns
  • Agentic research systems that synthesize multiple sources

Your competitors are still optimizing for 2015 search behaviour. You'll be optimized for 2025+ AI-first discovery.

Results

Industrial Client Results

Victrex - Advanced Materials Leader

Sectors

Industrial Sectors We Serve

Advanced Materials | Polymers & Composites | Aerospace Components | Medical Devices | Industrial Automation | Scientific Instrumentation | Chemical Engineering | Energy Technology | Manufacturing Technology | Industrial Software | Process Equipment | Testing & Measurement

Client types

  • FTSE 250 and Fortune 500 industrial divisions
  • Mid-market technical manufacturers (£50M-£500M revenue)
  • Materials science innovators
  • Engineering-led B2B companies
  • Technical product manufacturers
  • Scientific and industrial instrumentation
  • Process technology providers
The Growth Diagnostic

Your Entry Point

You don't need a retainer commitment. You need diagnostic clarity first.

The Growth Diagnostic gives you a precise map of where your industrial GTM is leaking revenue, what's blocking growth, and a systematic path to measurable improvement - or we work for free.

Weeks 1-2: The Revenue Leak Map

Katelyn runs your entire GTM system through 40 diagnostic lenses covering discovery diagnostics, clarity diagnostics, conversion diagnostics, and system diagnostics.

You receive a complete revenue leak report identifying the 10 highest-impact fixes with quantified gaps and expected uplift.

Weeks 2-4: Quick Wins

We execute 3-5 surgical fixes that create demonstrable improvement within 14-30 days.

The guarantee

If you don't see measurable improvement in visibility, lead quality, or conversion within 90 days, we work for free until you do.

Common Questions

Frequently Asked Questions

Do you work with companies outside advanced materials?

Yes - we serve £50M-£500M industrial B2B companies across all technical manufacturing and engineering sectors. Our advanced materials pedigree (graphene, 2D materials, carbon fiber, polymers) means we can clarify any complex technical product. If you manufacture engineered products sold to technical buyers through long sales cycles, we can help.

Why not just hire another industrial marketing agency?

Because agencies produce activity without diagnostic clarity. We focus on precision diagnostics that identify the exact surfaces where revenue leaks (AI invisibility, technical clarity gaps, BOFU friction, journey breaks) and systematically fix them with engineering discipline. Think systematic problem-solving applied to GTM, not more marketing campaigns.

What happens in the first 14 days of the Growth Diagnostic?

You get a complete revenue leak map showing exactly where your industrial GTM is losing qualified demand. This includes: AI visibility audit across all surfaces, technical clarity scoring for key content, BOFU friction identification, journey break analysis, CRM health assessment, competitive positioning gaps, and your top 10 priority fixes with expected impact. Plus we begin implementing 1-2 quick wins during this diagnostic phase.

How do you measure ROI and success?

We track commercial metrics that matter to industrial leaders:

  • Qualified pipeline increase - more opportunities that Sales actually wants
  • Conversion rate improvement - better yield from existing traffic
  • AI visibility gains - AI Overview appearances, featured snippet capture, LLM citation probability
  • CRM data quality - attribution clarity and forecasting confidence
  • Sales cycle compression - faster committee consensus and decision velocity
  • Lead quality improvement - better ICP fit and technical qualification

Most teams see measurable uplift within 6-8 weeks. If you don't, we keep working until you do.

What if we've already tried industrial marketing agencies and been disappointed?

That's exactly our target client. Most agencies produce activity without diagnosing the real problem. They deliver campaigns, content calendars and social media posts while your actual revenue leaks - AI invisibility, journey breaks, BOFU friction - go unaddressed. We start with Katelyn's 40-lens diagnostic to identify the precise leaks killing your pipeline, then execute surgical fixes with engineering discipline. No generic campaigns. No random acts of marketing. Just systematic problem identification and resolution.

Can you work alongside our existing marketing team?

Yes - we're designed to augment internal teams, not replace them. Most industrial companies have strong internal marketing people who are simply overwhelmed and lack specialist AI-era GTM expertise. We provide the diagnostic engine your team doesn't have time to build, AI-native optimization expertise that's new to everyone, systematic execution frameworks that enable team productivity, weekly priority identification so effort focuses on highest-impact work, and technical communication capability for engineering-heavy products.

How is this different from traditional industrial marketing agencies?

Traditional agencies optimize for campaign volume and marketing "activity." We optimize for diagnostic precision - finding exact revenue leak points, commercial metrics (pipeline, conversion, lead quality), AI-era visibility (optimizing for how buyers actually research in 2025), engineering credibility (technical accuracy that builds trust), and performance guarantees (we work until you see measurable improvement). Plus we're led by a CTO with 20+ years in advanced materials, polymers and aerospace - not marketers trying to understand engineering.

What's the risk if we wait another 6-12 months?

Your competitors are already implementing AI-native GTM systems. Every quarter you delay: your AI invisibility gap widens as competitors optimize for LLM extraction, engineering buyers increasingly use AI tools that can't find or accurately represent your capabilities, procurement copilots exclude you from automated vendor evaluations, your technical content becomes comparatively harder to evaluate, and committee consensus building favors vendors with clearer technical narratives. By Q3-Q4 2025, industrial buyers will primarily rely on AI-assisted research for initial vendor evaluation.

Do we need to create new content or can you work with existing assets?

Usually you don't need more content - you need clearer, AI-visible content. Most industrial companies have extensive technical resources (PDFs, spec sheets, application notes, whitepapers, product pages) that are AI-invisible or too dense for efficient evaluation. We focus on restructuring existing content for AI extraction and model comprehension, simplifying technical narratives without sacrificing accuracy, converting PDF black boxes into searchable, extractable assets, clarifying value propositions buried in engineering specifications, and building comparison frameworks from scattered capability descriptions.

How long until we see results from the Growth Diagnostic?

Weeks 1-2: Diagnostic clarity - you understand exactly where revenue is leaking

Weeks 2-4: Quick wins deployed - 3-5 high-impact changes implemented

Weeks 4-6: Early measurement - initial uplift visible in key metrics

Weeks 6-12: Systematic improvement - compounding gains across multiple surfaces

After 90 days: If you haven't seen measurable improvement (you will), we continue working for free until you do.

Next Steps

Ready to find your revenue leaks?

The Growth Diagnostic gives you diagnostic clarity in 14 days, measurable improvement in 90 days, and a systematic path to predictable pipeline growth.

Request the Growth Diagnostic