When economic headwinds forced most organisations to pause marketing in 2023, true leaders see opportunity; and Camwood leaned in. This is the story of how Andrew Carr, Managing Director of Camwood, transformed a 25-year-old technology services company from partner dependent to market-leading, achieving a complete reversal of their business model whilst elevating their brand to enterprise- grade status.
Working with AI growth marketing experts at Jam 7, Camwood didn't just weather the economic storm; they used it as a catalyst for unprecedented growth and market positioning.
The UK technology services company used the downturn to rebuild its go-to-market around a governed, human-led agentic-AI operating model; owning the sales cycle, elevating brand perception to enterprise-grade, and compounding discoverability where intent already lived. What follows is the complete story; challenge, strategy, implementation, results; with the artefacts a board and revenue team need to judge effectiveness and replicate the playbook.
End Results Snapshot
- Revenue mix: ~70% partner / 30% direct → ~30% partner / 70% direct (≈15 months)
- Pipeline influenced: ≈ £2.77 million
- Organic visibility: average position +7.9; keyword footprint +~17%
- Priority ranks: “AVD Migration” #17 → #12; “Intune Migration” 100+ → #10
- Conversion: homepage conversion rate +~152%
- Demand quality: 277 new leads; 233 progressed to SQL; Google Ads leads +~1100%
The TL;DR
- Who: Camwood; 25+ years in enterprise technology services.
- What: A direct-first revenue model achieved by replacing campaign-led marketing with a human-in-the-loop, agentic-AI growth system.
- Why: Channel dependence limited control of narrative, margin, and cycle time; direct-first restored control.
- When: Kick-off in 2023; compounding outcomes across ≈15 months.
- Where: UK focus with applicability to enterprise and regulated sectors.
- How: ICP truth → enterprise message architecture → agentic-AI content & performance engine → CRO and paid as signal amplifiers → quarterly optimisation.
1) Situation and stakes
By 2023, roughly 70% of Camwood’s revenue flowed through partners. The leadership team knew the cost of that success: less control over the sales cycle, less ownership of the story, and slower learning loops. As Managing Director Andrew Carr put it: “We don’t control the sales cycle… We needed to own our own destiny.”
At the same time, macro headwinds created a window. “Everyone can sail a boat in calm waters,” Andrew noted.
“If everyone else is going to pull back on marketing, why don’t we push the button a little bit and push ourselves in terms of budget?”
The ambition: flip to a 70% direct / 30% partner model without losing momentum.
2) The strategic bet: from campaigns to an agentic-AI system
Camwood partnered with Jam 7 to pursue an AI-enabled system; not a campaign. The programme anchored to three compounding pillars:
- ICP clarity & demand architecture – turning diffuse buyer notes into precise ICPs (pains, triggers, decision criteria), then mapping those to questions buyers already ask in market.
- Enterprise-grade message architecture – recasting Camwood from “project capacity” to governed outcomes (reduced complexity, accelerated release velocity, hardened security posture, lower cost-to-serve), applied consistently across the site and sales assets.
- Agentic-AI content and performance engine (human-in-the-loop) – domain-trained AI agents for research, clustering, copy and performance, orchestrated by a human Growth Agent with brand and compliance governance. The promise wasn’t “more content,” it was governed velocity and repeatability.
From the outset, Camwood called it straight.
“The fact that there was a structure and a framework that we worked towards gave us an authentic framework which we could buy into… It wasn’t just a workshop where you ask a few questions and you go off on different tangents.”
3) Implementation timeline (what happened when)
Phase 1 ; Foundations (weeks 1–6)
- Content & asset audit, analytics hygiene, technical SEO fixes
- Message and terminology governance; claims & referencing standards
- Editorial plans by cluster; measurement baselines for visibility, conversion, influenced pipeline
Phase 2 ; Production (weeks 7–18)
- Weekly publishing cadence (pillars + supporting articles)
- CRO sprints (forms, offer clarity, friction) and paid to accelerate signal
- Service pages re-written from features → outcomes & proof
Phase 3 ; Optimisation (weeks 19+)
- Internal-link depth, structured headings, FAQ opportunities, performance hygiene
- Spend reallocation toward qualified demand (not just cheaper clicks)
- Quarterly reviews focused on visibility, conversion, and influenced pipeline
Learning was mutual. “It took us a bit of time to learn how you were doing what you were doing for us.” That honesty compressed the learning curve and hardened the operating model.
4) The operating model Jam 7 deployed (human-led, AI-powered)
Ownership & cadence
- 70/30 split of work: Jam 7 produced ~70% of outputs; Camwood provided the ~30% only the client can give (approvals, nuance, domain insight).
- Rituals: weekly production stand-ups; monthly CRO reviews; quarterly business reviews.
- Team: Growth Lead, SEO, Content Strategist, CRO Specialist, Performance Lead, AI operators, Designer.
Agentic-AI loop
- ICP research → 2) topic clustering & briefs → 3) weekly production → 4) CRO experiments → 5) paid amplification for faster signal → 6) sales/CRM feedback → back to strategy.
Human-in-the-loop means every asset passed editorial QA (accuracy, tone, brand), with compliance and accessibility checks (headings, alt text, link wording).
Governance
- Brand voice codified; claims and data sources checked
- Structured headings for scanability; internal pathways to conversion pages
- Change logs to preserve editorial integrity over time
5) What changed on the ground
Information scent & clustering
Interlinked pillar pages and supporting articles answered executive questions and evaluation detail: why it matters, how it works, outcomes, timelines, prerequisites, risk and handover. Navigation became intuitive for buyers and answer engines.Pages that convert
Service pages shifted from static capability lists to outcome narratives with unmissable proof. Micro-CTAs invited small commitments (assessment, teardown, workbook download) at natural decision points.
Paid & CRO as signal amplifiers
High-intent categories received paid support to accelerate learning. Winning offers, messages and page patterns migrated into SEO pages so learnings compounded.
Technical & structural hygiene
Headings mirrored buyer questions; internal-link depth increased; performance basics removed friction. A substantial FAQ block captured recurring objections and unlocked rich-result eligibility.
Storytelling like an analyst
The narrative moved from “what we did” to “what changed”; governed transformation, reduced complexity, measurable KPIs, risk reduction in enterprise contexts.
6) Results (evidence that compounds)
- Business model flip achieved: from ~70% partner / 30% direct to ~30% partner / 70% direct in ≈15 months.
- Pipeline influenced: Jam 7’s activities directly influenced approximately £2.77 million.
- Discoverability: average position +7.9; keyword footprint +~17%; with priority topics moving into traffic-bearing territory (e.g., “AVD Migration” #17 → #12 and “Intune Migration” 100+ → #10).
- Conversion: homepage conversion +~152%.
- Lead velocity & quality: 277 new leads; 233 progressed to SQL; Google Ads leads +~1100%.
- Perception: “The work that Jam 7 did started getting us noticed… People were finding us, which they hadn’t been previously.” “People still comment on and love the brand, really love the way you’re talking to the market.” “People are standing up and taking notice.”
7) Risks, constraints and controls (why these results are credible)
- What we didn’t change: no pricing strategy shifts; no CRM re-platform; no PR spikes. That kept attribution clean.
- Quality guardrails: domain training for AI agents; human editorial QA for every asset; compliance checks for claims and privacy.
- Attribution & lag: GA4/GSC/Ad platform/CRM sources; linear model where multi-touch was unavailable; weeks for leading indicators, quarters for pipeline compounding.
8) Transferability (where this works)
The system excels for B2B technology providers pursuing digital-first growth where governance, security alignment and measurable outcomes matter most. It is particularly effective for firms with complex product/service narratives, multi-stakeholder sales, and the need to convert latent brand equity into direct, qualified pipeline.
9) Replicable playbook (90-day starter plan)
- Choose one high-intent cluster; publish a pillar + three supporting articles.
- Re-write one core service page from features → outcomes & proof.
- Run weekly CRO sprints to remove friction.
- Fund modest paid on the same cluster to learn messages/offers quickly.
- Review signals every two weeks; ship improvements weekly; report monthly on acceptance and cycle time.
10) Client voice (what it felt like)
- “The fact that there was a structure and a framework that we worked towards gave us an authentic framework which we could buy into… It wasn’t just a workshop where you ask a few questions and you go off on different tangents.”
- “Because we’ve spent time investing in the relationship both ways, I think we’ve managed to have those very early conversations with each other and get back on track.”
- “The work that Jam 7 did started getting us noticed… People were finding us, which they hadn’t been previously.”
- “People still comment on and love the brand, really love the way you’re talking to the market.”
- “People are standing up and taking notice.”
Andrew’s closing advice to B2B tech leaders:
“Everybody wants the silver bullet, right? And that silver bullet’s never existed in business.”
Sustainable, programmatic marketing outperforms sporadic campaigns; and transparency makes partnerships work.
11) Working with Jam 7 on AMP (light overview)
Human-led, agentic-AI by design. Jam 7’s Agentic Marketing Platform (AMP) pairs a Growth Agent with specialised AI agents (research, clustering, copy, performance). Strategy and execution run in a single governed loop, turning ICP truth into weekly outputs, CRO learnings and paid signal; without clients “managing a tool.”
Onboarding; what to expect. A short, structured capture of your positioning, tone, personas and goals trains AMP on your business. You see velocity in week one, with outputs reviewed against brand and compliance standards. Cadence and transparency; like you’ve read here; are the point, because they compound.
(If you prefer to evaluate the engine behind the work before talking scope, ask for the Board Pack and a 15-minute GTM Teardown; those will show the motions, artefacts and KPIs we manage week to week.)
12) Calls to action
- Download the Direct-First GTM Board Pack (2-page summary, timeline poster, KPI workbook).
- Book a 15-minute GTM Teardown to map your path from channel-dependent to direct-first.
13) Frequently asked questions (AEO-ready)
What is an agentic-AI marketing system; and how is it different from “AI content”?
A human Growth Agent orchestrates specialised AI agents for research, clustering, copy and performance inside a single governed plan. Instead of random volume, you get governed velocity: consistent outputs tied to ICP truth, brand standards and measurable commercial goals.
How did this system produce outcomes so quickly at Camwood?
It replaced campaign sprawl with a weekly operating cadence: ICP-aligned topics, production, CRO experiments and paid signal feeding back into the plan. That’s how discoverability, conversion and pipeline improved together; culminating in a mix reversal to roughly 70% direct in about 15 months.
Which KPIs mattered most to leadership?
Pipeline influenced (≈£2.77M), conversion (homepage +~152%), lead acceptance (MQL→SQL), ranking lifts (avg position +7.9, footprint +~17%), and paid efficiency (Google Ads leads +~1100%). These are leading and lagging indicators tied to commercial outcomes.
How is brand safety and accuracy maintained with AI?
All outputs pass human editorial QA with brand, compliance and accessibility checks. AI agents are domain-trained on first-party materials; governance rejects anything off-brand or unproven before it ships.
What did you deliberately not change (so attribution stayed clean)?
Pricing, HubSpot CRM platform, and PR spikes remained constant during initial sprints. The point was to measure the system itself; strategy, content, CRO, and paid working together.
What risks did you plan for; and how were they mitigated?
Quality drift (solved by QA and domain training), ICP mismatch (sales feedback loop), channel dependence (portfolio balance), stakeholder bandwidth (RACI and templates), ranking volatility (cluster depth and refresh cycles).
Where does this approach work best?
B2B technology contexts where governance and measurable outcomes matter; enterprise and regulated settings, complex product/service stories, multi-stakeholder sales.
What’s the 90-day plan to prove signal before scale?
One cluster, pillar + three supports, weekly CRO sprints, modest paid on the same cluster, and one service page rewrite from features to outcomes. Review signals fortnightly; move resources toward what compels acceptance and accelerates cycle time.
What did Camwood say about the partnership?
Among other remarks: “The work that Jam 7 did started getting us noticed… People were finding us, which they hadn’t been previously.” And on timing: “If everyone else is going to pull back on marketing, why don’t we push the button a little bit and push ourselves in terms of budget?”
Andrew's Recommendations for B2B Tech Leaders
- The relationship we built with Jam 7 pushed us to think differently about how we approached marketing. They took us from trying to be normal and best of breed to finding different ways of talking about what we do.
- My advice to other B2B tech leaders: if you haven't thought about marketing differently, you should do so now. The window of opportunity for AI-enhanced marketing is here, and if you don't jump on it and go all in, you're going to miss that chance.
- But remember—there's no silver bullet. Success comes from sustained investment, clear strategy, and partnerships built on transparency and mutual respect."
The Return: Lessons for B2B Tech Leaders
Andrew's journey offers valuable insights for B2B technology leaders facing similar challenges:
Embrace Counterintuitive Timing
"If everyone else is going to pull back on AI marketing, why don't we push the button a little bit?" Sometimes the best opportunities emerge when others are retreating.
Invest in Sustainable Marketing
"Everybody wants the silver bullet, right? And that silver bullet's never existed in business," Andrew reflects. The lesson: sustainable, programmatic marketing outperforms sporadic campaigns every time.
Think Beyond the Logo
Brand is more than visual identity; it's messaging architecture, market positioning, and customer perception. True brand transformation requires systematic approach across all touchpoints.
Relationship-First Partnerships
"You can't put a price on relationships when they work like that," Andrew emphasises. The most successful transformations happen when vendors become true partners through transparency and mutual investment.
AI Marketing as Accelerator, Not Silver Bullet
AI enhances human creativity and strategy rather than replacing it. The most effective implementations combine AI efficiency with human insight and authentic brand voice.
Conclusion
Camwood’s shift from channel dependence to direct-first growth was not a campaign; it was a governed, agentic-AI operating system applied with consistency, candour and measurable standards. If you need your next quarter to create better odds for the next year, this is the kind of system that compounds; because it converts truth about your buyers into momentum you control.
