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.
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.
Camwood partnered with Jam 7 to pursue an AI-enabled system; not a campaign. The programme anchored to three compounding pillars:
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.”
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.
Ownership & cadence
Agentic-AI loop
Governance
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.
High-intent categories received paid support to accelerate learning. Winning offers, messages and page patterns migrated into SEO pages so learnings compounded.
Headings mirrored buyer questions; internal-link depth increased; performance basics removed friction. A substantial FAQ block captured recurring objections and unlocked rich-result eligibility.
The narrative moved from “what we did” to “what changed”; governed transformation, reduced complexity, measurable KPIs, risk reduction in enterprise contexts.
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.
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.
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.)
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 journey offers valuable insights for B2B technology leaders facing similar challenges:
"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.
"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.
Brand is more than visual identity; it's messaging architecture, market positioning, and customer perception. True brand transformation requires systematic approach across all touchpoints.
"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 enhances human creativity and strategy rather than replacing it. The most effective implementations combine AI efficiency with human insight and authentic brand voice.
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.