01 / Metabolic London
How B2B GTM Tactics Drove 247% Growth for a B2C Fitness Brand
247%sign-up growth87%attribution accuracy180%corporate client increase
Client background
Metabolic London is a London-based boutique HIIT studio with locations in Camden and Brentwood. Daily classes, body-composition focus, quality programming, strong community. The business ran on Mindbody for bookings, ClassPass for fill, and Instagram for awareness. Sign-ups were rising but the team had zero visibility into what was actually working.
The challenge
Sign-ups were happening but Metabolic couldn’t see why. Mindbody source attribution was broken, ClassPass volume masked direct conversions, and Instagram content felt like a black box. Revenue leaked everywhere they couldn’t measure. Corporate wellness was an obvious adjacent revenue stream they hadn’t touched. The growth ceiling was no longer about content quality — it was about infrastructure.
The solution
Two-track engagement. Track one: B2B outbound to London corporate wellness programs and HR teams using a personalised LinkedIn + email motion. Track two: rebuild the analytics stack from scratch — PostHog for behavioural data, Mindbody source attribution fixed at the API layer, and dashboards that finally answered “where is the next pound coming from?”
Implementation
- Corporate wellness ICP built, enriched in Clay, targeted in HeyReach and Smartlead
- PostHog implemented across web + booking funnels, sessions stitched to bookings
- Mindbody UTM/source attribution rebuilt with custom field mapping
- Live revenue + cohort dashboards delivered weekly to ops
- Organic retargeting layered through email and LinkedIn DMs
Results
247% sign-up growth. 87% of new sign-ups now traceable to source. 180% increase in corporate clients within the year. Seven distinct revenue channels operating with clear attribution. ~35% of new MRR coming from a B2B channel that didn’t exist before.
“Jared completely transformed how we think about growth. The B2B channel opened a revenue stream we didn’t know existed, and the analytics infrastructure finally gave us visibility into what actually drives sign-ups. The 247% growth speaks for itself, but the real value is having infrastructure that scales with us.”
Lawrence Hannah · CEO and Founder
↑ back to top02 / Mindset
Automated Investor–Startup Matching: 4 Hours → 15 Minutes, 10x Throughput
4hr → 15minper matching cycle10xweekly throughputSame-dayintros
Client background
Mindset operates an investor-to-startup matching platform. Founders engage to find aligned capital; investors come to find vetted dealflow. Quality of match is the entire product. The bottleneck was the human matching step that gated every intro.
The challenge
Each match took roughly four hours of an analyst's time: research the startup, scan the investor universe, score on stage, sector, geo and thesis, then write the intro. At ten to twelve startups a week the team was already at capacity — and quality dropped under pressure. Growth meant more headcount or a different model.
The solution
Reframe matching as a data + algorithm problem, not a workflow problem. Enrich every investor and startup with structured signals. Score matches with a multi-dimensional model. Use automation to do everything except the final human sense-check.
Implementation
- Investor and startup databases enriched in Clay with sector, stage, check size, recent activity
- Matching algorithm scoring on 8 weighted dimensions with explainable output
- Workflow orchestration in Make and n8n: brief in, ranked match list out
- Quality control feedback loop — every accepted/rejected intro improves the next match
Results
Each match cycle dropped from 4 hours to 15 minutes. Weekly throughput went from ~10 startups to ~150 with the same team. Intros now happen the same day instead of the following week. The matching data compounds — every cycle makes the next one sharper.
“The crème de la crème of outbound marketing. Jared is extremely professional and the best at what he does. Incredibly proactive, planning ten steps ahead, communicates clearly. I see him as an extension of our team due to his collaborative approach. His unique approach to copywriting will knock your socks off.”
Dexter Hutchings · Marketing Manager, Mindset.ai
↑ back to top03 / CultureBot
From 2 Days to 2 Minutes: Billing Automation Unlocked 40% Faster Growth
2 days → 2 mininvoice generation-95%billing errors+40%scaling speed
Client background
Chicago-based employee engagement platform serving 1,000+ remote and hybrid teams through Slack and Microsoft Teams. Strong product, freemium model, consistent acquisition. Ready to scale aggressively — except the back office wouldn’t let them.
The challenge
Billing was completely disconnected from sales and product. Every invoice took two days from deal close. Errors were frequent and embarrassing, cash flow dragged, sales velocity was artificially capped by finance throughput, and new customer experience started rough because activation waited on billing.
The solution
RevOps Engineering. Connect CRM directly to billing. Generate invoices automatically the moment a deal closes. Deliver them with embedded payment links. Sync payment status back into CRM and product so customers activate the same day they pay. No manual touches anywhere in the loop.
Implementation
- Sales-to-billing integration triggered by Closed Won deal stage
- Intelligent invoice generation with proration, tax, and seat counting
- Automated customer delivery via email with self-serve payment portal
- Closed-loop sync: payments update CRM, trigger product provisioning, notify CS
Results
2 days to 2 minutes. 95% reduction in billing errors. 16 hours per week recovered for the finance team. Same-day customer activation. Payment collection 60% faster. The operational ceiling on growth lifted entirely.
“The billing automation transformed our ability to scale. We went from manually processing every invoice to fully automated billing in minutes. Our finance team got their time back, our customers get activated instantly, and we removed the ceiling on how fast we can grow. This infrastructure investment paid for itself in the first month.”
CultureBot Leadership Team
↑ back to top04 / MindK
Unified 8 Disconnected Systems, Prevented $400K in Churn Year One
30% → 98%lead data completeness-70%deal close time$400Kchurn prevented
Client background
Software development agency with teams across San Francisco and Eastern Europe. 120+ engineers, 170+ delivered projects, 4.9/5 Clutch, multiple years on Inc 5000. Strong reputation, strong delivery. Weak internal infrastructure.
The challenge
Eight disconnected systems running the revenue org: separate CRMs, Asana for delivery, three enrichment tools, a contract tool, a billing tool, a BI tool. Marketing and sales pulled different versions of the truth. Only 30% of leads had complete data. Contracts bottlenecked at the proposal step. Leadership couldn’t see churn risk until customers were already gone.
The solution
Treat the eight tools as one system. Real-time bidirectional sync, automated enrichment at the lead source, dynamic contract generation triggered by deal stage, predictive churn scoring fed from product + support signals, and one unified reporting layer that everyone could trust.
Implementation
- Real-time sync infrastructure across all 8 systems
- Automated enrichment pipeline at lead-source (Clay + Apollo)
- Dynamic contract generation triggered by deal stage
- Unified reporting dashboard pulling from one source of truth
- Predictive churn scoring from product, support, and billing signals
Results
Cross-system sync went from manual hours to under 2 minutes. Lead data completeness jumped from 30% to 98%. Deal close time dropped 70%. Churn surfaced 60 days earlier on average, preventing roughly $400K in lost ARR in the first year. Eight systems felt like one.
“We’ve come across many mobs that claim they can deliver, though haven’t seen any one of them execute at the level and transparency that Jared has. A good mix of ethical, human-touch automation and clever copy.”
John Hammond · Director of Operations, MindK
↑ back to top05 / Factmata
£15 to £1.20 Per Lead. 300 Qualified Leads Daily. Acquired by Cision.
-92%cost per lead300/dayqualified leadsAcquiredby Cision (2022)
Client background
AI-driven media monitoring company founded in 2017. Backed by Biz Stone (Twitter co-founder), Craig Newmark and Mark Cuban. Narrative monitoring at scale: brand risk detection across the open web, identifying disinformation, hate speech and reputational threats before they spread.
The challenge
£15 cost per qualified lead was unsustainable. Manual enrichment was eating engineering hours that should have been going into the product. A lean seven-person team couldn’t afford to scale GTM operations by hiring — they needed infrastructure that scaled without headcount.
The solution
Treat lead generation as an engineering problem. Automated enrichment pipeline. Quality assurance checks at every step. Volume infrastructure designed to handle hundreds of leads a day without manual intervention.
Implementation
- Automated enrichment pipeline across Clay, Apollo, LinkedIn, and proprietary signals
- Quality assurance gates that drop low-fit leads before they hit the SDR queue
- Scalable infrastructure designed for 300+ qualified leads per day
- Engineering team protected from operational lead-ops work entirely
Results
Cost per qualified lead dropped from £15 to £1.20 — a 92% reduction. Volume scaled to 300 qualified leads per day. Engineering reclaimed full focus on the product. The infrastructure carried Factmata through to acquisition by Cision in November 2022.
“Creativity as well as disciplined iteration are key to cutting through the noise in modern marketing. Jared has both in buckets.”
Antony Cousins · CEO, Factmata
↑ back to top06 / ClearStake
43% Conversion Lift. Dynamic Pricing Engineering Unlocked £800K+ in Annual Revenue.
+43%conversion increase+£800Kannual revenue unlocked8-tierdynamic pricing model
Client background
London fintech founded in 2020. Financial data for the igaming sector — Open Banking integration used by gambling operators for affordability checks and financial due diligence. Backed by Flutter Entertainment, PointsBet, Stats Perform and EML Payments. Seven-figure seed round closed in early 2024.
The challenge
Flat pricing left money on the table. Enterprise operators with high volume got premium value at mid-market prices. Smaller operators bounced because the flat price didn’t scale down. Win rate on deals under £50K sat at 23%. Pricing decisions were inconsistent because they were intuition, not data.
The solution
Pricing as data engineering, not strategy. Build a system that segments customers across multiple dimensions, predicts willingness-to-pay, recommends optimal pricing per deal, and learns from every win and loss.
Implementation
- Customer segmentation pipeline producing 8 distinct segments
- Predictive pricing model recommending tiers with conversion probability per deal
- Dynamic proposal generation integrated into the sales workflow
- Learning loop — win/loss outcomes refine the model continuously
Results
43% conversion increase across all segments. Enterprise ACV up 67%. Win rate on under-£50K deals went from 23% to 41%. £800K+ in annual revenue unlocked in year one. Sales cycle 28% shorter. Pricing inconsistency eliminated.
“Jared transformed our pricing from guesswork into a systematic revenue engine. The 43% conversion improvement speaks for itself, but the real value is having pricing that scales with our business.”
Martin Burt · CEO, ClearStake
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