Before/after evidence with problem, baseline, intervention, system built, results, and timeline.
Anonymous where needed — use company type and stage rather than name if the client prefers.
£18M+revenue generated
£6.8M+paid spend managed
6×app downloads (healthtech)
35%lower CAC (fintech)
Case Studies
How the system was built.
Each case study follows the same structure: problem, baseline, intervention, system, results, timeline.
eCommerce · Growth-stage, post-PMF
eCommerce: 21% retention uplift in three months
Acquisition was producing customers. The product produced repeat orders. The lifecycle programme didn't bridge them.
+21%90-day repeat purchase rate
3.2×Win-back conversion rate
+18%Lifecycle revenue contribution
What made it work: Retention (90-day repeat-purchase rate) moved up 21% in three months. The improvement concentrated in the two target cohorts. The lifecycle programme moved from three flows to seven, but the team's weekly load went down because the new flows were triggered, not batch-sent.
The team was paying full-funnel CAC for users who would never reach the funnel that mattered. Eight weeks of structural fixes.
-35%Customer acquisition cost
+28%Conversion rate (paid → activated)
11 → 6Number of active campaigns
What made it work: CAC dropped 35% in eight weeks. Paid spend stayed roughly flat. The team kept the rebuilt account structure and the routing logic; the agency relationship was renegotiated around managing the structure rather than buying more creative cycles.
B2B SaaS: from founder-led chaos to a weekly GTM cadence
The founder was still approving every message test. The fix was a tight weekly cadence, clearer ICP, and one owner map — not more channel spend.
-18%Sales cycle (median)
3 → 7Experiments shipped / month
-35%Founder hours on GTM
What made it work: Qualified pipeline became more predictable week to week; sales cycles shortened modestly once messaging aligned to the sharper ICP. The company made its first dedicated growth hire with a documented playbook instead of starting from blank.
AI HealthTech: 6× monthly app downloads in 6 months
Acquisition was busy. The app had press, downloads, and a working app store listing. What was missing was a system.
6×Monthly downloads
+38%Activation rate
-41%Cost per qualified install
What made it work: Monthly downloads moved from ~2,000 to 12,000+ over six months. The number wasn't the win — the win was that the team could explain *why* it moved, what to scale, and what to drop. The growth story became fundable, and the founder spent less time approving experiments.
90 days from reactive marketing to a working GTM operating system.
2.4×Qualified pipeline
+42%Reply rate on outbound
3Channels actively invested in
What made it work: By the end of the engagement, the team owned a working experiment rhythm, had retired three channels that were absorbing time without compounding, and had shipped a positioning update that moved reply rates on outbound by a double-digit percentage. The CEO spent noticeably less time in marketing decisions.
Most startups don't have a channel problem. They have a clarity problem.
When the offer is specific enough, the right channel becomes obvious.
Fix the message before you fix the media.