An 18-person B2B SaaS startup with growth flatlining. The CEO had been functioning as accidental CMO. Treetop engaged as fractional CMO for 18 months. Here is what changed and how.
Composite case study: a synthesis of patterns we have seen repeatedly across similar engagements. Specific names, numbers, and details are illustrative; the patterns and outcomes reflect real client results.
Company stage: 18-person B2B SaaS, $4M ARR, growth stalled for 3 quarters.
Marketing situation: 1 marketing coordinator and a paid media agency. CEO acting as default CMO.
Pain: Pipeline coverage was thin. Positioning was generic. Agency relationship producing leads but not pipeline. CEO consumed by marketing decisions instead of CEO work.
Existing AI usage: Minimal. Marketing coordinator used ChatGPT occasionally for drafts.
Months 1-2: Operational ICP rebuilt (15 fields instead of vague description). Positioning sharpened around defensible differentiator. Agency relationship restructured with measurable goals.
Months 3-4: AI-native marketing workflows deployed. Content production scaled 3x with the existing 1.5 FTE team. Shared Claude Projects with voice and ICP.
Months 5-9: Hired 2 marketing ICs against the new operating model. Onboarded them into the AI-native workflows from day one.
Months 10-18: Iterated and optimized. Built lifecycle marketing, account-based motion, and demand generation engine.
Content output: From ~6 substantive pieces/month to 18.
Pipeline contribution: Marketing-sourced pipeline grew from 28% of total to 47%.
CAC: Held roughly flat despite 3x marketing investment — the additional spend was higher-leverage.
Sales cycle: Compressed from 75 days to 52 days because of better qualified leads.
The firm hit the inflection where a full-time CMO made sense. The fractional engagement had built the function to the point where a permanent hire could step in successfully.
Total fractional cost over 18 months: $190,000.
ARR growth: $5M of new ARR.
The handoff: Treetop ran the search for the full-time CMO, briefed them on the AI-native operating model, and continued as advisor for 90 days post-hire.