We model CAC and LTV before a dollar moves, test every channel against a control, and trace spend back to pipeline, not just clicks. If your paid budget is growing faster than your pipeline trust, this is the fix.
Built for Series A–B B2B SaaS ($3M–$15M ARR) moving past founder-led sales — not pre-PMF startups or enterprise teams with growth already scaled in-house.
We work out the acquisition plan before we touch a single campaign: channel mix, budget pacing, audience segmentation, and a creative testing rhythm, all held against a unit-economics ceiling so growth stays profitable, not just loud.
We build cohort-level unit economics before spend commits, not after the fact when the story’s already written. Payback period, contribution margin, and LTV:CAC ratio become live inputs to how budget gets allocated, updated as each cohort matures.
→ Cohort Payback Curves
→ Contribution Margin Models
→ LTV:CAC Threshold Gates
Structured tests across search, social, and programmatic, run with real statistical rigor and a control budget held back so you know what actually worked.
→ Search
→ Social
→ Programmatic
→ Attribution
Search
Most search accounts bleed budget on broad-match traffic nobody qualified. We rebuild around real intent tiers, kill the keywords that only look busy, and hold Quality Score as a lever, not a vanity number.
Social
Meta, LinkedIn, and TikTok spend usually competes against itself once retargeting and prospecting overlap. We fix the exclusions first, then iterate creative fast.
Programmatic
DSP buys layered on your own first-party audiences, run at a frequency we actually control, not whatever the platform defaults to.
Attribution
Cookie deprecation and ad blockers broke last-click months ago. We build multi-touch, server-side attribution tied to your CRM pipeline, not the ad platform's own dashboard.
Directional figures from performance marketing engagements over the past 24 months, split by business model, because a blended average hides more than it shows. Full engagement detail lives in our case studies.
−34%
B2B SaaS: average CAC reduction within the first two testing cycles
−41%
DTC / marketplace: average CAC reduction within the first two testing cycles
3.1x / 3.6x
Median LTV:CAC post-optimization — B2B SaaS / DTC & marketplace
45d
Typical time from kickoff to first statistically significant test read, both segments
Directional, not guaranteed — every business starts from a different baseline. See Work for the engagement-level detail behind these numbers.
Every performance marketing engagement follows the same sequence: model the economics first, test with discipline, then scale only what the data has already proven works — the same diagnose-before-you-build discipline that runs through every engagement.
We build the CAC/LTV model, audit whatever attribution you already have, and set the spend ceiling before a single campaign gets touched.
Controlled tests across search, social, and programmatic isolate what actually moves CAC, not what just looks good on a platform dashboard.
Winning channels get the budget; attribution gets hardened so every dollar stays traceable as spend scales up.
Go-to-Market Strategy
The positioning and channel priorities that performance marketing spend gets pointed at.
Retention & Ops
The lifecycle flows, lead scoring, and process work that turn paid traffic into pipeline after the click.
Further Reading
Why blended CAC and LTV numbers are close to useless, and what cohort-level reporting looks like instead.
No pitch, no pressure. Just clarity on what your CAC and LTV can actually support, and whether a project sprint or an ongoing performance retainer is the right fit. Scope and pricing depend on channel mix and testing cadence, so we work that out together on the call rather than guessing at it here.