Industry: B2B SaaS · Vertical Fintech | Stage: Series B | Engagement: Growth AI retainer | Timeline: 5 months to 3x activation
Composite company profile
A Series B vertical fintech SaaS platform selling embedded payment and reconciliation workflows to mid-market accounting teams. Headquartered on the US East Coast, roughly 90 employees at engagement start, ARR band $8M-$14M, average annual contract value between $18K and $42K depending on volume tier. The company had raised a $32M Series B eighteen months prior and was under board pressure to convert a top-of-funnel that looked healthy on paper into activated, paying accounts.
Client identity protected under NDA. Details available under mutual sign-off in a discovery call.
The problem
On paper the funnel looked fine. Around 1,400 free-trial signups per month, a well-instrumented product, and a paid media program that had been running for two years. The board saw the top-line MQL number and asked why net-new logos were not scaling.
The real problem sat between signup and paid activation. Trial-to-paid conversion was 4.1 percent against a segment benchmark closer to 11 percent. CAC had drifted from $6,200 the prior year to $9,800 in the trailing quarter. Sales was blaming lead quality. Marketing was blaming sales follow-up. Product was blaming both.
Two prior efforts had failed to move the number. An offshore SDR pod was added in Q2 and produced volume without lift. A LinkedIn thought-leadership push generated impressions but no measurable pipeline. The internal team had a strong instinct that activation was the bottleneck but no instrumentation to prove it or fix it.
What our team diagnosed
Vance oversaw the engagement. Our analytics and revops leads ran a two-week diagnostic before we shipped a single deliverable. Three findings surfaced that the client had not seen on their own.
First, the activation event the client used in their dashboards (account created, first data source connected) was not the event that predicted retention. When we ran a cohort analysis across twelve months of product data, the real predictor of a 12-month paid retention was a specific three-step sequence completed inside the first eight days of trial. Only 9 percent of trial users completed that sequence. The dashboard event was hitting 61 percent and telling a false story.
Second, paid traffic and organic traffic were converting at wildly different rates and the client was allocating spend based on blended numbers. Organic trial signups converted to paid at 8.9 percent. Paid signups converted at 1.6 percent. The blended 4.1 percent number hid a paid channel that was actively unprofitable on a CAC-to-LTV basis.
Third, the top three intent keywords the client was bidding on were being cannibalized by five thin comparison pages on the client’s own domain. Google was serving those pages instead of the money pages, and the money pages carried the demo CTA that actually converted.
Strategy MV3 shipped
We proposed a Growth AI retainer with four workstreams running in parallel. The client engaged all four in month one.
- Activation redesign. Reinstrument the product analytics stack around the real activation sequence. Rebuild the in-product onboarding to compress that sequence from eight days to three.
- Paid rebuild. Kill 60 percent of paid keyword spend. Reallocate to a smaller, higher-intent keyword set with dedicated landing pages and a segmented signup path.
- SEO cannibalization fix. Consolidate the five thin pages into two canonical money pages. Rebuild internal linking. Publish six new mid-funnel comparison assets targeting the real buyer questions.
- Lifecycle sequence. Build a nine-touch trial-nurture sequence keyed to the activation event, not to signup date, so a user who stalled at step two got a specific unblock message rather than a generic reminder.
Implementation
Our team executed under a weekly cadence with a Monday planning sync and a Friday review. Deliverables shipped inside the client’s tools where possible so their team owned the artifacts after the engagement.
- Analytics rebuild in the client’s existing product analytics platform (event schema, funnel definitions, retention cohorts), completed in weeks one through three.
- In-product onboarding rewrite delivered as a spec, wireframes, and copy. Client product team shipped the build in weeks four through seven.
- Paid restructure across Google Ads and LinkedIn Ads with new campaign structure, four rebuilt landing pages, and a segmented lead router. Live in week two.
- SEO consolidation and six new mid-funnel articles, 1,800 to 2,400 words each, with FAQPage and Article schema. Shipped across weeks two through nine.
- Lifecycle sequence built in the client’s marketing automation platform, keyed to product events via a webhook bridge our revops team specified.
Outcomes
Measured at the end of month five against a matched 90-day baseline period before engagement start.
- Trial-to-paid activation rate lifted from 4.1 percent to 12.7 percent (roughly 3.1x). This is the primary outcome the engagement was scoped against.
- CAC dropped from $9,800 to $4,150, a 58 percent reduction, driven mostly by the paid rebuild and the activation lift.
- Organic trial signups grew 41 percent as the consolidated money pages recaptured the intent keywords. Two of the three target keywords moved from page-two positions into the top three.
- MQL-to-SQL conversion moved from 22 percent to 38 percent because the lifecycle sequence pre-qualified users on real product usage rather than form-fill behavior.
- Payback period on new paid logos compressed from 14 months to 6 months, unlocking a board conversation about scaling paid spend rather than cutting it.
Timeline
Kickoff to the 3x activation result took 22 weeks. Diagnostic in weeks one and two. First quick wins (paid restructure, analytics rebuild) live by end of week three. Onboarding rewrite live in week seven. SEO consolidation complete by week nine. Lifecycle sequence live in week five. The activation number crossed the 12 percent threshold in week 19 and held through the measurement window in weeks 20 through 22.
What the client said
“We spent eighteen months trying to fix this internally and we could not get past our own dashboards. The diagnostic in the first two weeks reframed the problem in a way that made the fix obvious. What I appreciated most was that the team shipped inside our tools so we owned everything at the end.” — Priya, VP of Growth.
NDA framing
Client identity protected under NDA. Numeric outcomes are actual, verified against the client’s production data. Composite framing on company profile and quote is used across all MV3 case studies to protect client confidentiality. Full details, including the client name and a reference call, are available under mutual sign-off in a discovery conversation.
Ready to fix your own activation gap?
If your trial-to-paid or free-to-paid activation rate is stuck under 8 percent and you suspect the dashboard is telling you a false story, we run a two-week diagnostic as the first phase of every Growth AI engagement. It ends with a written root-cause document and a shipped-in-30-days remediation plan.
Book a discovery call → or explore the Growth AI retainer.
