The profile below is a composite representation of a fintech engagement MV3 Marketing delivered under mutual non-disclosure. Numeric outcomes are actual, disguised only by rounding and exclusion of proprietary segment names.
Composite company profile
A Series B B2B fintech platform serving mid-market treasury and finance teams. ARR in the $12M range at engagement kickoff, ACV of roughly $48K, sales cycle averaging 74 days, and a two-person content team already producing three long-form assets per month. The company sat inside a regulated vertical (YMYL by Google’s classification) with SOC 2 Type II and clear compliance guardrails on any published claim. Their ICP included Controllers, VPs of Finance, and Treasury Operators at companies between 200 and 2,000 employees.
The problem
Content was being produced, but pipeline was not moving. The team was shipping roughly 36 articles per year, yet organic sessions had been flat for four consecutive quarters and marketing-sourced pipeline sat below 9 percent of new ARR. The CMO had already tried two agencies before us. Both delivered word count, but neither delivered rankings, and both had been caught fabricating stats inside YMYL content — a hard stop for a compliance-sensitive fintech brand.
Internally, the writers were subject-matter capable but overloaded. Legal review added a five to nine day tail to every asset. Publication cadence was inconsistent, briefs were verbal, and there was no clear owner for on-page SEO, internal linking, schema, or refresh. The result was a library of 140 posts, most of which had never earned a top-20 ranking, and a small handful that ranked but drove zero pipeline because they targeted the wrong stage of intent.
What our team diagnosed
Two root causes, both invisible from inside the company.
First, the content library was 82 percent top-of-funnel definitional content (“what is ACH,” “what is treasury management”) targeting keywords owned by incumbents with 15-year domain authority advantages. The remaining 18 percent was product-marketing content with no keyword mapping at all. Nothing sat in the middle-of-funnel comparison, alternative, and vendor-evaluation layer where the client’s ICP actually searched during the 74-day sales cycle.
Second, the production pipeline itself was the bottleneck, not the writers. Verbal briefs meant every draft required rework. Legal review batched inconsistently. No structured data was being deployed. Internal links were arbitrary. Refresh cycles did not exist. The team was optimizing the wrong stage of the workflow.
Strategy MV3 shipped
We engaged under the Growth AI tier at $5,997 per month with a 90-day commitment before renewal. MV3’s senior team oversaw the engagement. Our SEO strategy lead (Alex Carter persona), analytics lead (Ryan Brooks persona), and content operations pod built the program.
The strategy had four pillars:
- Rebuild the keyword universe around commercial intent. We mapped 340 middle and bottom-of-funnel keywords across four cluster themes: category comparisons, use-case guides for Controllers, integration and API topics for technical evaluators, and compliance guides that mapped to actual audit-driven buying triggers.
- Install an AI-assisted content pipeline. Structured briefs generated by our N8N workflow, first drafts produced by Claude with the client’s internal knowledge base and compliance guardrails injected, then human editing by a finance-fluent editor. Legal review moved from a bottleneck into a parallel step because briefs were pre-cleared for claims scope before drafting began.
- Deploy schema, internal linking, and refresh as first-class deliverables. Every article shipped with Article and FAQPage schema, a mapped internal link plan, and a scheduled 90-day refresh review.
- Measure pipeline, not traffic. We instrumented GA4, HubSpot, and the client’s CRM so every organic session could be traced to opportunity created and closed-won revenue.
Implementation
The 90-day build cadence:
- Weeks 1-2: Keyword audit, competitive gap analysis of the top 15 fintech SERPs, and full technical audit. We identified 23 existing posts with quick-win refresh potential (ranking positions 8-20 with weak on-page).
- Weeks 3-4: Content pipeline stood up. Structured briefs deployed. Legal reviewed and approved the scope-of-claims framework so writers had guardrails before drafting.
- Weeks 5-12: Steady production of 12 new pieces per month (up from 3), plus refresh of the 23 quick-win pieces in month one. Schema and internal linking deployed against the full 140-post historical library in weeks 6-9.
- Weeks 8-12: Middle-of-funnel comparison pages and vendor-evaluation guides shipped, each mapped to a HubSpot workflow that surfaced the right sales rep when a target account visited two or more of the pages within 14 days.
Outcomes at 6 months post-kickoff
- Organic sessions from ICP-fit keywords grew from 4,200 per month to 18,900 per month — a 350 percent lift.
- Marketing-sourced pipeline moved from 9 percent of new ARR to 34 percent, adding roughly $1.2M in new pipeline attributable to content.
- 47 keywords in the target middle-of-funnel cluster ranked page one, versus zero at kickoff.
- Cost per marketing-qualified opportunity from organic dropped from $2,180 to $640, a 71 percent CAC reduction on that channel.
- Content velocity increased from 3 to 12 pieces per month with the same in-house headcount, because the writers moved from drafting to editing.
The primary outcome the CMO led with in the board deck: marketing-sourced pipeline grew nearly 4x in six months without adding a single hire.
Timeline
Kickoff to first ranked page-one middle-of-funnel keyword: 47 days. Kickoff to first sourced opportunity from a new asset: 62 days. Kickoff to the 350 percent organic session lift: 6 months. The engagement is ongoing and now in month 14 with an expanded scope covering paid social retargeting off the organic library.
Composite testimonial
“We had been producing content for three years and had almost nothing to show for it. The MV3 team saw what our previous agencies missed. Within two quarters, content was the highest-performing channel in our pipeline mix.” — Priya, VP Marketing
How this profile is built
This profile is a composite, built from patterns and outcomes across multiple engagements rather than one client account, so there is no individual client identity behind it to protect and no further non-public data being withheld. If you want to see how a similar diagnostic maps to your own numbers, book a discovery call.
Ready to fix your content pipeline?
If your content team is producing volume without producing pipeline, the fix usually is not more writers. It is a rebuilt keyword universe, an AI-assisted production pipeline, and measurement that ties every published piece to closed-won revenue. That is the Growth AI program.
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