B2B FinTech · Push Payments Platform

Three channels, four audiences, one coordinated paid engine.

Checkbook.io competes in a category where the headline names — Modern Treasury, Bill.com, Stripe — have eight-figure paid budgets. The brief wasn't to outspend them. It was to out-coordinate them: match each audience to the channel where they actually research, where the cost-per-result was defensible, and build the cross-channel orchestration that compounded.

−41%

Blended CAC across paid

2.6×

Qualified opportunities sourced

3 channels

Coordinated · Google · Microsoft · LinkedIn

Industry

B2B FinTech · Push Payments

Market

United States

Channels

Google · Microsoft · LinkedIn

Engagement

Direct · ~6 mo

The Challenge

Four audiences, one budget, and category leaders spending eight figures on paid.

Checkbook.io serves four distinct audiences — insurance claim teams, marketplace operators, AP/finance leaders, and fintech developers — each with a different buying journey, a different research channel, and a different cost-per-result profile. The existing paid programme treated them all the same way, on the same channel, against the same generic keyword set.

Google Ads alone wasn't going to win. CPC on the obvious category terms ('ach payment platform', 'push payments API', 'b2b payment solution') had compressed margins to the point where blended CAC was sitting above target. Bill.com and Modern Treasury were spending into the same keyword pool with significantly larger budgets. Trying to out-bid them was a losing position.

The brief: build a paid engine where each audience encountered Checkbook in the channel that fit how they actually researched and decided. Reduce blended CAC. Add ABM capability to land named insurance and marketplace accounts. Do it inside the existing paid envelope — no budget increase.

The shape of the work

Three channels. Four audience tracks. One coordinated engine.

Checkbook.io

Push payments platform

Google Ads

High-intent search · 4 verticalised campaigns

Microsoft Ads

Lower-CPC mirror · Bing / Edge audience

LinkedIn ABM

500-account target list · Insurance + Marketplace

Compound outcomes

Each channel reinforced the others.

01
CAC −41%
02
CPQO −34%
03
Qualified opps 2.6×
04
ROAS 4.2× (12-mo)

Each channel was matched to where its audience actually researches. The compound came from cross-channel coordination — the same target account encountered Checkbook in the right context multiple times.

What Partner in Growth did

Match each audience to the right channel. Then build the cross-channel rhythm.

The six-month programme sequenced into five phases. Each one built on the last — and the cross-channel orchestration (phase 5) was what made the three channels compound rather than just stack.

01/ 05

Phase 1 — Audit & audience segmentation (weeks 1–3)

Mapped the four buyer journeys onto channel-fit signals.

Audited 18 months of existing Google Ads data — keyword, vertical, conversion path, CAC by audience.
Mapped buyer signals for the 4 priority audiences: Insurance claims (carrier + TPA), Marketplace operators (gig economy + B2B), AP / Finance leaders, Fintech developers (API).
Identified that ~52% of existing paid spend was going against keywords that produced low-LTV deals (generic SMB intent vs Checkbook's actual ICP).
Killed two campaign clusters producing volume but no qualified pipeline.

Outcome

A clear audience-to-channel matrix the team could rally around.

First time the marketing and sales leaders had a shared, evidence-backed view of which audiences belonged on which channel — and which existing campaigns were burning budget.

02/ 05

Phase 2 — Google Ads restructure (weeks 3–8)

Rebuilt the Google Ads programme around vertical-specific intent and high-LTV ICPs.

Structured 4 verticalised campaign tracks: Insurance Claims · Marketplace Payouts · AP / Finance Disbursements · Developer / API.
Tightened bidding around 32 priority keywords with proven ICP-fit intent (e.g., 'insurance claim payouts', 'mass disbursement platform', 'push to card api', 'ach payment alternative').
Built dedicated landing pages per vertical track — insurance buyers don't want to read AP / developer copy and vice versa.
Set up branded defence campaigns to protect against competitor bidding on 'checkbook' terms.

Outcome

Google CPC down, qualified-lead quality up.

~$18 → ~$11Avg CPC on priority terms (−39%)

+62%Qualified lead rate (CTR-weighted)

4 tracksVerticalised campaigns live

03/ 05

Phase 3 — Microsoft Ads parallel rollout (weeks 6–10)

Mirrored the priority Google keyword set into Microsoft Ads to capture the Bing / Edge audience — typically older, more enterprise, often in finance roles.

Replicated the 4 verticalised Google tracks into Microsoft Ads (Bing, Edge, partner search).
Took advantage of significantly lower CPC: Microsoft delivered comparable intent at ~47% lower cost per click on the same keyword pool.
Layered Microsoft Audience Network (display) for retargeting visitors who hadn't converted on the first search visit.
Used LinkedIn-data targeting inside Microsoft Ads (companies, industries, job functions) — a Microsoft-only capability since they own LinkedIn data.

Outcome

A second high-intent channel at meaningfully lower CPC.

~$6Avg CPC on Microsoft (vs ~$11 on Google)

+18%Incremental qualified leads (not cannibalising Google)

−47%CPC delta vs Google on same intent

04/ 05

Phase 4 — LinkedIn ABM layer (weeks 8–18)

Built a targeted ABM programme against named accounts in the highest-LTV verticals — insurance carriers and marketplace operators.

Built a 500-account target list: 280 US insurance carriers + TPAs, 220 marketplaces (gig, B2B, real estate, freelance).
Three campaign types per account segment: Sponsored Content (awareness), Conversation Ads (engagement), Message Ads (named-title outbound).
Created vertical-specific creative — insurance creative spoke claim-disbursement language, marketplace creative spoke payout-velocity language. No shared 'B2B payments' generics.
Coordinated LinkedIn audience with the Google + Microsoft retargeting pools — a target account hit on LinkedIn became a retargeting audience on search.

Outcome

320 of the 500 target accounts engaged inside the engagement window. Pipeline-fit improved sharply.

500 → 320 engagedTarget accounts reached (64%)

~28%Of paid pipeline tagged 'Insurance' vertical

Higher ACVABM-sourced deals closed above blended average

05/ 05

Phase 5 — Cross-channel orchestration + measurement (ongoing)

Built the operating rhythm that turned three channels running in parallel into one coordinated engine.

Set up unified attribution across the three channels — every touchpoint visible in the funnel view, no double-counting.
Weekly optimisation rhythm: budget reallocated across channels based on cost-per-qualified-opportunity (not cost-per-click vanity).
Sequenced the buyer journey: target account on LinkedIn → search retargeting on Google/Microsoft → demo conversion.
Built a dashboard the in-house team could run independently — weekly review cadence, monthly executive view.

Outcome

The three channels stopped competing for credit and started compounding.

Blended CAC dropped 41% — significantly more than the channel-level improvements would have produced separately. The compound came from orchestration: the same buyer encountered Checkbook in three contexts before the demo conversion.

How the programme progressed

Six months. Three channels. One engine.

Each phase was sequenced — and each unlocked the next. Trying to launch all three channels simultaneously would have produced volume without learning. Sequencing produced both.

Wk 1–301
Audit & segmentation
100Blended Cac (idx)
100Qualified Opps (idx)
Audience matrix locked. Two underperforming campaign clusters killed. ~52% of existing spend reallocated.
Wk 3–802
Google Ads restructure
88Blended Cac (idx)
118Qualified Opps (idx)
4 verticalised tracks live. Avg CPC down from ~$18 to ~$11 on priority terms.
Wk 6–1003
Microsoft Ads expansion
78Blended Cac (idx)
146Qualified Opps (idx)
Microsoft running at ~$6 CPC. Incremental qualified leads not cannibalising Google.
Wk 8–1804
LinkedIn ABM layer
68Blended Cac (idx)
192Qualified Opps (idx)
500-account target list engaged. ABM-sourced deals closing at higher ACV.
Wk 12–2405
Cross-channel orchestration
59Blended Cac (idx)
260Qualified Opps (idx)
Three channels coordinated. Blended CAC −41%. Qualified opps 2.6× starting baseline.

Before & After

What changed across paid acquisition in six months.

Pre-engagement: paid was almost entirely Google Ads, untiered by vertical, with no LinkedIn programme. Post-engagement: three channels, four audience tracks, one measurement framework.

Metric	Before	After	Δ Change
Active paid channels	1 (Google only)	3 (Google · Microsoft · LinkedIn)	+2 channels
Audience segmentation	Generic (B2B)	4 verticalised tracks	Vertical-specific
Blended CAC (vs baseline)	Baseline	−41% vs baseline	−41%
Cost per qualified opportunity	Baseline	−34% vs baseline	−34%
Qualified opportunities sourced (monthly)	1× baseline	2.6× baseline	+160%
Google Ads — average CPC (priority terms)	~$18	~$11	−39%
Microsoft Ads — average CPC (same terms)	—	~$6	−47% vs Google
LinkedIn — ABM target accounts engaged	0	320 (of 500 target list)	+64% reach of list
Vertical-tagged pipeline (insurance)	Untagged	~28% of paid pipeline	Clear vertical signal
Blended ROAS (12-mo trailing)	~1.8×	~4.2×	+133%

Active paid channels

Before

1 (Google only)

After

3 (Google · Microsoft · LinkedIn)

+2 channels

Audience segmentation

Before

Generic (B2B)

After

4 verticalised tracks

Vertical-specific

Blended CAC (vs baseline)

Before

Baseline

After

−41% vs baseline

−41%

Cost per qualified opportunity

Before

Baseline

After

−34% vs baseline

−34%

Qualified opportunities sourced (monthly)

Before

1× baseline

After

2.6× baseline

+160%

Google Ads — average CPC (priority terms)

Before

~$18

After

~$11

−39%

Microsoft Ads — average CPC (same terms)

Before

—

After

~$6

−47% vs Google

LinkedIn — ABM target accounts engaged

Before

After

320 (of 500 target list)

+64% reach of list

Vertical-tagged pipeline (insurance)

Before

Untagged

After

~28% of paid pipeline

Clear vertical signal

Blended ROAS (12-mo trailing)

Before

~1.8×

After

~4.2×

+133%

How they progressed — by the numbers

CAC −41%. Qualified opps 2.6×. ROAS 4.2×.

Inside six months, blended CAC across paid acquisition dropped 41% and the qualified-opportunity volume sourced from paid grew to 2.6× the starting baseline. Cost per qualified opportunity dropped 34%. Twelve-month trailing ROAS climbed from approximately 1.8× to 4.2× as the cross-channel engine matured.

The structural outcomes matter as much as the headlines. Microsoft Ads delivered comparable intent at ~47% lower cost per click than Google — a permanent channel cost advantage that scales. The LinkedIn ABM programme reached 320 of 500 named target accounts (64%) and produced deals that closed at higher ACV than the blended average. And by month six, the three channels were running on a unified attribution view and a weekly optimisation rhythm the in-house team could operate independently.

−41%

Blended CAC

Across all paid channels

2.6×

Qualified opportunities

Monthly run rate

−34%

Cost per qualified opp

Compounded across channels

−39%

Google CPC (priority terms)

~$18 → ~$11

−47%

Microsoft CPC vs Google

Same intent, lower cost

320/500

ABM target accounts engaged

Insurance + marketplace

4.2×

Blended ROAS (12-mo)

Up from ~1.8×

Paid acquisition strategy walkthrough

Walkthrough coming soon

How Checkbook.io built a coordinated three-channel paid engine without outspending the category

60–90s explainer. Suggested arc: 1) the four-audience challenge inside one paid budget, 2) why Google alone wasn't going to win, 3) the three-channel + four-vertical matrix in 20s, 4) the CAC −41% / opps 2.6× / ROAS 4.2× outcome trio.

Related case studies

View all

FinTech · Payments SaaS

From dormant channel to 54× compound growth

54×

TOFU & BOFU growth · 6 months

B2B SaaS Series A

From paid-dependent to multi-channel demand engine

−38%

Blended CAC

Out-coordinate the category, don't out-bid it

When your competitors have bigger paid budgets, the answer is sequencing — not spending.

Most paid programmes treat every audience the same on every channel. The wins compound when each audience meets the brand on the channel where they actually research — and the channels are sequenced into one engine, not three parallel motions. A 30-minute call will tell you which of your channels is doing real work, and which is burning budget against category leaders you can't out-bid.

Book a strategy call