Pipeflow CRM is a fictional company. This audit is based on patterns we see regularly in SaaS paid acquisition accounts. Your actual audit will be built entirely from your real data, campaigns, and funnel — no assumptions, no generic findings.

PPC Audit — Pipeflow CRM
Example audit — B2B SaaS
Pipeflow CRM was spending $25k/month.
Here's exactly what we found.
A solid product, a real sales team, and a paid acquisition channel quietly bleeding money. This is what the account looked like before we touched it — and what needed to change.
$25,000 / month ad spend Google Ads & Meta B2B SaaS — CRM
Where things stood before the audit
Blended CAC
$940
Healthy: $300–500
CAC payback
14 mo
Healthy: 6–9 mo
Trial-to-paid
9%
Healthy: 20–30%
LTV:CAC ratio
1.8x
Healthy: 3x+

At these numbers, paid acquisition isn't growing the business — it's taxing it. A 14-month payback period means every new customer costs 14 months of margin before they turn profitable.

Blind Scaling — No Unified Data, No Real Numbers
Layer 1 — Revenue & Market Intelligence
The data was fragmented — CAC was a guess, not a number

Google Ads, Meta, and the CRM were all living in separate tabs. CAC was being calculated manually in a spreadsheet, updated once a month. By the time anyone noticed spend had crept up, weeks of budget had already gone the wrong direction.

Impact

Every optimization decision was being made on lagging, incomplete data. Google Display was spending $6,200/month generating $1,200 in MRR — invisible until everything was unified.

What we did
  • Connected Google Ads, Meta, and CRM into a single real-time dashboard
  • Ran full quantitative analysis — true CAC, payback period, LTV:CAC, MRR per channel, funnel conversion at every stage
  • Ran qualitative analysis — cancellation surveys, behavior patterns, onboarding drop-off — to understand why people weren't converting
  • Passed revenue values back to Google and Meta so bidding optimized for paying customers, not just trial signups
The unified dashboard we built — explore it
app.webriv.io/dashboard/pipeflow-crm
Overview
Channels
Funnel
AI Alerts 3
Blended CAC
$940
↑ 18% vs last month
CAC Payback
14 mo
Benchmark: 6–9 mo
MRR (paid)
$8.2k
↑ 4% vs last month
LTV:CAC
1.8x
Benchmark: 3x+
MRR vs Ad Spend — last 6 months
CAC by channel
AI alert: Google Display spend up 22% this week with no MRR movement. Recommend pausing and reallocating to Search.
Click the tabs above — Overview, Channels, Funnel, and AI Alerts are all live
The Funnel Was Leaking From Every Direction
Layer 2 — Acquisition Efficiency & Conversion Engineering
The ads were talking about the product. Nobody cared.

Every headline was feature-led. "Powerful CRM Dashboard." "Automated Follow-Up Tools." These aren't things a sales manager searches for when their team keeps losing deals. The ads were answering questions nobody was asking.

Impact

CTR at 1.17% when the benchmark is 3–5%. Thousands of dollars in impressions that never turned into clicks.

What we'd fix
  • Rewrite all headlines around outcomes: "Stop Losing Deals to Poor Follow-Up," "The CRM Your Sales Team Will Actually Use"
  • Add social proof — G2 rating, customer count, trust signals in ad copy
  • Test specific CTAs: "Start Free 14-Day Trial" instead of "Get Started"
  • Run 8–10 meaningful headline variations per RSA, not 3 recycled versions
Ad copy — what was running vs what should run
Current — feature-led
"Powerful CRM Dashboard"
"Automated Follow-Up Tools"
"Pipeline Management Software"
CTA: Get Started · CTR: 1.17%
Rewritten — outcome-led
"Stop Losing Deals to Poor Follow-Up"
"Close More Without Adding Headcount"
"The CRM Your Team Will Actually Use"
CTA: Start Free 14-Day Trial · Target: 3–5%
The landing page was losing 96 out of every 100 clicks

Generic hero, no social proof above the fold, a 5-field form asking for phone and LinkedIn before anyone had seen the product, and 4.2 second load time on mobile. Every one of those things was a reason to leave.

Impact

4.1% conversion rate against an 8–12% benchmark. The traffic wasn't the problem — what happened when it arrived was.

What we'd fix
  • Rewrite the hero around what the visitor actually wants, not what the product does
  • Move social proof above the fold immediately
  • Cut the form to email only — every extra field kills conversion rate
  • Fix page speed to under 2 seconds
  • Add a secondary path: "Watch a 3-minute demo" for people not ready to trial
Trial users were being acquired and then abandoned

No welcome sequence. No onboarding emails. Average user logged in 2.3 times during a 14-day trial and disappeared. 61% of cancelled trials said "didn't have time to figure it out." That's not a product problem — that's an onboarding problem costing them every single day.

Impact

Trial-to-paid at 9% when it should be 20–30%. The CAC had already been paid. The conversion was being lost for free.

What we'd fix
  • Define a single activation milestone — first pipeline, first deal moved, first teammate invited
  • Build a 3-email onboarding sequence to get users there within 72 hours
  • Replace generic feature tours with prompts that drive the one action that matters
  • Add a personal touchpoint for high-intent trial users
Funnel breakdown — where the drop-off happened
Clicks / month
2,100
—
Landing page CVR
4.1%
Bench: 8–12%
Trial signups
87 / mo
—
Onboarding CVR
36%
Bench: 60–70%
Trial-to-paid
9%
Bench: 20–30%
The Campaign Infrastructure Was Working Against Itself
Layer 3 — Multi-Channel PPC Management & Scaling
Everything was in one campaign — which made everything invisible

Search, Display, YouTube, and PMax all running together. Branded and non-branded keywords competing in the same ad groups. 40+ keywords across 3 ad groups. The result was a blended performance number that looked passable on the surface but hid the fact that certain channels were actively losing money.

Impact

Display was spending $6,200/month generating $1,200 in MRR. That only became visible once the data was properly separated.

What we'd fix
  • Separate Search, Display, YouTube, and PMax into individual campaigns immediately
  • Split branded vs non-branded — each needs its own visibility and budget control
  • Rebuild ad groups around tightly themed clusters of 5–10 keywords max
  • Feed PMax with first-party signals — paying customers, trial users, high-value visitors
Google Ads — what the account structure actually looked like
Google Ads
Search
Reports
Tools
P
All campaigns › Pipeflow CRM — Jan 2024
!
Campaign structure issue detected — Search, Display, and PMax traffic are mixed into a single campaign, making optimization impossible.
Overview
Recommendations
Insights
Campaigns
Ad groups
Ads
Keywords
Jan 1 – Jan 31, 2024 ▼
 Campaign Status Budget Type Clicks Impr. CTR Avg. CPC Cost Conv. Conv. rate
Total — all campaigns — — 1,847 157,420 1.17% $13.51 $24,960 87 4.71%
Main Campaign — Mixed
⚠ Search + Display + YouTube blended
Enabled
Needs separation
 $600/day Mixed ⚠ 1,204 102,890 1.17% $15.45 $18,600 51 4.24%
PMax — General
⚠ No audience signals configured
Enabled
Blind targeting
 $213/day PMax ⚠ 643 54,530 1.18% $9.95 $6,400 36 5.60%
Showing 2 of 2 campaigns · Should be rebuilt into 5 focused campaigns

Rebuilt architecture — what this should look like:

Search — branded Search — non-branded Display YouTube PMax + audience signals
Meta was running to an audience of 45 million — and nobody warmer

One broad interest audience. No lookalikes from paying customers. No retargeting for people who had already visited, started a trial, and left. The warmest leads in the entire funnel were getting zero paid follow-up.

Impact

Meta CAC at $1,120 — more than double where it should be — because the highest-converting audiences weren't even running.

What we'd fix
  • Build customer lookalike audiences immediately — consistently the lowest-CAC Meta audience
  • Launch retargeting for website visitors and trial abandoners
  • Test UGC-style and talking-head video creative against current static images
  • Let strong creative do the audience filtering instead of interest targeting at 45M+
Meta audience tiers — what was and wasn't running
Customer lookalikes not running
Built from paying customers — highest purchase intent
Lowest CAC
Retargeting — warm audiences not running
Website visitors + trial abandoners who already know the product
Mid CAC
Broad interest — 45M+
Only audience active — cold, expensive, low-intent
Highest CAC

What we'd fix first — in order

  • 1
    Build the unified dashboard and fix attribution
    Can't optimize what you can't see — this unlocks everything else
  • 2
    Separate campaign types and add a negative keyword list
    20–30% reduction in wasted spend, usually within 30 days
  • 3
    Rewrite ad copy and fix the landing page
    CTR and landing page CVR both move toward benchmark range
  • 4
    Build the trial onboarding sequence
    Trial-to-paid moves from 9% toward 20%+ — the CAC was already paid
  • 5
    Launch Meta retargeting and lookalike audiences
    Recover warm leads currently being left on the table
Where these metrics should land after fixes
Blended CAC
$940
$500
CAC payback
14 mo
7 mo
Trial-to-paid
9%
21%
LTV:CAC
1.8x
3.2x
Pipeflow CRM is a fictional company. This audit is based on patterns we see regularly in SaaS paid acquisition accounts. Your actual audit will be built entirely from your real data, campaigns, and funnel — no assumptions, no generic findings.