Pipeline Intelligence
Role on this engagement
The data foundation. Server-side GTM, GA4 rebuild, BigQuery, and the HubSpot-to-ad-platforms offline conversion loop.
See the serviceIRONSCALES
Cybersecurity · Email Security
Inbound Pipeline Growth
Pipeline Intelligence
2.3× pipeline in 90 days.
Rebuilt the campaign infrastructure on first-party data activation. The bid algorithm stopped optimizing for form-fills. Started optimizing for opportunities.
92%
increase in MQLs for the same cost per MQL
2.3×
increase in marketing-attributed pipeline
227%
increase in marketing-sourced pipeline
The company
About IRONSCALES.
IRONSCALES is a self-learning email security platform that protects organizations from phishing, business email compromise, and account takeover at scale. The product sits inside the email security category — alongside Proofpoint, Mimecast, and Abnormal — and competes on AI-driven threat detection plus security awareness training built into the same platform.
The buyer is the security buying committee: CISO, security architect, IT director. The sales motion is named-account driven, with significant inbound demand from buyers actively evaluating the email security category.
The problem
The problem.
What the dashboards said
Click-through rates healthy
Lead volume trending up
Spend-to-conversion ratio stable
What the pipeline review said
CRM conversion data didn't reconcile
Bid algorithms training on form-fills
Pipeline not moving proportionally
IRONSCALES faced challenges growing their Marketing Qualified inbound leads and marketing-sourced pipeline. The campaign metrics looked healthy on paper. The pipeline review told a different story.
The ad platforms were optimizing against form-fill data that didn't translate to opportunities. The team needed the bid algorithms to see deal outcomes — not lead-gen events. That meant rebuilding the data infrastructure underneath the paid program before any campaign work could move the pipeline number.
The work
What we built.
Three components, deployed in 90 days. Each works on its own — but the system is what moved pipeline.
Component 01
Server-side measurement foundation.
Server-side GTM container deployed. Event taxonomy redesigned for B2B funnel logic, not e-commerce defaults. GA4 cleaned and rebuilt around real conversion events. Data piped to BigQuery for ownership and zero sampling.
sGTM
GA4
BigQuery
Component 02
HubSpot offline conversion integration.
Lead-to-CRM stitching verified end-to-end. HubSpot deal-stage events — MQL, SQL, Opportunity, Closed-Won — pushed to Google Ads via offline conversion uploads. Same event stream piped to LinkedIn Conversions API. Microsoft Advertising added for harvest-channel coverage.
HubSpot
Google Ads OC
LinkedIn CAPI
Component 03
Value-based bidding and audience refinement.
Conversion values assigned per CRM stage. The bid algorithm started bidding harder on accounts that close, not contacts that convert. ICP audiences rebuilt against closed-won lookalikes — modeling what a real buyer looks like, not a high-volume form-filler.
Value-based bidding
Lookalike audiences
The outcomes
What changed in 90 days.
2.3×
pipeline in 90 days.
Marketing-attributed pipeline more than doubled in the first 90 days, driven by deeper-funnel signal feeding the bid algorithms.
92%
more MQLs, same cost per MQL.
MQL volume nearly doubled within 90 days while cost per MQL held flat. Same paid budget, twice the qualified pipeline input.
227%
increase in marketing-sourced pipeline.
Pipeline sourced from marketing tripled over the engagement window. The 1st-party data infrastructure made every campaign decision more accurate.
What it meant for the team.
The new campaign structure plus 1st-party data activation produced compounding pipeline growth — without raising paid media spend. Every new conversion fed back into the bid algorithm, sharpening targeting on accounts that actually close.
The customer voice
In their words.
“VertoDigital helped us achieve sizable MQL growth from paid channels in just 3 months. Their expertise in activating our first-party data infrastructure and attention to lead quality were invaluable in optimizing our paid investment.”
Grant Ho
CMO, IRONSCALES
The services
The services behind the work.
The IRONSCALES program ran across the inbound stream, with the data layer built by the Pipeline Intelligence team.
Paid Search
Role on this engagement
The harvest channel. Value-based bidding tied to deal-stage signals. The bid algorithm trained on opportunities, not lead-gen events.
See the serviceLinkedIn Paid Social
Role on this engagement
The awareness layer. ICP audiences rebuilt against closed-won lookalikes. Bid algorithm trained via LinkedIn Conversions API.
See the serviceFree · 5 business days · No commitment
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