US HealthTech SaaS: 16 Hours Weekly Reporting Eliminated
A US-based HealthTech SaaS with 6 marketing channels and 5 disconnected reporting platforms was spending 16 hours every Monday on manual data consolidation, with conflicting numbers that no one in leadership could reconcile.
Published: April 2026 · Timeframe: 3 weeks
Company Overview
- Industry
- B2B SaaS / HealthTech
- Campaign Duration
- 3 weeks
- Primary Service
- Marketing Dashboard
- Type
- Growth-Stage HealthTech SaaS Platform
- Status
- Active Client
The Challenge
The client's marketing team of six was running campaigns across Google Ads, LinkedIn, Meta, and organic search, but had no unified reporting view. The Head of Marketing spent every Monday morning pulling data from five platforms into a shared Google Sheet that would be out of date by Tuesday afternoon. Worse, each platform reported conversions differently: LinkedIn showed 340 conversions in Q1, Google Ads showed 180, and GA4 showed 120, and no one could reconcile the numbers.
- 16 hours of manual reporting every Monday morning from 5 disconnected data sources
- LinkedIn, Google Ads, and GA4 each showing different conversion numbers for the same period
- No single source of truth, leadership meetings spent 40 minutes debating which number was right
- Marketing ROI unmeasurable: no view connecting channel spend to pipeline or revenue
- Reports outdated within 24 hours of publication, no real-time visibility
- No automated delivery, CEO and CFO received marketing updates only when someone remembered to share the sheet
Our Solution
Phase 1: Requirements Workshop & Data Model Design (Days 1–5)
We began with a structured requirements workshop to define exactly what each stakeholder needed to see, and built a normalised data model that could answer those questions consistently.
Stakeholder Requirements Workshop
Ran a 2-hour workshop with the CMO, CEO, and Head of Paid Media to define the three distinct dashboard audiences and their needs: the C-suite (ROI and pipeline), the paid media team (campaign performance), and the content/SEO team (organic growth). Each audience got a separate dashboard view.
Conversion Definition Standardisation
Resolved the multi-platform conversion discrepancy: LinkedIn, Google Ads, and GA4 all used different attribution windows and counted different actions. Established a single conversion definition (GA4 as source of truth with agreed attribution window) and documented why platform-native numbers will always differ, eliminating the Monday morning debate.
Normalised Data Model Build
Built a blended data model in Looker Studio connecting GA4, Google Ads, LinkedIn, and Meta via native connectors. Created consistent naming conventions, metric calculations, and attribution windows across all sources. The model updates automatically each night at midnight.
Phase 2: Dashboard Build (Days 5–15)
With the data model ready, we built three purpose-built dashboards, each designed for its specific audience and decision-making context.
Executive Dashboard
Built for the CEO and CFO: revenue pipeline from marketing, CAC by channel, MQL-to-SQL conversion rate, and month-to-date vs. target pacing. Designed to answer 'is marketing working?' in under 60 seconds. No raw numbers, no platform jargon, only commercial outcomes.
Campaign Performance Dashboard
Built for the paid media team: all campaigns across Google Ads, LinkedIn, and Meta in a single view. Sortable by ROAS, CPL, CTR, and spend. Budget pacing alerts highlight campaigns underspending or overpacing against monthly allocation. Saves 3 hours of individual platform checking per team member per week.
Organic Growth Dashboard
Built for the content and SEO team: keyword ranking trends, organic traffic by page, blog engagement metrics, and organic MQL volume. Connected GA4 goal completion data to specific content pieces to show which blog posts are generating actual pipeline.
Phase 3: Automated Delivery & Handover (Days 15–21)
Dashboards that require someone to open them get forgotten. We automated delivery to ensure the right data reaches the right people without requiring any manual action.
Automated Email Delivery
Configured scheduled email delivery: the Executive Dashboard renders as a PDF and lands in the CEO, CMO, and CFO inbox every Monday at 7am, before the weekly leadership meeting. The Paid Media Dashboard sends every Wednesday to the paid media team with the prior 7-day performance summary.
Team Handover & Documentation
Documented the full data architecture, connector configuration, and update schedule. Trained two team members on making dashboard edits. Set up a monitoring alert to flag if any data connector stops refreshing, preventing silent data gaps from undermining trust in the system.
Results & Impact
The full Monday morning data-consolidation process was replaced by an automated dashboard that updates overnight. Zero manual reporting hours required.
All marketing data, Google Ads, LinkedIn, Meta, GA4, organic, consolidated into a single normalised data model with three purpose-built dashboard views.
The multi-platform conversion discrepancy debate was eliminated. All stakeholders now reference the same source of truth with an agreed attribution model.
The CEO receives a rendered PDF dashboard before the weekly leadership meeting, no one has to remember to share it, and it never arrives after the meeting has started.
"We went from a Monday morning data fire drill to an automated dashboard that lands in the CEO's inbox before 7am every week. The reporting argument is over, everyone is looking at the same numbers from the same source. DigiBlazon built something we should have had two years ago."
Daniel Park
Head of Marketing, US HealthTech SaaS Platform
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