Maxoderm’s marketing team was drowning in disconnected data. Ad spend lived in Google Ads, call tracking scattered across spreadsheets, sales data buried in the CRM, and revenue metrics locked in financial systems. Nobody had a complete picture of what was actually working.
Data engineering, marketing analytics, dashboard development, API integration
Healthcare & Wellness Marketing
60 hours
20-12-2024
Centralized data pipeline via Apps Script to auto-fetch and merge data from Google Ads, Meta, GA4, CRM, and finance, eliminating manual work and standardizing all datasets.
Automated daily/weekly ETL triggers to extract, transform, and append campaign, call, and revenue data for real-time performance tracking.
AI logic handled anomaly detection, data normalization, and deduplication. Added advanced Looker Studio KPIs like MER, RPC, CPA+OB, and answered rates.
Built a Looker Studio dashboard showing spend trends, call metrics, approval/decline breakdowns, revenue attribution, and efficiency ratios.
Each API behaved differently, Google Ads throttled requests, Meta tokens expired, and the CRM timed out. We had to prevent these failures from breaking early-morning pipeline runs.
Metric names and formats varied widely across platforms. Terms like “Cost,” “Spend,” and “Total_Amount” differed, and date formats weren’t consistent, requiring translation and normalization.
The CRM often returned partial lead details. Revenue sometimes appeared before the marketing source, so we built logic to safely backfill missing data without duplication
The CRM often returned partial lead details. Revenue sometimes appeared before the marketing source, so we built logic to safely backfill missing data without duplication
With 50,000+ rows, Sheets slowed down. We designed an optimized, append-only data warehouse structure with automated archival to maintain performance.
With 50,000+ rows, Sheets slowed down. We designed an optimized, append-only data warehouse structure with automated archival to maintain performance.
Customers touched multiple platforms before converting. Tracking which campaign actually drove revenue, especially for Click-To-Call, required multi-touch attribution across disconnected systems.
The business impact showed up quickly. High-CPA campaigns got identified and paused, saving thousands in wasted spend. Marketing and sales teams are aligned around the same lead quality metrics. Budget allocation shifted toward campaigns with strong MER and RPC numbers. Reporting time dropped from hours to minutes since everything updates automatically. Maxoderm’s marketing team now operates with complete visibility into their Click-To-Call campaigns. They know which ads drive quality calls, which calls convert to sales, and which campaigns actually generate profitable revenue, all in real-time, all in one place.
