A revenue-ready data product in 8 weeks
Objective
Build a modern, scalable analytics foundation that centralises product, marketing, and revenue data.
Obstacle
Rebrandly faced significant data infrastructure challenges that limited their ability to generate reliable insights.
Outcome
A fully modernised, automated analytics stack, complete with unified models for product and marketing data.
Background
Rebrandly is a global leader in link management and branded short URLs, serving customers ranging from individual creators to enterprise teams. As the business scaled, Rebrandly needed a data foundation capable of supporting fast-growing traffic, complex workspace-level user interactions, and multi-channel acquisition strategies.
Challenges
Fragmented Data: With an ecosystem spanning MySQL, S3, GA4, Google Ads, Salesforce, Stripe and Mixpanel, Rebrandly had no unified source of truth. Our audits identified gaps including missing user IDs blocking attribution, disconnected backend & frontend events and no centralised marketing spend vs. conversion linkage. This meant teams could not reliably answer basic questions like “Which marketing channels drive high-value accounts?” or “How do product actions correlate with revenue expansion?”
Siloed Insights: Each department owned isolated spreadsheets or dashboards, creating conflicting numbers across teams and preventing Rebrandly from scaling reporting efficiently. Blockers included: Stripe data not connected to product or marketing, Salesforce accounts not unified with usage patterns and Mixpanel identity mismatches between events.
Solution
Strategic Alignment: We partnered with senior leadership including: Product, Engineering, Marketing, and Revenue Ops to align on a unified set of KPIs and definitions.
This included building a comprehensive Data Dictionary and mapping all required models and metrics for the project, giving complete transparency on exactly how we would put together the models and what would be delivered.
Scalable Data Infrastructure: 173tech designed and delivered a modern analytics stack leveraging; Redshift as the central data warehouse, S3 + Redshift Spectrum for event data, Zero-ETL MySQL ingestion, Fivetran for Google Ads and Salesforce and then dbt in GitLab for modelling, testing, CI/CD. We engineered core dimension and fact tables covering: Users, Workspaces, Organisations, Subscriptions and Daily user activity. These tables became the backbone for product analytics, marketing attribution, and financial reporting.
Reverse ETL: Modelling data is the process of centralising and combing it into useful metrics and reverse ETL is the process of then sending those metrics back into the tools that teams use. As part of this project we used Census to send Product usage signals and Teammate activity back into Salesforce.
Impact
End-To-End Customer Journey Visibility: Rebrandly now has a complete, scalable data foundation powering analysis across every department. We have surfaced key dimensions across the customer journey from: From ad click → website session → signup → workspace activity → subscription revenue → churn, all stitched together for the first time. That means that all marketing and sales activity is fully attributed, product teams can understand usage signals and everything is tied back to customer value.
Our data modelling revealed that reactivated accounts had been counted within the new user base, inflating weekly paid conversion numbers by 40% – 75% and understating true customer acquisition costs. This misclassification was invisible in the previous reporting.
Supporting Internal Hiring: Centralising all of your sources can often take years. We ran a structured, multi-phase roadmap over several months, completing all major phases on schedule. With a new core analytics foundation in place we helped Rebrandly to onboard dedicated internal data resources, focused on delivering business value and not installing the basics.
Optimisation: We cloned databases for faster validation, introduced macros to minimise downtime during materialisation, and aligned Looker deployments and dbt branching within existing processes, all to enable BlueMatrix to scale this product in the future. Within 1 weeks of completion, the first external customer was scheduled for onboarding.
Creating Value For Rebrandly...
We reduced manual data requests by 80% ,
Unified five data sources tracking billions of links,
And discovered conversion numbers were inflated by up to 75%.
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