Oct 1, 2024
Data Modeling
Unified Product Tracking Model
Unify product tracking into a scalable, validated model
dbtCloud
SQL
Metabase
Context
As a specific post-sales product gained relevance with a growing client base, analysis became fragmented—driven by ad-hoc queries on raw data tailored to each objective.
This led to constant maintenance and limited scalability, making it harder to meet increasing demand from Sales.
Action
I spotted this recurring pattern of mini-requests and proposed reprioritizing quarterly initiatives to build a centralized solution.
To address this, I developed a data model that unified Sales information into a single source of truth—validated, structured, and easy to maintain.
I then consolidated the Sales Hub, our main dashboard for Sales, standardizing the tracking of key metrics like client conversion, Energy Expert performance, KR and SLA compliance—enabling segmentation by client type, product type, and multiple levels of granularity (dates, stages, agents, etc.).
Result
The model enabled no-code, self-service analytics through Metabase questions, speeding up insights and reducing operational reliance.
All relevant Sales metrics are now centralized in a single, reliable dashboard: Sales Hub.
Behind the screen
I’m Alonso, but people call me Alo — curious by nature, strategic by instinct. I like asking better questions, solving real problems, and building stuff that actually helps.
Not a fan of busywork
— I’m all about clarity, good systems, and tiny details that make things just… work.
Right now, I’m focused on working smarter, learning fast, and creating value where it matters most.
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