Use Case - Konfio
Use Case - Konfio
Use Case - Konfio
Transforming Marketing Analytics:
Unlocking Diagnostic Insights and ROI in 4 Weeks
Transforming Marketing Analytics:
Unlocking Diagnostic Insights and ROI in 4 Weeks
Transforming Marketing Analytics:
Unlocking Diagnostic Insights and ROI in 4 Weeks
Industry
Industry
Fintech
Fintech
Product
Product
Finance
Finance
Problem
Problem
Shallow Analytics
Shallow Analytics
Data Product
Data Product
Actionable Marketing Analytics
Actionable Marketing Analytics
The Challenge
The "Vanity Metric" Ceiling
Konfío, a leading Fintech providing corporate cards and financing, faced a critical blind spot in their growth engine. While their marketing team generated massive engagement across social platforms, they were stuck relying on static reports and "vanity metrics." They knew what was happening—likes, shares, and clicks—but they couldn't explain why it was happening. Without the ability to drill down into the data or compare performance across channels, strategy relied on intuition rather than evidence, leaving potential conversions and optimized ROI on the table.
Konfío, a leading Fintech providing corporate cards and financing, faced a critical blind spot in their growth engine. While their marketing team generated massive engagement across social platforms, they were stuck relying on static reports and "vanity metrics." They knew what was happening—likes, shares, and clicks—but they couldn't explain why it was happening. Without the ability to drill down into the data or compare performance across channels, strategy relied on intuition rather than evidence, leaving potential conversions and optimized ROI on the table.
The Cause
Data Fragmentation and Taxonomy Chaos
The root cause was a disconnected data ecosystem. Konfío operated across four major platforms (Facebook, Instagram, LinkedIn, and X), each speaking a different data language. A "photo post" on Facebook was defined differently than on Instagram, making apples-to-apples comparisons impossible. Furthermore, their existing tooling (Hootsuite) was excellent for scheduling but lacked the heavy-lifting capabilities required for deep, diagnostic analytics. With limited engineering resources to build custom pipelines, the team was trapped in manual spreadsheets, unable to distinguish between sticky content and random noise.
The root cause was a disconnected data ecosystem. Konfío operated across four major platforms (Facebook, Instagram, LinkedIn, and X), each speaking a different data language. A "photo post" on Facebook was defined differently than on Instagram, making apples-to-apples comparisons impossible. Furthermore, their existing tooling (Hootsuite) was excellent for scheduling but lacked the heavy-lifting capabilities required for deep, diagnostic analytics. With limited engineering resources to build custom pipelines, the team was trapped in manual spreadsheets, unable to distinguish between sticky content and random noise.
The Solution
A Unified, AI-Powered Intelligence Layer
We deployed a rapid-response data modernization tailored for speed and scalability. Using Fivetran, we automated the ingestion of all social data into Google BigQuery, bypassing the need for fragile, custom-coded pipelines.
Unified Taxonomy: We engineered a "Medallion Architecture" (L0–L3) that normalized disparate data definitions into a single, coherent language (e.g., standardizing "Post Type" across all platforms).
Looker Semantic Layer: We built dynamic dashboards that allow non-technical users to drill down from high-level trends to individual post performance instantly.
AI Integration: We leveraged Vertex AI and BigQuery ML to implement automated sentiment analysis, turning unstructured comments into quantifiable reputation metrics.
We deployed a rapid-response data modernization tailored for speed and scalability. Using Fivetran, we automated the ingestion of all social data into Google BigQuery, bypassing the need for fragile, custom-coded pipelines.
Unified Taxonomy: We engineered a "Medallion Architecture" (L0–L3) that normalized disparate data definitions into a single, coherent language (e.g., standardizing "Post Type" across all platforms).
Looker Semantic Layer: We built dynamic dashboards that allow non-technical users to drill down from high-level trends to individual post performance instantly.
AI Integration: We leveraged Vertex AI and BigQuery ML to implement automated sentiment analysis, turning unstructured comments into quantifiable reputation metrics.
Our Architecture
The Results
The Revenue Revelation
The transformation delivered immediate business value in just 4 weeks—finishing two weeks ahead of schedule. The new platform empowered Konfío to move from simply describing the past to diagnosing the drivers of success, leading to a significant increase in conversions from social channels.
Strategic Clarity: The data revealed that previous "engagement spikes" were actually driven by timing (holidays) rather than content stickiness, allowing the team to recalibrate their editorial calendar.
Risk Automation: The new AI-driven sentiment analysis now provides near real-time alerts on reputational risks, automating what used to be a manual review process.
The transformation delivered immediate business value in just 4 weeks—finishing two weeks ahead of schedule. The new platform empowered Konfío to move from simply describing the past to diagnosing the drivers of success, leading to a significant increase in conversions from social channels.
Strategic Clarity: The data revealed that previous "engagement spikes" were actually driven by timing (holidays) rather than content stickiness, allowing the team to recalibrate their editorial calendar.
Risk Automation: The new AI-driven sentiment analysis now provides near real-time alerts on reputational risks, automating what used to be a manual review process.