Key outcomes:

• 15 hours per week of manual data gathering and reporting eliminated — equivalent to two working days of an analyst.
• All marketing data from 14+ platforms consolidated into one BigQuery setup, creating a single source of truth.
• Attribution accuracy increased by 43% thanks to Algorithmic Multi-Touch Attribution (MTA), which revealed true channel contribution versus last-click.
• Real-time performance dashboards replaced static reports, reducing time-to-insight from days to minutes.

Andreas Waldmann

Chief Marketing Officer (CMO), Kueski

“Windsor.ai transformed how we understand marketing performance. Multi-touch attribution showed us that channels we thought weren’t working were actually driving our most valuable customers. This insight alone saved us $2.8M annually and helped us scale our loan business more efficiently than ever.”

About the client

Kueski is Mexico’s leading fintech company, offering innovative financial solutions such as personal loans, credit lines, and digital payment services to millions of consumers. As one of Latin America’s fastest-growing fintechs, Kueski relies on multiple digital channels to acquire new customers and drive loan applications.

Challenges

As Kueski scaled its marketing operations, the team faced several roadblocks:

• Attribution blind spots: With campaigns across Apple Search Ads, Google Ads, Facebook, TikTok, Pinterest, Bing, Criteo, and more, it was difficult to see which touchpoints drove high-quality loan applications.
• Data silos: Marketing data was spread across 14+ platforms with no unified view of performance.
• Manual reporting: Analysts spent over 15 hours weekly gathering data and building reports manually.
• Budget misallocation: Media spend was based on last-click attribution, undervaluing awareness channels.
• Complex conversion tracking: The full journey from ad click to “Loan application submitted” and “New user conversion” was highly fragmented.

These challenges drained valuable analyst hours and limited Kueski’s ability to make timely, data-driven decisions regarding campaign and budget optimization.

Solutions

To unify its marketing performance data and achieve accurate attribution, Kueski turned to Windsor.ai. Initially adopting Windsor when it was primarily an MTA platform, Kueski later expanded its use to include Windsor’s full data integration capabilities.

Key features utilized

1. Data integration

Data sources connected to BigQuery through Windsor.ai’s native connectors:

• Paid search & social: Apple Search Ads, Google Ads, Bing Ads
  
• Social media: Facebook, Instagram, TikTok, Twitter, Pinterest
  
• Programmatic: Criteo
  
• Organic & analytics: Google Analytics 4, Facebook Organic
  
• Monitoring & reporting: Datadog, Google Sheets
  
• Attribution events: Loan application submitted and New user conversions
  

2. Multi-touch attribution

• Upper-funnel channels (TikTok, Pinterest, Facebook awareness) contributed 41% more value than last-click showed.
  
• Search campaigns were being over-credited by 28%.
  
• Cross-device journeys accounted for 52% of conversions.
  

3. Real-time monitoring

• Automated daily reports.
  
• Automated performance alerts.
  
• Integration with Datadog for technical monitoring.
  

4. Advanced conversion tracking

• Attribution was mapped to both “Application Submitted” and “New User” events.
• Conversion events were directly linked to loan approval outcomes.
  

Results

Thanks to Windsor.ai’s automated pipelines and MTA, Kueski achieved the following results:

Attribution accuracy

• +43% accuracy with MTA vs. last-click.
  
• Found that 57% of conversions labeled “direct” actually came from paid campaigns.
  
• TikTok and Bing, previously undervalued, drove 23% of high-value loan applications.
  

Operational impact

• 15 hours/week saved on reporting.
  
• Real-time performance tracking across all channels.
  
• 87% faster budget decisions, reducing time-to-insight from days to under 30 minutes.
  

Customer journey insights

• Average of 4.2 touchpoints before a loan application.
  
• Facebook + Google Ads combined drove 34% higher conversion rates than either alone.
• Apple Search Ads performed best for direct response, while TikTok excelled at awareness and consideration.

Business impact

With Windsor.ai, Kueski:

• Strengthened its market share in Mexico’s competitive fintech space.
  
• Increased customer acquisition efficiency, achieving 23% QoQ growth.
  
• Embedded data-driven marketing as a core competitive advantage in LATAM fintech.
  

Future plans

Kueski is expanding its Windsor.ai setup to:

• Build predictive models for loan default risk by channel.
• Start integrating data with LLM systems through Windsor MCP to enable conversational analytics and faster decision-making.

Final takeaway

Kueski replaced fragmented, manual reporting with Windsor.ai’s automated data integration and algorithmic MTA. In one setup, marketing data from 14+ platforms flows into BigQuery with hourly refreshes, powering real-time dashboards and enabling true attribution tracking.

The result: a single source of truth across all marketing channels, more accurate channel valuation, smarter budget decisions, and higher customer acquisition efficiency, which led to 23% quarter-over-quarter growth in a highly competitive fintech market.

Curious what Windsor.ai can do for your team?

Start your free 30-day trial: https://onboard.windsor.ai/, or book a demo: https://calendly.com/windsorai/guided-onboarding.