FinTech Growth
How a Series B fintech reduced fraud detection latency by 60% using Sonus's real-time anomaly engine.
Case Study
How Veritas Retail Recovered $2.4M in Annual Revenue Leakage with Sonus
Transforming fragmented e-commerce data into a real-time revenue protection engine.
The Customer
Veritas Retail
A mid-market e-commerce giant managing 12,000+ SKUs and 4 million+ monthly orders across North America. Veritas relies on a modern data stack centered on Snowflake and dbt, with Looker serving as their primary BI layer.
The Challenge
Drowning in Dashboards, Starving for Insight
With over 50 active dashboards, Veritas's data team was spending 80% of their time maintaining reports rather than analyzing anomalies. Revenue spikes were often missed until they appeared in the P&L, causing a reactive rather than proactive approach to inventory and pricing.
The team struggled with delayed anomaly detection; by the time a significant drop in conversion rate was flagged in their legacy tools, the revenue impact had already materialized. Furthermore, the volume of daily alerts was overwhelming, leading to alert fatigue and analysts ignoring critical signals.
The Solution
Implementing Sonus Signal Detection in Two Weeks
Veritas deployed the Sonus Signal Detection and Alerting Engine directly into their Snowflake environment. Within 48 hours of connection, Sonus auto-discovered their key e-commerce metrics and began establishing baselines.
The implementation was streamlined through Sonus's warehouse-native architecture. The team configured custom alert rules for revenue leakage—specifically targeting sudden drops in average order value (AOV) and unusual inventory turnover rates. By Week 2, the platform was live, flagging 12 potential anomalies that had previously gone unnoticed.
Key Results
Measurable Impact in the First Quarter
$2.4M
Annual revenue recovered through immediate anomaly intervention
73%
Reduction in missed anomalies compared to manual monitoring
4hrs
Saved per analyst per week on alert triage and report maintenance
The Rollout
From Pilot to Platform: The First 90 Days
The first week of the rollout was dedicated to data mapping. Sonus's schema discovery feature identified over 200 potential metrics, allowing the Veritas team to curate a "Signal Library" focused on high-impact KPIs like cart abandonment, shipping delays, and pricing discrepancies. By the end of Week 2, the engine was live, and the team began receiving daily "Signal Reports" instead of manual spreadsheets.
In Month 1, the platform identified a subtle but persistent dip in conversion rates across mobile devices. While traditional BI tools showed a flat line, Sonus's statistical modeling highlighted a 4% variance that correlated with a recent payment gateway update. The team acted immediately, reverting the gateway configuration and preventing a projected $400k loss.
By Month 3, the integration with dbt was complete. Sonus now reads the transformed models directly, ensuring that the signals it surfaces are based on the most accurate, cleaned data available. The team has since expanded the scope to include inventory forecasting, turning Sonus from a diagnostic tool into a strategic planning asset.
"Sonus changed how we operate. Before, we were reactive—cleaning up messes after they happened. Now, we are proactive. The platform surfaces the signal we were missing, and the plain-language explanations make it easy to get executive buy-in for immediate action."
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