HomeToGo speeds up manual data investigation by up to 80% with Sisu
Company Size
1,000+
Region
- Europe
Country
- Germany
Product
- Sisu Decision Intelligence Engine
Tech Stack
- Business Intelligence (BI)
- dbt
- Snowflake
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Real Time Analytics
- Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
- E-Commerce
- Software
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- System Integration
- Training
About The Customer
HomeToGo is a marketplace with the world’s largest selection of vacation rentals, listing millions of offers from thousands of trusted partners to deliver the perfect accommodation and great memories. The Data & Analytics team at HomeToGo aims to deliver greater value from data by scaling access and making data more usable without creating an 'army of analysts' to answer the company's growing, yet critical, questions. They focus on tools and processes geared towards flexibility and self-service to help teams answer their own questions and drive work independently.
The Challenge
HomeToGo’s Data & Analytics team faced challenges in reducing time spent on manual analysis, accelerating KPI investigation, increasing A/B testing, and promoting self-service and data engagement across the business. As the business and data continued to grow, it became clear that business intelligence alone wasn’t enough to scale the questions of the business. The team sometimes dedicated over a week’s worth of manual analysis to diagnose key business metric declines, which was not scalable. They needed a better, faster way to perform analysis, speed up data exploration, and surface more actionable insights while providing more business user engagement than static BI reports alone.
The Solution
HomeToGo decided to evaluate Sisu’s Decision Intelligence Engine to augment their existing BI workflow. They were particularly drawn to Sisu’s scalability, ability to reduce time spent on manual analysis, and intuitive UI for self-service analysis. Athene Cook, Senior Data Analyst at HomeToGo, led a backtesting approach to measure how much faster Sisu could diagnose the cause of previous issues. The evaluation showed that Sisu could highlight the facts and key drivers up to 80% faster than before. After deciding to move forward with Sisu, the Data & Analytics team took a thoughtful approach to train employees across the organization, fostering a self-service data culture. This included hosting company-wide training, creating recordings for employees and new hires, conducting deep-dive training for power users, and building open lines of communication for support.
Operational Impact
Quantitative Benefit
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