Posadas implements Event Tracking to better understand conversion funnel abandonment, sees conversion rate uplift of up to 88%
Customer Company Size
Large Corporate
Region
- America
Country
- Mexico
Product
- Google Analytics
Tech Stack
- Event Tracking
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Sales & Marketing
Services
- Data Science Services
About The Customer
Posadas is Mexico’s largest hotel chain, with hotels in Mexico as well as Brazil, the US, Argentina and Chile. The company operates over 100 properties and uses Google Analytics to analyze its website’s efficiency in converting visitors into customers. Posadas was looking to improve its conversion rates by gaining a better understanding of customer behavior during the booking process. The company wanted to segment the traffic flowing through the conversion funnel to make a differentiated analysis for each of its hotels and enrich the abandonment analysis by uncovering the opportunity cost of users leaving the booking process before completing a transaction.
The Challenge
Posadas, Mexico’s largest hotel chain, was looking to improve its conversion rates by gaining a better understanding of customer behavior during the booking process. The company was using Google Analytics to analyze its website’s efficiency in converting visitors into customers. However, Posadas wanted to segment the traffic flowing through the conversion funnel to make a differentiated analysis for each of its over 100 hotels. The company also wanted to enrich the abandonment analysis by uncovering the opportunity cost of users leaving the booking process before completing a transaction.
The Solution
To achieve its goals, Posadas implemented Event Tracking in the conversion process. This allowed the company to get a data matrix showing the differences in traffic flow for each of the steps in the booking process, for each hotel. The company could also look at differences between quoted prices and actual revenue, look for significant fluctuations in traffic and money amounts, and discover potential optimization points with more detail than the standard conversion funnel report allowed. In addition, Posadas implemented a survey to obtain feedback from visitors about why they abandon the process in each of the high fluctuation points. This information would help Posadas to make sound optimization decisions on a hotel-by-hotel basis, to tailor pricing policies, and even to experiment with specific sales promotions.
Operational Impact
Quantitative Benefit
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