How to Think About Customer Cohort Analysis with Steve Groccia, Head of Customer Success Operations at Mosaic
Apr 21, 2022
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Steve Groccia, Head of Customer Success Operations at Mosaic, discusses the reasons finance leaders don't use cohort analysis, the difference between segment-based and time-based cohort analysis, and the importance of collaboration between finance and customer success.
Accurate and reliable historical data is crucial for effective customer cohort analysis.
Cohort analysis provides detailed insights into customer behavior over time, allowing businesses to understand retention dynamics and identify contributing factors.
Deep dives
The Importance of Trusting Historical Data for Cohorting
In order to effectively use historical behavior data for customer analysis, it is crucial to trust the accuracy and reliability of the historical data. Cohorting can be a valuable tool, but it requires having the right data in the right structure and format. Starting fresh and gathering reliable data is necessary to confidently use cohort analysis and benefit from it in the long run.
The Power of Cohort Analysis in Understanding Retention
Cohort analysis can provide deeper insights into customer retention by going beyond basic churn analysis. While basic churn analysis provides a high-level view of retention, cohort analysis allows for more detailed analysis of customer behavior over time. By segmenting customers into cohorts and analyzing their behavior patterns, businesses can better understand the dynamics of retention and identify the factors that contribute to it.
Different Approaches to Cohort Analysis
There are two main approaches to cohort analysis: segment-based and time-based. Segment-based cohorting involves analyzing cohorts based on different customer segments, such as sign-up dates or product usage patterns. This approach helps businesses understand customer behavior within specific segments. On the other hand, time-based cohorting focuses on analyzing behavior over time, allowing businesses to study specific customer behaviors and identify patterns and trends.
Overcoming Challenges in Cohort Analysis
There are several challenges in implementing cohort analysis. Gathering and trusting reliable historical data is crucial for accurate analysis. It can be time-consuming and require resources to structure and organize the data in a usable format. Additionally, some companies may not find cohort analysis beneficial until they reach a certain scale or have a sufficient number of customers and transactions. Despite these challenges, cohort analysis can provide valuable insights that enable businesses to make data-driven decisions and drive growth.
The contemporary business world depends on in-depth and high-quality data analysis. But it seems like many departments don't have adequate time or tools to focus on data.
In a study conducted by Mosaic, only 14% of surveyed finance leaders said they used cohort analysis. Therefore, it is critical to determine the reasons behind this small percentage and offer solutions.
In this episode of The Role Forward, host Joe Michalowski welcomes Steve Groccia, the Head of Customer Operation at Mosaic. Steve and Joe discuss the reasons finance leaders don’t use cohort analysis. Steve also explains the difference between segment-based and time-based cohort analysis and the steps in the process.
Guest-at-a-Glance
💡 Name: Steve Groccia
💡 What he does: Steve is the Head of Customer Operations at Mosaic.