Process
Analytics
Introduction
At Cisco, I’ve been at the forefront of integrating analytics into our design processes, leading the charge in leveraging data to inform decision-making. Through my commitment to continuous learning, I’ve completed several courses in Amplitude, our analytics software, allowing me to harness its full potential. I have also developed and instituted a comprehensive data collection process, enabling our team to gain valuable insights into user behavior and enhance the overall user experience. My efforts ensure that our design strategies are not only user-centered but also data-driven, fostering a culture of informed decision-making.
Slide from a design group wide internal conference that myself and a colleague presented at on analytics.
Analytics Program Objectives
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Enhance Understanding of User Behavior: Our analytics program aims to provide deeper insights into user interactions, allowing us to identify patterns, preferences, and pain points in their journeys.
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Informed Decision-Making: By understanding how users engage with our products, we can make data-driven decisions that align our design strategies with actual user needs, ensuring that our solutions are effective and relevant.
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Quantify Design Success: We strive to establish metrics that measure the impact of our design efforts, enabling us to quantify successes and areas for improvement, and ultimately driving continuous enhancement of the user experience.
Tools we use
At Cisco, we leverage Amplitude for comprehensive product analytics, allowing us to track user behavior and derive actionable insights. Additionally, we utilize Power BI for data visualization and reporting, enabling us to present complex data in an easily digestible format, facilitating informed decision-making across teams.
Collection Process
The data collection process I created begins with a collaborative meeting with cross-functional group to define our goals. From these goals, we establish key performance indicators (KPIs) that guide our tracking efforts. We focus on tracking only the events that align with these goals, ensuring our data is relevant and actionable.
Once we’ve identified the necessary events, we implement a consistent naming convention to maintain clarity. We’ve collaborated with Engineering to enforce title case in our event names, recognizing that Amplitude is case sensitive. Our event naming follows the format: Left Nav Item - Flow (standardized) - Action (standardized). For event properties, we use the format: Flow - Action (standardized) - Target (standardized) = Value (yes/no, true/false, etc.).
For more information and examples, please refer to the accompanying slideshow.
Case Study - First Time Setup Wizard
The First Time Setup Wizard (FTSW) plays a crucial role in our user experience, as nearly 90% of orders pass through this feature. By leveraging analytics, we were able to assess the impact of our design decisions effectively. We created a comprehensive event tracking table, which revealed several significant insights:
User Retention: We closely monitored the number of users reverting to the old experience, and this has consistently decreased, reaching 0% today.
Streamlined Flow: The new FTSW reduced the setup time from an average of 40 minutes to just under 10 minutes—a major achievement that enhances user satisfaction.
Experience Optimization: Initially, we designed the FTSW to accommodate customers with multiple meeting sites. However, analytics showed that very few users had this need. As a result, we decided to streamline the experience for single meeting sites and make the multiple meeting sites option a secondary feature.
This project exemplifies how data-driven insights can lead to meaningful improvements in user experience.
Lessons Learned
One of the key lessons we've learned is the important distinction between events and event properties. Understanding this distinction is crucial, as failing to do so can lead to “dirty” data that undermines our analytics efforts. Additionally, we recognized the value of standardizing both events and event properties, which helps maintain data integrity and ensures consistency across our analytics framework.
For a deeper dive into these lessons and how we've applied them in the Partner Hub, please refer to the accompanying video.
