Background

Playbooks is a browser extension that allows sales representatives to make sales interactions following different cadences. As a part of the product, every rep has access to a leaderboard that shows them their performance score ranking among their team.

Problem

The original scoring system was designed to help reps understand how they are performing and improve their performance. However, because of the lacking of visuals and context information, sales reps find it hard to understand. The leaderboard became one of the least used features, with less than 10% users using it daily.

Before: The correlation features you can access vary depending on your location within the product and the specific chart you are analyzing.
Old rankings panel is lacking visuals and context making it hard to use

Solution

After talking with some customer success managers and PM, we found that companies and reps have been demanding a better performance indicator, not only how reps are doing relative to their team but also to themselves.To solve that, I designed a new performance center that includes easy-to-understand data visualizations and a more intuitive ranking view.

A new performance view with easy-to-understand data visualizations and a more intuitive ranking view.

Constraint

The original scoring system was designed to help reps understand how they are performing and improve their performance. However, because of the lacking of visuals and context information, sales reps find it hard to understand. The leaderboard became one of the least used features, with less than 10% users using it daily.

Research

Weekly semi-structured User Interviews

We pulled all the data points we collected from our weekly semi-structured user interviews with the tags "personal metrics", "leaderboards", "scorecard", "reporting", "smart features", etc.

Talking with CSMs, PMs, and Data Scientists

Our customer success managers (CSMs) constantly communicate with our clients on their business needs and pain points. Our PMs know what the product should focus on. Our data scientists have insights and data to support our core functionalities. Therefore, we arranged meetings with them to discuss opportunities.

Synthesis Workshop

After we gathered all the information reps care about and the questions they are trying to answer, we did three workshop sessions. During those workshops, we did various exercises to group data, identify problems, and brainstorm idead.

Findings

  • Reps don't have time to read and learn any complex data during their busy workday, so we should use the most understandable data and prioritize relative information for them.
  • Our users use notebooks, excel sheets, and other services to keep track of their activities and performances on their own.
  • By providing transparent data on the outcome of intelligent features, reps will trust and use those features more confidently.
  • There is no one-fits-all system. Every rep, every company values different aspects of their performance. So we should always provide more than one metric.

Data visualization exploration

Final design