Why are completion rates for Benchling's CRISPR workflow declining steadily over the past 6 months?

Introduction

The declining completion rates for Benchling's CRISPR workflow over the past 6 months present a critical challenge that requires immediate attention. To address this issue, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

My analysis will follow a structured framework, beginning with clarifying questions to establish context, followed by a thorough examination of external factors, product understanding, metric breakdown, data gathering, hypothesis formation, root cause analysis, validation planning, and finally, a comprehensive resolution strategy.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timeline, I'm wondering if there have been any significant product updates or changes to the CRISPR workflow in the last 6-8 months?

Why it matters: Recent changes could directly impact user behavior and completion rates. Expected answer: Information about recent updates or lack thereof. Impact on approach: If changes occurred, we'd focus on those specific alterations; if not, we'd look at gradual shifts in user behavior or external factors.

• Considering user segments, have we noticed any particular group (e.g., academic vs. industry users) experiencing a more significant decline in completion rates?

Why it matters: Identifying affected segments helps narrow down potential causes and tailor solutions. Expected answer: Data on completion rates across different user segments. Impact on approach: If specific segments are more affected, we'd investigate factors unique to those groups.

• Regarding the definition of "completion," has there been any change in how we measure or define a completed CRISPR workflow in the past year?

Why it matters: Ensures we're comparing apples to apples in our metric analysis. Expected answer: Confirmation of consistent measurement or details of any changes. Impact on approach: If the definition changed, we'd need to recalibrate our analysis based on the new criteria.

• Have we observed any changes in the average time users spend on the CRISPR workflow, even if they don't complete it?

Why it matters: This could indicate whether users are struggling at specific points or losing interest. Expected answer: Data on time spent on the workflow over the past 6-8 months. Impact on approach: Longer times might suggest usability issues, while shorter times could indicate early abandonment.