Funnel to Fortune: Analyzing Feature Impact

As product managers, we often launch features with the expectation of driving significant business value. However, the true impact of these features can be less clear. That's why it's crucial for us, as strategists, to proactively analyze the impact of each new feature to ensure our product decisions genuinely contribute to success.

Ever paused to clarify the business value behind a feature? This isn't just about seeking clarity; it's about transitioning from simply completing tasks to strategically guiding your product.

Why hit the pause CTA as a PM?

• Question Assumptions: Challenge the initial ideas to dodge expensive missteps.

• Drive Impact: Make sure each project goes beyond just ticking boxes and genuinely advances business goals.

• Build Trust: Strengthen your role as a key player in your company's success, not just as an executor.

Feature Impact Analysis

Imagine you're the Uber PM for the driver team. You've been told that improving the ride acceptance process for drivers could up our business revenue by 10%. Let's get to work!

1. Establish a Baseline:

• Determine how many users currently move through the relevant part of your product funnel and where drop-offs occur. This will provide a benchmark for comparison after your new feature is released.

2. Quantify the Problem:

• Identify the target audience: Who is this feature intended to serve? (In our example: Uber drivers)

• Define the start point: What action triggers the beginning of the process? (Example: Driver activates "Ride Mode")

• Define the endpoint: What is the ideal outcome? (Example: Driver successfully completes a ride)

• List the intermediate steps: What actions must the user take between the start and end points? (Example: Receive ride request, accept request, verify OTP, commence ride)

Analyzing the Driver Drop-Off

Our funnel analysis reveals a significant drop-off after drivers accept a ride (step 3 of the process). This illogical behavior suggests a specific problem we need to address.

Rather than focusing solely on the largest drop-off(step 1), pinpointing this unusual pattern(step 3) may lead to a key fix with a tangible impact.

Based on this finding, our initial assumption of a 10% business value increase may be overestimated. A more realistic target could be around 4% once we resolve the step 3 issue.

Next Steps

• Investigate: Use interviews, surveys, or data analysis to understand why drivers drop off at this point.

• Brainstorm: Generate potential solutions to reduce friction specifically at step 3.