What factors have contributed to the unexpected 30% drop in Lunar Energy's solar panel installation requests during the summer months?

Introduction

The unexpected 30% drop in Lunar Energy's solar panel installation requests during summer months presents a critical challenge for our business. This analysis will systematically identify, validate, and address the root cause while considering both immediate and long-term implications for our solar energy product line.

I'll approach this issue by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the seasonality, I'm thinking this drop might be unusual for summer. Can you confirm if this 30% drop is compared to previous summers or to other seasons this year?

Why it matters: Seasonal patterns are crucial for solar panel demand. Expected answer: Compared to previous summers. Impact on approach: If it's compared to previous summers, we'll focus on year-over-year changes.

• Given the specificity of the 30% figure, I'm wondering about our measurement accuracy. Have there been any recent changes to how we track installation requests?

Why it matters: Ensures we're not chasing a data anomaly. Expected answer: No recent changes to tracking methods. Impact on approach: If there were changes, we'd need to audit our data collection first.

• Considering potential market shifts, has there been any significant change in our pricing or competitor offerings recently?

Why it matters: Price sensitivity could explain demand fluctuations. Expected answer: No major price changes from us or competitors. Impact on approach: If pricing has changed, we'd prioritize market positioning analysis.

• Thinking about our customer base, are we seeing this drop across all customer segments or is it concentrated in specific groups?

Why it matters: Helps identify if it's a broad issue or segment-specific. Expected answer: The drop is fairly uniform across segments. Impact on approach: If it's segment-specific, we'd focus on those particular user groups.