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Company focus

Lazada

Why has the average order value for fashion items on Lazada declined steadily over the past month?

Prepared by NextSprints

15 mins
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Data Analysis Problem Solving Strategic Thinking E-commerce Fashion Retail Online Marketplaces E-Commerce Data Analysis Root Cause Analysis User Behavior Fashion Retail
Product Management Root Cause Analysis Question: Investigating declining average order value in e-commerce fashion

Introduction

The steady decline in average order value (AOV) for fashion items on Lazada over the past month is a concerning trend that requires immediate attention. This analysis will systematically investigate potential root causes, generate data-driven hypotheses, and propose actionable solutions to address the issue.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into internal product and user behavior aspects. My goal is to identify the most likely root cause and develop a comprehensive plan to reverse the AOV decline.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be seasonal factors at play. Has this decline coincided with any particular shopping season or holiday period?

Why it matters: Seasonal trends can significantly impact purchasing behavior. Expected answer: No significant seasonal events during this period. Impact on approach: If seasonal, we'd focus on adjusting our strategy for these periods.

  • Considering user segments, I'm curious about the distribution of this decline. Is the AOV decrease uniform across all customer segments, or is it more pronounced in specific groups?

Why it matters: Identifying affected segments helps target our solution more effectively. Expected answer: The decline is more significant among mid-tier customers. Impact on approach: We'd focus on understanding and addressing issues specific to this segment.

  • Thinking about recent changes, have there been any significant updates to the product recommendation algorithm or the user interface in the past month?

Why it matters: Recent changes could directly impact user behavior and purchasing decisions. Expected answer: A new recommendation algorithm was implemented three weeks ago. Impact on approach: We'd investigate the algorithm's impact on product visibility and user choices.

  • Regarding competitive landscape, have there been any notable changes in competitor pricing or promotions during this period?

Why it matters: Competitive pressures could be driving users to make smaller purchases or shop elsewhere. Expected answer: No significant changes in competitor strategies observed. Impact on approach: We'd focus more on internal factors rather than market dynamics.

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Updated Nov 19, 2024