Introduction
To enhance Olist's product categorization and make it easier for shoppers to find items across multiple sellers, we need to approach this challenge systematically. I'll analyze the current state, identify key user segments and pain points, propose solutions, and outline a strategy for implementation and measurement.
I'll be using a structured approach to tackle this problem, focusing on user needs, data-driven insights, and scalable solutions. Let's align on this framework before we dive in.
Step 1
Clarifying Questions
Why it matters: Determines the complexity of the categorization problem and informs potential solutions. Expected answer: 20-30 main categories, 100-200 subcategories, with varying seller representation. Impact on approach: A large, diverse catalog might require more sophisticated categorization and search algorithms.
Why it matters: Helps prioritize improvements in category structure vs. search functionality. Expected answer: 60% use search, 30% browse categories, 10% use both. Impact on approach: High search usage might suggest focusing on improving search algorithms and category tagging.
Why it matters: Influences the approach to category management and potential seller-facing tools. Expected answer: Sellers choose categories but Olist can override; some inconsistencies exist. Impact on approach: Might need to consider a hybrid model of seller input and centralized control.
Why it matters: Affects the scalability and flexibility required in the categorization system. Expected answer: Planning expansion to 2-3 new countries in the next year. Impact on approach: Would need to design a flexible, localizable category structure from the outset.
I'd like to take a quick moment to organize my thoughts based on your responses before we move to the next step. Is that alright with you?
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