NakedCollector2024-03-07 01:36 PM
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Amount Spent: Overall investment by the customer, indicating their spending level.
Token Types: Diversity in investment, showing whether customers prefer to diversify their holdings.
Transaction Frequency: Engagement level, indicating how active the customer is.
Feature Engineering: Derive new features that might offer more insights, such as average spend per transaction, time between transactions, or categories of tokens/NFTs purchased (e.g., art, gaming).
Exploratory Data Analysis (EDA): Use statistical analysis and visualization to understand the distribution and relationship of these features with customer segments or behaviors you're interested in.
Model Feedback: Use feedback from the clustering or predictive models to assess feature importance and iteratively refine your feature set.
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