When you work as a data analyst, a lot of time you will try to understand your customers so that you can target them effectively, improve their experience, improve marketing strategies, and much more.
๐๐ฒ๐ ๐บ๐ฒ ๐ด๐ถ๐๐ฒ ๐๐ผ๐ ๐๐ผ๐บ๐ฒ ๐ฏ๐ฎ๐๐ถ๐ฐ ๐ฎ๐ฑ๐๐ถ๐ฐ๐ฒ ๐๐ต๐ฎ๐ ๐บ๐ถ๐ด๐ต๐ ๐ฏ๐ฒ ๐๐๐ฒ๐ณ๐๐น ๐ถ๐ป ๐๐ต๐ถ๐:
โข Perform EDA to understand key customer behavior such as purchases according to regions, age, gender, and more. This will allow you to have a high level of understanding about customers.
โข Then try to group customers according to age (creating age groups), region, gender, and more.
โข Now, analyze some important business metrics such as their membership tier, ratings, complaints, average spend, delivery timelines, and more.
โข Now, try to combine customer variables with these key metrics such as:
1. Membership tier for each age group.
2. Segment customers according to complaints and age groups or regions.
3. Understand the satisfaction score given by customers who had complaints (you can create categorical variables for satisfaction scores such as "Bad", "Good" or "Excellent").
4. Then you can also dive deep into delivery timelines for different regions so that delivery time can be improved and more.
These are just some basic instances and how deep you can go into customer behavior actually depends upon how many crucial variables you have.
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