Imagine you're an Analytics Engineer for an online retail company.
Your main stakeholders are:
The marketing team, who drive traffic to the site through paid ads, email, and organic search. The customer success team, who build relationships with existing customers and handle their concerns. The product team, who builds and manages the website. The analytics and data science team (your teammates), who do in depth analyses and reporting for the same stakeholders. TASK Attached is an "online retail transactions" dataset, with a sample set of purchase transactions on our site. Here's the schema:
Column Definition InvoiceNo A unique identification number assigned to each transaction. (Numeric) StockCode A unique identification code assigned to each product sold by the retailer. (Numeric) Description A brief description of the product sold. (Text) Quantity The number of units of the product sold in each transaction. (Numeric) InvoiceDate The exact date and time when the transaction occurred. (Date/Time) UnitPrice The price per unit of the product sold. (Numeric) Country The country where the customer resides. (Text)
Answer the questions below. Please answer them as if you were in a real life business context - list assumptions, questions you might ask your stakeholder, issues that may arise, future work, etc..
Customer success wants a dashboard to help them track and identify specific customers to reach out to - particularly engaged ones to upsell to, or not-so-engaged ones that may just need a little nudge. Using the attached dataset, create a dashboard with 2-3 insights to help them with this (assume it updates daily).
For this exercise, please focus on the visualizations and queries. Assume we have a tool (e.g. Hex, Looker, Tableau) that will handle the scheduling pipeline for you. Please walk through how you would explain this to the team so they know how to interpret and use your dashboard.