Customer Data Analysis Needed
Budget: $250 – $750 USD
I have a sizable set of customer data sitting in CSVs and I want it turned into clear, actionable insights. Right now I’m still deciding which angle will be most valuable—anything from simple descriptive trends through to predictive or even prescriptive models is on the table—so I’d like your input on what the data can realistically deliver.
Here’s what you’ll be working with
• Customer profiles (demographics, acquisition source)
• Historical purchase records and spend patterns
• Engagement logs from email and in-app activity
What I need from you
1. A short plan outlining the analysis path you recommend once you’ve skimmed a sample of the data. Feel free to propose segmentation, churn risk scoring, lifetime value estimates, or another approach you believe will surface the biggest wins.
2. The analysis itself—code (Python, R, or SQL), notebooks, or dashboards (Power BI, Tableau) that I can rerun on fresh data.
3. A concise write-up and a handful of slides that translate the numbers into plain-English recommendations I can hand to marketing and product.
4. A cleaned, well-documented version of the dataset so the work is fully reproducible.
I’ll provide the raw files plus a quick call to walk you through business context and data quirks. Let me know how you’d tackle this and how long you’d need—looking forward to seeing what my customer data is really telling me.
Here’s what you’ll be working with
• Customer profiles (demographics, acquisition source)
• Historical purchase records and spend patterns
• Engagement logs from email and in-app activity
What I need from you
1. A short plan outlining the analysis path you recommend once you’ve skimmed a sample of the data. Feel free to propose segmentation, churn risk scoring, lifetime value estimates, or another approach you believe will surface the biggest wins.
2. The analysis itself—code (Python, R, or SQL), notebooks, or dashboards (Power BI, Tableau) that I can rerun on fresh data.
3. A concise write-up and a handful of slides that translate the numbers into plain-English recommendations I can hand to marketing and product.
4. A cleaned, well-documented version of the dataset so the work is fully reproducible.
I’ll provide the raw files plus a quick call to walk you through business context and data quirks. Let me know how you’d tackle this and how long you’d need—looking forward to seeing what my customer data is really telling me.