Contact person: Business Client

Phone:Show

Email:Show

Location: Hyderabad, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I’m ready to stand up a lean MVP that proves the core value of AnanthaAI’s Customer Insights & Growth Opportunity Agent. The goal is simple: given a bundle of sample customer data, the app should surface the right analytics, predict the next moves, and let a user download ready-to-act segments.

Data scope
• I will supply (or we can auto-generate) synthetic datasets that imitate CRM, e-commerce, and in-store tables.
• At minimum the transactions file must include purchase history.
• For feedback we’ll work with three streams—survey responses, online reviews, and customer-support transcripts.

Core pipeline
1. Data ingestion & cleaning in Python (pandas preferred).
2. Out-of-the-box analytics: RFM scoring, behavioural segmentation, cohort analysis.
3. Predictive models for churn risk, lifetime value and next-best action—scikit-learn, XGBoost or similar are fine.
4. Streamlit UI that lets a user select a segment, view key metrics, read plain-English recommendations, and export a CSV.
5. Everything containerised or at least runnable with a one-shot requirements file.

What I need to see before sign-off
• Code repo with clear structure and concise README
• Working Streamlit app deployable locally
• Synthetic datasets and generation scripts
• Short demo video or GIF walking through the UI

This build will be shown to early clients and advisors, so polish and reliability matter more than edge-case coverage. If you’ve wired up analytics dashboards or ML-driven recommender flows in the past, I’d love to hear how you’d approach this and the timeline you envision.

MVP Objectives

The freelancer must deliver:

1. Data ingestion & cleaning pipeline


2. Automated customer analytics (RFM, cohorts, CLV, churn risk)


3. Recommendation engine (growth opportunities)


4. Action-ready output (CSV/Excel segments + insights)


5. UI in Streamlit


6. Documentation + lightweight architecture diagrams
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3. Project Deliverables

A. Data Layer

1. Sample Dataset Creation

Freelancer must create 5 datasets:
(minimum 10,000 rows each)

1. Customers (ID, demographics, membership, signup date)


2. Transactions (ID, date, SKU, amount, category)


3. Visits/Appointments (for service businesses)


4. Feedback/NPS (scores, comments, dates)


5. Marketing Campaign Data (channels, spend, response)" (client-provided description)