Assessfy Business Functions Lab Advanced 6 milestones 100 marks

Customer Lifetime Value and Churn Analytics for Indian SaaS Subscription Firms

Function: Business Analytics Industry: SaaS / Technology Function: Business Analytics Type: Business-function applied project Team: up to 4 Assessment: 6 milestones (100 marks)

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About this project

Objective: To analyse customer lifetime value and predict churn for a subscription-based business, enabling targeted retention strategies.

Subscription businesses in India, such as SaaS firms and digital platforms, face challenges in predicting customer churn and maximizing customer lifetime value (CLV). High competition and price sensitivity make it crucial to identify at-risk customers and optimize retention investments.

The approach involves gathering transactional and behavioral data from Indian SaaS platforms (e.g., Freshworks, Zoho), using analytics frameworks to segment customers, calculate CLV, and build predictive churn models. Methodologies include cohort analysis, regression, and machine learning techniques.

Deliverables include a comprehensive data analysis report, churn prediction model, CLV calculation dashboard, and actionable recommendations for customer retention. Analysis will be reviewed via peer and faculty feedback, and iterative model validations.

The business impact is to inform management decisions on marketing spend, customer engagement strategies, and pricing, directly reducing churn rates and improving profitability.

Milestones

1. Problem Definition & Business Case

8 marks 16d

Define the business problem, scope, and justify the case for CLV and churn analytics for an Indian SaaS subscription firm. Reviewed via written proposal and faculty feedback.

2. Domain Research & Data Gathering

12 marks 23d

Conduct domain research, identify relevant Indian SaaS companies, gather or simulate customer data, and document sources. Reviewed via data inventory and research summary.

3. Solution Design / Methodology

12 marks 18d

Design the analytical approach: segment customers, select CLV and churn models, and plan validation techniques. Reviewed via methodology document and peer review.

4. Build / Analysis & Implementation

30 marks 35d

Implement data analysis, build CLV and churn models, visualize findings, and develop retention recommendations. Reviewed via interim analysis report and faculty feedback.

5. Validation & Results

22 marks 28d

Validate model accuracy, test retention strategies, interpret business impact, and refine recommendations. Reviewed via validation report and expert/industry input.

6. Final Report & Presentation

16 marks 18d

Compile the final project report, deliver executive summary, and present findings to faculty and industry panel. Reviewed via oral presentation and written report.

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Skills you'll learn

SaaS / TechnologyBusiness AnalyticsCustomer segmentation and cohort analysisStatistical modeling and regression analysisData visualization and dashboardingPython/R programming for analyticsMachine learning for churn predictionBusiness communication and reportingUse of CRM data and SaaS metricsDecision-making with analytical insights

Tools used

Microsoft ExcelSQL databases (MySQL/PostgreSQL)Python (pandasscikit-learnmatplotlib)Power BI or TableauCRM data from Indian SaaS firms (sample or simulated)Google Analytics (where available)Customer Lifetime Value frameworks (e.g.RFM analysis)Churn prediction models (logistic regressionrandom forest)

Prerequisites

Basic statistics and probabilityIntroduction to business analyticsSQL and relational database conceptsFundamentals of marketing or customer relationship managementData visualization basics

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