💡 PLCC Top-up & IRA Campaign Analytics – Credit Lending Domain

🔍 Overview

This project aimed to improve the targeting and efficiency of personal loan acquisition through two structured outbound campaigns: the Top-up Campaign and the Interest Rate Advantage (IRA) Campaign. Together, they targeted over 3.5 lakh customers per month and led to significant improvements in conversion rates and incremental profitability.

🧩 Business Objective

• Reduce the inefficiency of blanket telecalling by identifying high-propensity customer segments.
• Design strategic campaigns using timely triggers (e.g., loan maturity or interest rate differentials).
• Improve conversion rates and incremental profitability through better targeting and segmentation.

🧰 Tools & Technologies

• SQL – Used throughout all stages: extracting large-scale customer and loan data, applying maturity-based and interest-rate-based filters, and finalizing shortlists with high targeting precision.
• Microsoft Excel – Utilized for sharing finalized customer lists with the telecalling team and for version-controlled tracking of campaign performance.
• Power BI – Developed interactive dashboards to monitor:
  • Monthly campaign reach and conversion trends.
  • Uplift vs baseline for Top-up and IRA campaigns.
  • Call performance dashboards showing Attempt Intensity (calls per customer from total called batch) and Contact Intensity (calls per customer from total converted batch).
  • Visualization of how many customers from our campaign batch were actually called, how many were connected, and how many remained uncontacted. These dashboards provided real-time visibility to business teams and helped optimize ongoing strategy.
• PowerPoint – Occasionally used to present campaign performance summaries and long-term trends to internal stakeholders.

🧾 Campaign Design & Targeting Criteria

1. 📌 Top-up Campaign

• Goal: Identify customers who had previously availed personal loans and are likely to need additional credit.
• Logic: Select customers whose loans (from own or other institutions) were:
  • Closing within the next 60 days, or
  • Already matured in the past 60 days.
• Volume: Targeted ~1.5 lakh customers per month.
• Action: Shared filtered customer lists (excluding DNC/NDNC numbers) with the telecalling team.
• Outcome: Conversion rate improved by 4x compared to the baseline average.

2. 📌 IRA Campaign (Interest Rate Advantage)

• Goal: Acquire customers with higher-interest loans from other institutions by offering better repayment terms.
• Logic:
  • If the new loan interest rate < existing loan rate → offer directly.
  • If the new loan EMI is lower despite a higher interest rate → offer based on affordability.
  • Used both interest rate and EMI comparison where available; fallback to EMI when rate was missing.
• Volume: Targeted ~2 lakh customers per month.
• Action: Prioritized high-opportunity segments for telecalling outreach.
• Outcome: Conversion rate increased by 11.5x, significantly boosting monthly acquisitions.

📊 Data Preparation & Execution

• Extracted customer data using complex SQL joins and filters based on real-time attributes like loan maturity and interest rate.
• Removed customers flagged under DNC/NDNC to maintain compliance.
• Used Excel to maintain version-controlled campaign sheets and historical tracking of performance.
• Tracked execution using monthly feedback reports from the outreach team and refined targeting logic accordingly.

🤝 Cross-Team Collaboration

• Worked closely with the telecalling operations team to fine-tune targeting logic and validate outcomes.
• Presented insights using PowerPoint decks showcasing monthly trends, performance comparisons, and L6M impact.

📈 Outcome & Business Impact

Metric	Top-up Campaign	IRA Campaign
Customers Targeted (Monthly Avg)	~1.5 lakh	~2 lakh
Conversion Rate Uplift	↑ 4x vs baseline	↑ 11.5x vs baseline
Incremental Profit (Monthly)	₹33 million	₹13 million

• ✅ Higher ROI on Outreach – Avoided targeting the full 30 lakh eligible base by narrowing down to 12–15% high-propensity customers.
• ✅ Smarter Customer Engagement – Trigger-based logic helped approach customers with the right offers at the right time.
• ✅ Sustainable Campaign Strategy – Monthly refreshes, feedback loops, and compliance screening kept campaigns lean and effective.

📌 Key Learnings

• Micro-segmentation using time-bound events and financial logic can drastically improve campaign economics.
• Data + Domain + Delivery = measurable business value.
• A tight feedback loop with execution teams (like telecalling) is essential to measure and iterate effectively.