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To Maximise Ecommerce Sales.
Your brand needs value, and it needs it ASAP!!
Customer acquisition costs are rising. Retention rates are declining. RTOs, SLA breaches, returns etc. are eating into margins. Yet, most D2C brands are still relying on fragmented data and intuition.
This is where 360° Customer Profiling becomes essential. Instead of looking at customers in silos—separating acquisition, conversions, and retention—a full-circle approach connects every touchpoint into one actionable intelligence system.
At Pragma, with insights from 800+ Indian D2C brands, we have identified how brands can optimise every phase of the customer journey—pre-purchase, post-purchase, and post-delivery—using structured, data-driven profiling methods.
Let’s break it down systematically.
The Three Challenges You’ll Always Face
In a digital-first business, customer relationships—whether for a new startup or a well-established company—there are 3 key stages:
Acquisition
Conversion
Engagement (Retention)
And perfecting the 3 comes only with data across customer journey stages…
I. Pre-Purchase – Intelligent Acquisition & Higher Conversions
1. Behavioural Data Profiling – Identifying High-Intent Customers
Most D2C brands still use broad audience targeting for ads, resulting in high CAC (₹200-₹600 per customer) and low conversion rates (2-4%).
Profiling approach here involves:
Session Tracking: Identifies which pages customers interact with most before making a purchase.
Engagement Scoring: Ranks visitors based on time spent, clicks, and product views.
Propensity Modelling: Uses past customer behaviour to predict who is most likely to convert.
Customer Type | Avg. Session Duration | Conversion Rate | Recommended Action |
High-Intent Visitors | >90 sec | 8-12% | Target with retargeting ads |
Low-Intent Visitors | <30 sec | 1-3% | Push introductory content |
Deal Seekers | Medium | 3-5% | Offer conditional discounts |
Application: Brands using behavioural data profiling see a 25-30% higher ROAS (Return on Ad Spend).
2. Predictive Demographic & Location-Based Profiling
Customer Profiling Insight:
Customers from Tier-1 cities convert at 2X the rate of Tier-2/3 customers but have higher return rates.
COD orders from specific PIN codes have an RTO probability of 30-40%.
Implementation Strategies:
✅ Dynamic Pricing Based on Location – Offer lower prices to high-converting regions.
✅ Adaptive Payment Options – Restrict COD for high-RTO zones.
Application: Predictive demographic profiling reduces wasted ad spend by 15-20%.
II. Post-Purchase – Reducing RTOs, SLA Breaches & Optimising Returns
3. Fraud & Risk Profiling – Controlling RTOs at Scale
Reality Check: Every 1 in 5 COD orders in India results in an RTO.
RTO Cause | Industry Avg. % | How Profiling Helps |
Fake Addresses | 20-25% | Address validation using previous order data |
Delivery Refusals | 20% | Pre-screen high-risk customers |
Multiple Failed Orders | 10-15% | Block repeated non-paying customers |
Application: Brands using ML-based fraud detection, with meticulously designed parameters/filters reduce RTOs by >35%.
4. SLA Compliance & Customer Service Profiling
Reality Check: Delayed deliveries result in a 45% drop in repeat purchase probability.
A 360° approach to SLA tracking involves:
Carrier Performance Data: Tracking which logistics partners are causing delays.
Historical Delivery Performance: Profiling PIN codes with frequent SLA breaches.
Customer Complaint Analysis: Identifying customers who frequently report issues.
Customer Type | Avg. SLA Breach Impact | Retention Impact | Solution |
High CLV Customers | Severe | High churn risk | Priority shipping |
First-Time Buyers | Medium | 50% lower LTV | Proactive tracking updates |
Low-Intent Shoppers | Minimal | Low retention risk | No special action |
Application: Brands using delivery & SLA profiling reduce customer churn by 15-20%.
III. Post-Delivery – Retention, Lifetime Value & Repeat Purchase Optimisation
5. Post-Purchase Engagement Profiling – Who Will Buy Again?
Customer retention is 5X cheaper than acquisition. Yet, 80% of Indian D2C brands focus more on new customers than existing ones.
🔍 Key Profiling Metrics for Repeat Buyers:
RFM (Recency, Frequency, Monetary) Analysis: Segments customers into High-Value, At-Risk, or Churned.
Purchase Frequency Profiling: Identifies whether a product purchase cycle is one-time or repeatable.
Net Promoter Score (NPS) Correlation: High NPS customers are 3X more likely to buy again.
Customer Segment | Likelihood of Repeat Purchase | Recommended Strategy |
High-Value Customers | 50-70% | Exclusive loyalty offers |
First-Time Buyers | 20-30% | Onboarding & education emails |
Low-Engagement Users | 5-10% | Re-engagement campaigns |
Application: Brands using purchase profiling improve repeat purchase rates by 25-30%.
6. Retargeting with Purchase & Interest-Based Profiling
Instead of retargeting all past customers the same way, 360° profiling enables segmented re-engagement:
Product-Based Retargeting: Customers who bought skincare last time? Recommend complementary serums instead of generic promotions.
Seasonal Behaviour Profiling: Customers who buy summer apparel? Retarget them at the start of the next season.
Application: Brands using interest-based profiling see 50% higher CTRs on retargeting campaigns.
Why 360° Customer Profiling is a Competitive Advantage
Metric | Without Profiling | With Profiling |
Checkout Abandonment | 65-75% | 25-35% |
RTO Rate | 40-50% | 10-15% |
SLA Breaches | 10-15% | 3-6% |
Repeat Purchase Rate | 15-20% | 45%+ |
Brands that ignore profiling leave revenue on the table.
With 360° Customer Profiling, you aren’t just collecting data—you’re using it to drive higher conversions, lower operational costs, and increase retention.
That’s the end of our talk on “360° Customer Profiling – To Maximise Ecommerce Sales.”...
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