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Industry: Retail & E-commerce

Predictive ML for Indian retail & D2C brands

Churn scoring that tells you which customers to save 90 days ahead. LTV forecasts that transform your paid-acquisition bidding. RTO fraud detection that stops COD losses at checkout. SKU-level demand forecasts for cleaner warehouse planning. All deployable on Shopify, WooCommerce, or your custom stack.

15-25%
Churn reduction
25-40%
RTO reduction
20-40%
ROAS lift on CLV bidding
MAPE 10-20%
Demand forecast accuracy
The Retail ML Problem

You're running D2C on gut feel because your data lives in five different tools and none of them talk to each other.

Orders in Shopify. Ads in Meta and Google. CRM in HubSpot or Sell.Do. Warehousing in ShipRocket. Support tickets in Zendesk. Your team looks at each dashboard in isolation, makes decisions by gut, and can't tell which customer is about to churn until they've already left.

Predictive ML pulls all of this into a unified feature store, learns the patterns, and outputs actionable scores. Which customer will churn. Which order is a fake COD. Which SKU will stock out in 3 weeks. Which paid channel is overspending on tire-kickers. Your dashboards keep working, but now they show forward-looking scores instead of just backward-looking numbers.

What retail leaders ask ML to predict
  • Which customers will stop buying in the next 90 days
  • What each new customer is worth over 12 months (LTV)
  • Which COD orders are RTO risk (fake orders, wrong intent)
  • How many units of SKU X to hold in warehouse next month
  • Which product to recommend next to customer Y
  • What price point maximizes revenue on price-sensitive SKUs
  • Which paid-media segments are turning into repeat buyers
  • Which support tickets are early warnings for cohort churn
ML Patterns for Indian Retail

Six models that move revenue metrics

Churn & Win-back Scoring

Predicts which repeat customers will stop buying 60-90 days ahead. Retention team gets a ranked list. Win-back offers focus on savable customers, not on people who would've bought anyway.

15-25% churn reduction

Customer LTV Forecasting

Predicts what each new customer is worth over 12-24 months based on first-order signals. Feeds paid-media bidding rules so you spend more to acquire high-LTV cohorts and less on low-LTV ones.

20-40% ROAS improvement

RTO Fraud Detection

Scores every COD order at checkout for return-to-origin probability. High-risk orders get prepaid nudges, WhatsApp confirmation flows, or manual verification. Kills a huge margin leak on Indian COD flows.

25-40% RTO reduction

Demand Forecasting

SKU-level demand forecasts at daily / weekly / monthly granularity. Handles seasonality, festivals, weather, promotions. Feeds warehouse and purchase-order workflows for cleaner inventory.

MAPE 10-20% typical

Personalized Recommendations

Next-best-product suggestions on your PDPs, cart pages, and email/WhatsApp campaigns. Combines collaborative filtering, content-based signals, and recent-behaviour weighting. Higher AOV, higher repeat rate.

10-20% AOV lift on recommended slots

Dynamic Pricing & Discount Personalization

Predicts price sensitivity per customer segment per SKU. Personalizes discount depth in cart, email, and WhatsApp campaigns. Full margin on price-insensitive customers, strategic discounts on the rest.

Margin lift without volume loss

Curious what your data can predict?

15-min call. Tell us your platform (Shopify, Woo, custom), monthly order volume, top 3 growth or margin pain points. We come back with a data-audit checklist and prototype scope in 48 hours.

Book Free 15-min Call
Retail Stack Integrations

Fits into your storefront, ads, and warehouse tools

Storefronts

Shopify · WooCommerce · Magento · BigCommerce · Custom Rails / Laravel / Node · Headless (Next.js)

Ads & Attribution

Meta Ads · Google Ads · GA4 · CAPI · Segment · Hyros · Northbeam · Custom attribution

Warehousing & Logistics

Shiprocket · Delhivery · Blue Dart · Unicommerce · Increff · Custom WMS · GRN systems

CRM & Messaging

Sell.Do · LeadSquared · HubSpot · Zoho · WhatsApp Business API · BookMySMS · Klaviyo · WebEngage
Process & Pricing

6-9 weeks. Fixed pricing per phase.

Week 1
Discovery

Storefront review, order data audit, decision to score, business impact projection. Written feasibility.

Free
Weeks 2-3
Prototype

Baseline model on your data. Accuracy report, cohort analysis, business impact estimate. Your growth team reviews.

₹1.5-3 L
Weeks 4-8
Production Build

Feature store, retraining pipeline, Shopify or WooCommerce integration, admin dashboard, monitoring, deployment.

₹6-15 L
Ongoing
Managed Ops

Drift detection, quarterly retraining, dashboard maintenance, monitoring, quarterly business reviews.

From ₹40k/mo
FAQ

Questions D2C founders and growth leaders ask

Yes. Churn ML predicts which customers will stop buying 60-90 days ahead. Your retention team gets a ranked list, focuses win-back offers on savable customers, and stops wasting discounts on people who would have bought anyway. Typical outcome: 15-25% reduction in effective churn rate on the intervened segment. Works best when combined with a WhatsApp win-back bot.

CLV forecasts tell you what each new customer is worth over 12-24 months. This changes how you bid on paid acquisition (higher CPA is fine for high-LTV cohorts), which channels to double down on, and whether to offer aggressive first-order discounts. Marketing teams typically see 20-40% improvement in ROAS after CLV-informed bidding kicks in.

Return-to-origin fraud is a huge problem in Indian COD e-commerce. Customers place orders they never intend to accept, costing you shipping and reverse logistics. Our RTO model scores every COD order at checkout for RTO probability. High-risk orders get: prepaid nudges, WhatsApp confirmation flows, or (for very high risk) manual verification calls. Typical RTO reduction: 25-40%.

Yes. SKU-level demand forecasts at daily, weekly, or monthly granularity depending on your planning cycle. Handles seasonality, promotions, festivals, holidays, weather effects. Typical accuracy: MAPE 10-20% for stable SKUs, 20-35% for new or highly-seasonal SKUs. Feeds directly into your warehouse and purchase-order workflows.

Shopify: we pull orders, customers, and products via Shopify Admin API, push scores back via Shopify Metafields, and inject checkout logic via Shopify Functions or Script Editor. WooCommerce: standard REST API for reads, custom plugin for score writes. Custom storefronts: any REST or GraphQL API. Scores available in your admin, CRM, and via webhook for real-time actions.

12-18 months of orders (minimum 20,000 orders across at least 5,000 unique customers) for churn and LTV. 24 months of daily/weekly SKU sales for demand forecasting. Historical RTO flags for RTO models (even a few thousand cases work). Product catalogue for recommendation engines. If you have less, we start rule-based and add ML as data grows.

Prototype: ₹1.5-3 lakh (2-3 weeks). Full production build: ₹6-15 lakh depending on integration complexity (4-8 weeks). Ongoing ops: ₹40,000/month covering drift detection, quarterly retraining, dashboard maintenance. Discovery call is free.
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Stop running growth on gut feel

Book a 15-min call. Tell us your platform, monthly volume, top 3 growth or margin pain points. We come back with a data-audit checklist and prototype scope in 48 hours.

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