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Case study · Retail · Google Cloud

Real-Time Personalisation Engine for 5M Monthly Users

Leading D2C BrandGoogle Cloud5 months14 engineers
28%
Conversion rate uplift
3×
Faster page loads
5M
Monthly active users
<80ms
Recommendation latency
The challenge

Generic Experiences Costing Crores in Lost Revenue

The brand's e-commerce platform served the same product catalogue to every visitor regardless of browsing history, purchase behaviour, or real-time intent signals. A/B tests showed personalised experiences could lift conversion by 20%+, but the legacy recommendation engine — a batch-updated collaborative filter — refreshed only once every 24 hours and couldn't respond to in-session behaviour.

Batch recommendation engine refreshing only every 24 hours
No real-time in-session intent signal processing
Homepage load times averaging 4.2 seconds on mobile
Estimated ₹45 Cr annual revenue loss from poor personalisation
Our approach

Event-Driven ML Personalisation on Google Cloud

SkySync replaced the batch recommendation engine with a real-time event-driven architecture on Google Cloud. Every user interaction — clicks, dwell time, add-to-cart, search queries — is streamed into Pub/Sub, processed by a custom two-tower neural network, and served as personalised recommendations in under 80ms.

01

Real-Time Event Pipeline

Instrumented the frontend with a lightweight event SDK streaming to Google Pub/Sub. Dataflow jobs process 2M+ events per hour with sub-second latency.

02

Two-Tower Recommendation Model

Trained a two-tower neural network on 18 months of purchase and browse history. The model updates embeddings every 15 minutes via Vertex AI Pipelines.

03

Low-Latency Serving Layer

Deployed recommendations via Cloud Run with Redis Memorystore caching, achieving p99 latency of 78ms — down from 1.4 seconds on the legacy engine.

04

Performance & CDN Overhaul

Migrated static assets to Cloud CDN with edge caching, implemented lazy loading and image optimisation, cutting mobile load time from 4.2s to 1.4s.

Architecture

Real-Time ML on Google Cloud

Streaming

Google Pub/Sub + Dataflow

Real-time ingestion and processing of 2M+ user events per hour

ML Training

Vertex AI Pipelines

Automated two-tower model retraining every 15 minutes

Serving

Cloud Run + Redis Memorystore

Sub-80ms recommendation serving with in-memory caching

Storage

BigQuery + Cloud Bigtable

User feature store and historical event warehouse

CDN

Google Cloud CDN

Global edge caching for static assets and API responses

Observability

Cloud Monitoring + Looker

Real-time A/B test dashboards and model performance tracking

Results

Revenue Impact in 90 Days

28%
Conversion rate uplift
Measured via 6-week A/B test across 2.4M users
3×
Faster page loads
Mobile load time from 4.2s to 1.4s
<80ms
Recommendation latency
p99 serving latency, down from 1.4 seconds
₹38 Cr
Incremental annual revenue
Attributed to personalisation uplift in first year
"We'd been talking about real-time personalisation for two years. SkySync shipped it in five months and the revenue impact was visible within the first 90 days. The architecture they designed will scale us to 50 million users."
VP of Engineering
Leading D2C Brand

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