Personalisation Systems Built for India. Every Outcome Measured
Built on signals, not just segments, to lift conversion across every channel
Trusted by
30+
live signals behind every rStorefront decision. The personalisation system ONE CX built for a hyperlocal-retailer marketplace
94%
Of Indian consumers want recommendations tailored to their goals and shopping history. - Accenture Consumer Pulse Survey, 2025
84%
of marketers admit to running generic campaigns. - Salesforce, State of Marketing 10th Edition, 2026
Global personalisation engines aren't plug-and-play. They aren't built for Indian behaviour or the Bharat stack, and the foundations they assume aren't standard in Indian stacks.
Data sits siloed. Identity breaks. Pipelines run slow. Segments age while customers move. Vernacular gets English templates. WhatsApp gets wired last. One app serves three customers.
At ONE CX, we don't deploy another global engine, or an off-the-rack Indian one blindly. We audit your readiness, then build your system on your stack: the foundation first (identity, signals, consent), then decisions, vernacular and channels, with ROI measured per language and per tier.
Global Personalisation Fails to Adapt to India. We Build It for India.
30+
live signals behind every rStorefront decision. The personalisation system ONE CX built for a hyperlocal-retailer marketplace
94%
Of Indian consumers want recommendations tailored to their goals and shopping history. - Accenture Consumer Pulse Survey, 2025
84%
of marketers admit to running generic campaigns. - Salesforce, State of Marketing 10th Edition, 2026
Global personalisation engines aren't plug-and-play. They aren't built for Indian behaviour or the Bharat stack, and the foundations they assume aren't standard in Indian stacks.
Data sits siloed. Identity breaks. Pipelines run slow. Segments age while customers move. Vernacular gets English templates. WhatsApp gets wired last. One app serves three customers.
At ONE CX, we don't deploy another global engine, or an off-the-rack Indian one blindly. We audit your readiness, then build your system on your stack: the foundation first (identity, signals, consent), then decisions, vernacular and channels, with ROI measured per language and per tier.
Common Gaps Our Audits Keep Finding in India
One Account. 3 Users.
Accounts are shared in India. One mobile serves wife, husband and parent. The engine sees one persona built from three intents, so recommendations land on none
Consent at Signup. Activation Without It.
DPDP demands consent at activation, not just signup. Most engines check once at the record. Triggers fire without re-checking. Marketing exposed to legal.
Metro Trained. Bharat Lost
Engines train on Tier-1 patterns, then recommend to Tier-2 customers with different prices, brands and timings. Conversion stays flat.
Personalisation Compounds ROI
Each capability compounds conversion across every channel.
Personalisation Compounds ROI
Each capability compounds conversion across every channel.
Personalisation Stack, We Build for India
Foundation to activation to measurement. The first three layers are the data foundation our Data Engineering practice builds first; the last three are the personalisation system that runs on it
01
Identity Resolution
One customer, one record across mobile app, website, UPI, WhatsApp, offline and others
Live in 90 Days. Compounding From Day 91
From segment rules to a live system that lifts conversion, built on your stack, DPDP-defensible from day one.
Why the Personalisation We Build Outperforms Global Platforms
01
Foundation First, Not Another Engine
We don't deploy another engine, we build what global platforms assume exists, the identity, signals and consent our Data Engineering practice puts in first. The foundation India's stacks never had.
Foundation First, Not Another Engine
We don't deploy another engine, we build what global platforms assume exists, the identity, signals and consent our Data Engineering practice puts in first. The foundation India's stacks never had.
02
Live Signals Beat, Static Segments
Recommendations and search ranked by live signals across journeys and channels, from your own ecosystem
Live Signals Beat, Static Segments
Recommendations and search ranked by live signals across journeys and channels, from your own ecosystem
03
Consent-Governed by Architecture
Journey personalisation runs under consent governance, every nudge validated against consent state (DPDP) before it fires. No misses. No legal exposure
Consent-Governed by Architecture
Journey personalisation runs under consent governance, every nudge validated against consent state (DPDP) before it fires. No misses. No legal exposure
04
Vernacular Architecture, Not a Feature
Vernacular isn't translation. We build generation per customer, per language. Because the next 300 million customers don't browse in English.
Vernacular Architecture, Not a Feature
Vernacular isn't translation. We build generation per customer, per language. Because the next 300 million customers don't browse in English.
What Indian Growth Leaders Ask About Personalisation
What is signal-based personalisation, and how is it different from segments?
Segments group customers by demographic bracket, city tier or purchase recency, and fire the same message at everyone inside the cohort. Signal-based personalisation responds to what a specific customer did in the last ten minutes, browse depth, drop-off, UPI confirmation, WhatsApp reply, adding more depth to segments Segments respond to what a cohort did last month; signals respond to what this customer is doing now. The conversion difference is structural, not incremental
What is a personalisation decision engine?
One centralised logic governing message, offer, timing and channel for every customer. Replacing four platforms making independent decisions with one system that knows what every channel has already said before deciding what to say next. Auditable (what fired, when, why), tuneable, and consent-checked before every activation.
Why does personalisation built for global markets underperform in India?
Three structural mismatches. Identity: Indian accounts are shared, one app can serve a whole household, so engines built on one-person-one-account logic recommend to a persona that doesn't exist. Signals: India's strongest purchase signals UPI confirmations, WhatsApp engagement, dealer visits, offline purchases, rarely reach the decision engine. Language: 57% of urban Indian internet users prefer content in Indian languages, and template translation is not personalisation. Foundation has to be built for India, not configured for it.
How does the DPDP Act affect personalisation?
Every personalisation trigger running on personal data must operate within verifiable, purpose-linked consent, under an Act whose penalties run up to ₹250 crore per instance. Our architectural standard: consent checked at activation, not just at signup; purpose linked to every data class; audit trails on every decision. When done structurally, the defensible architecture accelerates personalisation legal signs off the architecture once instead of reviewing every campaign.
Do we need a CDP before we can personalise?
Not necessarily you need identity resolution, live signal capture, and consent architecture. A CDP is one way to get there; if you already run one, we build the decision layer on top of it. If you don't, we assess in the first two weeks whether your existing stack can supply the foundation before recommending any platform spend.
How long until personalisation shows measurable lift?
Foundation, identity, signals, consent by day 30. Decision engine live on priority journeys by day 60, with first lift visible. Attribution connecting decisions to revenue, audit-ready governance, by day 90. From day 91 the system compounds: models retrain on live data and the advantage widens monthly.
How do you measure personalisation ROI?
Per decision, per language, per tier. Conversion delta on personalised vs control journeys, basket and repeat-rate movement attributed to recommendation decisions, and search-to-purchase rates on signal-ranked results. Reported in revenue, with experiment-grade control, not in click-through rates.
Say Hello Headline: Build My Personalisation System. One Audit. No Commitment. One identity, one decision engine across every channel and language, measured in conversion, defensible under DPDP.