Buyer Digital Twin
Arjun Nair
An evolving intelligence model built from authorised digital, conversational and sales signals.
Current buying profile
3 BHKPrimary configuration
₹85L–₹1CrWorking budget
Kakkanad / InfoparkLocation preference
Self-usePurchase purpose
Decision intelligence
Primary concernPossession certainty
Secondary concernPayment schedule
Strongest affinityDD Green Village · 82%
Journey stateSite visit planned
Twin Summary
Arjun's behaviour has shifted from broad project discovery to active purchase evaluation. Repeated possession and floor-plan interactions indicate that timing certainty and 3 BHK suitability are now the decisive themes.
Recommended strategyResolve possession confidence first, then move directly to site-visit confirmation.
How the buyer twin evolved
Day 1
General search
3 BHK near InfoparkDay 4
Preference forms
Green Village repeatedDay 7
Budget known
₹85L–₹1CrDay 9
Project affinity
82% Green VillageDay 11
Concern detected
Possession timelineDay 13
Intent rises
Site visit requested
General search
3 BHK near InfoparkDay 4
Preference forms
Green Village repeatedDay 7
Budget known
₹85L–₹1CrDay 9
Project affinity
82% Green VillageDay 11
Concern detected
Possession timelineDay 13
Intent rises
Site visit requested
Signal confidence
| Signal | Evidence | Confidence |
|---|---|---|
| 3 BHK preference | Floor-plan views + chat | High |
| Possession concern | Repeated page + chat question | High |
| Budget range | Explicit conversation | High |
| Project affinity | 4 sessions + repeat views | Medium-High |
Human controls
Pulse supports judgement; it does not replace it.
Salesperson can correct profile assumptionsExplicit updates override inferred preferences.
Evidence is visibleKey recommendations are tied back to source signals.
Consent and data policy applyProduction implementation depends on authorised tracking and integrations.