OmniPulse | Real-Time CX Intelligence Platform
Client / Industry
Multi-location enterprise / customer experience management
🛑 The Business Challenge
The client is an established multi-location enterprise with hundreds of customer touchpoints. Legacy feedback loops suffered from survey fatigue, delayed data aggregation, and an inability to empower frontline staff to act before dissatisfaction became public churn.
- 48-Hour Feedback Lag: traditional email surveys let critical dissatisfaction go unnoticed until negative reviews surfaced publicly
- Low Response Density: lengthy questionnaires suffered from sub-2% response rates, creating non-representative data
- Siloed Store Data: physical locations, contact centers, and digital portals lacked unified scoring for CSAT, NPS, and CES
- No Service Recovery: frontline teams had no automated mechanism to engage detractors before they left the store premises
Solution: A 3-Tier Real-Time CX Architecture
We engineered a proprietary, real-time Customer Experience Management ecosystem from concept to cloud deployment, built around omnichannel ingestion, NLP sentiment intelligence, and closed-loop triage.
- Omnichannel Micro-Surveys: Lightweight, mobile-first survey completions in under 10 seconds via dynamic QR codes, SMS webhooks, and e-commerce web modals
- Real-Time NLP Engine: Processes raw qualitative feedback to categorize operational themes and compute standardized CSAT/NPS/CES scores
- Closed-Loop Triage: Dispatches automated SMS and push alerts directly to on-duty managers within 60 seconds of a negative submission
- Executive Benchmark Scorecards: Region-by-region NPS/CSAT comparisons and operational ranking leaderboards for HQ
💻 Modern Technical Architecture
Frontend: React & TypeScript for the survey designer and manager action hub
Backend Core: Node.js & Express for omnichannel ingestion and orchestration
NLP Engine: Python (FastAPI) for real-time sentiment tagging and topic categorization
Data & Cache: PostgreSQL with Redis for sub-200ms real-time pipeline performance
Cloud Stack: AWS ECS & Docker for containerized, horizontally scalable deployment
Technology
📋 Project Technical Summary
| SEO Category | Technology Implemented |
|---|---|
| Industry | Multi-Location Enterprise / CXM & Analytics |
| Core Stack | React/TypeScript, Node.js/Express, Python (FastAPI) |
| Data & Cache | PostgreSQL, Redis |
| Infrastructure | AWS ECS, Docker |
| Engagement | 4+ years, ongoing engineering team |
| Key Outcome | 65% faster escalation turnaround, +34% retention |
Result
Escalation turnaround cut by 65% (from ~48 hours to under 15 minutes), with a 34% lift in customer retention
Business Impact
Reduced dissatisfaction resolution from a 48-hour lag to under 15 minutes, letting frontline teams recover at-risk customers before they left the premises
🚀 Project Results & Impact
⚡
65% Faster Escalation: Response turnaround cut from ~48 hours to under 15 minutes
📈
4.2x Feedback Volume: Frictionless sub-10-second surveys drove a 320% ingestion growth in representative sample sizes
🤝
34% Retention Lift: Automated frontline service recovery protected customer lifetime value
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