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Customized Service Recommendation Platform

ein-des-ein.com

Business services

Information technology

Consulting

Current Challenges in Service Selection

Manual service discovery processes lead to inefficiencies, inconsistent recommendations, and missed opportunities for optimal service-client matching

About the Client

A business solutions provider specializing in connecting enterprises with tailored service offerings across multiple industries

Project Goals and Objectives

Develop an automated service recommendation engine
Improve service matching accuracy by 40%
Reduce client onboarding time by 60%
Integrate with existing CRM systems for seamless workflow

Core System Functionalities

Interactive client needs assessment wizard
Dynamic service database with tagging system
Machine learning-based matching algorithm
CRM integration module
Analytics dashboard for performance tracking

Technology Stack Preferences

React.js

Node.js

MongoDB

AWS Lambda

System Integration Requirements

Salesforce CRM
HubSpot
Stripe Payment Gateway

Technical Performance Criteria

99.9% system availability
Response time under 2 seconds
GDPR compliance
Horizontal scalability

Business Impact Assessment

Streamlined service discovery process, 35% reduction in operational costs, and enhanced client satisfaction through personalized recommendations