eWeb Customer Care Application

Purpose and Business Outcomes

The eWeb Customer Care application is an omnichannel platform for handling customer inquiries across email, chat, voice, social, and web forms in a unified workspace. It centralizes case management, knowledge, and analytics so teams can reduce repeat contacts and resolve issues faster. By consolidating tooling and automating repetitive steps, organizations typically lower cost-per-contact and improve both customer and agent experience without expanding headcount.

Success is measured with hard metrics. A well-configured eWeb deployment targets a 15–25% reduction in Average Handle Time (AHT) within 90 days, 8–12 percentage-point improvements in First Contact Resolution (FCR), and a CSAT uplift of 0.2–0.6 points on a 5-point scale. With standardized SLAs, median email response times can be brought under 4 hours, and live chat response to sub-20 seconds during staffed hours, supporting 24/7 coverage through deflection and virtual agents.

Core Features and User Workflows

Agents work from a single queue that merges all channels, with auto-triage using intent detection, language, and priority tags. SLA timers, collision detection, and canned replies reduce friction, while internal notes and @mentions streamline collaboration. Knowledge is built-in: agents can search AI-suggested articles, link solutions to cases, and trigger article feedback loops to close content gaps tied to deflection and FCR results.

Workflows cover the entire journey: intake and deduplication; skills-based routing; macro-driven resolution; and policy-based escalations (for example, Level 2 after 2 failed attempts or after 30 minutes of idle time). For chat, concurrency caps (4–6 sessions per agent) balance speed and quality; for voice, call pops and disposition codes standardize post-call work. Quality assurance can sample 5–10% of cases weekly using scorecards aligned to compliance and empathy standards.

• Omnichannel inbox: email, chat, voice (SIP), SMS, WhatsApp, Facebook, X (Twitter), and web forms; configurable business hours and holidays per queue.
• Automations: intent models with >90% precision on top intents after 4–6 weeks of tuning; macros that update fields, insert text, and route or close cases in one click.
• Knowledge and self-service: article versioning, approvals, and SEO-ready help center; target 20–40% deflection via recommended content and guided flows.
• Case management: parent/child cases, SLAs by priority (e.g., P1: 15 min response/2 hr resolution), custom fields, attachments up to 50 MB, and privacy redaction.
• Quality and coaching: rubric-based scoring, automated sampling, calibration sessions, and side-by-side coaching with session replays where supported.

Architecture and Integrations

eWeb follows an API-first architecture. Services expose REST and GraphQL endpoints with webhook callbacks for real-time updates. A message broker (e.g., Kafka or RabbitMQ) decouples ingestion from processing, ensuring steady performance during spikes. Typical throughput supports 200–400 transactions per second (TPS) with p95 API latency under 250 ms when deployed with horizontal autoscaling and in-memory caching for hot datasets (queues, user states, and SLA timers).

Integrations are standardized: CRM (Salesforce, Microsoft Dynamics 365) via REST and bulk APIs; identity via SAML 2.0/OIDC SSO and SCIM 2.0 for user provisioning; telephony via SIP/VoIP providers (e.g., Twilio, Amazon Connect) with call events synchronized in real time; and email via M365/Google APIs or SMTP/IMAP with OAuth 2.0. Webhooks deliver events for case updates, SLA breaches, and survey submissions. ETL connectors ship data to warehouses such as Snowflake, BigQuery, or Redshift for downstream analytics.

Data, Analytics, and KPIs

Operational data is split into hot (cases, conversations, SLAs, user presence) and warm stores (survey results, QA scores, knowledge signals). PII and PCI data can be segregated by field-level encryption and tokenization, while access control enforces least privilege. A nightly ETL aggregates interaction-level data into hourly/day-part fact tables, enabling cohort analysis, root-cause breakdowns, and seasonal forecasting. Typical retention is 24 months online with cold storage beyond that based on policy.

Dashboards refresh every 1–5 minutes for live operations and hourly for trend analyses. Executives track outcomes like cost-per-resolution and churn correlation, while team leads monitor agent occupancy (target 75–85%), backlog, and SLA adherence. Alerting triggers when metrics cross thresholds (e.g., queue > 30 waiting or SLA breach risk > 5%). Customer feedback funnels into topic-based sentiment reporting to identify product defects and documentation gaps.

• FCR: percentage of cases resolved without follow-up in 7 days; target 70–85% depending on complexity.
• AHT: handle + hold + after-call work; target 4–7 minutes for chat/voice, 8–15 minutes for email.
• Service Level: percent answered within X seconds/minutes; chat 80/20, voice 80/30, email 90% within 4 hours.
• Deflection Rate: percent of intents resolved by self-service; sustainable target 20–40%.
• CSAT and CES: rolling 30-day averages; investigate if CSAT drops >0.2 points or CES rises >0.3 points week-over-week.

Security, Compliance, and Privacy

Security controls include TLS 1.2+ in transit, AES-256 at rest, automatic key rotation, and secret management in HSM-backed vaults. Role-based access control (RBAC) limits data exposure; IP allowlists, device posture checks, and session timeouts protect access. Audit logs capture authentication, exports, permission changes, and data views; immutable storage retains logs for 365 days by default, configurable per policy. Rate limiting and WAF rules mitigate abuse and credential-stuffing attempts.

The platform is designed to support SOC 2 Type II and ISO/IEC 27001-aligned controls, with data residency options (e.g., EU/US regions) to satisfy GDPR. Data Processing Agreements and subprocessor disclosures should be maintained. Pseudonymization and field-level redaction minimize risk, and retention policies can auto-delete or anonymize after 24–36 months. For regulated workloads (e.g., HIPAA), enable encryption, access logging, and documented BAAs; accessibility targets WCAG 2.1 AA for agent and customer interfaces.

Deployment, Costs, and Scalability

Deployment models include SaaS, private cloud (AWS/Azure/GCP), or on-premises containers orchestrated via Kubernetes. A reference sizing supports 250 concurrent agents with 8 vCPU/16 GB RAM for the web/API tier, 4 vCPU/8 GB for workers, and a multi-AZ database with 2–4 vCPU/16–32 GB RAM, scaling horizontally under load. Autoscaling policies respond to CPU > 65%, queue depth, or p95 latency > 300 ms; canary releases and blue/green deploys reduce risk during updates.

Budgetary guidance: license costs often range $35–$85 per named agent/month depending on channels, WFM/QA add-ons, and analytics. Telephony adds $0.007–$0.03 per minute depending on carrier and recording. Infrastructure for a 250-agent private cloud footprint typically runs $1,800–$3,200/month (compute, database, storage, egress). A 3-year TCO model should include 15% annual growth, 10% contingency, and training at 8–12 hours per agent at fully loaded labor rates.

Implementation Timeline and Change Management

A practical rollout spans 10–14 weeks: discovery and design (2 weeks), configuration and branding (2–3 weeks), integrations and data migration (3–4 weeks), UAT and tuning (2 weeks), training and pilot (1–2 weeks), then phased go-live (1 week). Parallel runs with the legacy system for 1–2 weeks reduce cutover risk. Define exit criteria: 95% of critical workflows pass UAT, data parity validated on 3 days of parallel operations, and onboarding materials approved.

Change management is structured: role-based training (agents 8 hours, supervisors 12 hours, admins 16 hours) with sandbox practice and certification quizzes. Migrate knowledge in batches, redirect legacy URLs, and monitor deflection impact daily for the first 30 days. Communications should set expectations on SLA changes, escalation paths, and how feedback is captured; weekly steering reviews resolve blockers and approve adjustments to macros, routing, and article taxonomy.

Operations, SLA, and Support

Standard uptime SLA is 99.9% monthly (maximum 43.8 minutes downtime/week or ~43.8 minutes/month on a strict 30-day basis equals 43.2; operationally budget 52.6 minutes). Incident response targets: Sev1 acknowledgment within 15 minutes and mitigation within 1 hour, Sev2 within 1 hour/4 hours, and postmortems within 5 business days. Backups run continuously with a 15-minute RPO and 1-hour RTO; quarterly disaster recovery tests validate failover and restore procedures.

Monitoring covers application health, queue depth, SLA risk, and integration status, with alerts sent to on-call channels and a status page. For assistance, a typical support channel mix includes 24/7 phone at +1-555-013-0000, email at [email protected], and a portal at https://support.example.com/eweb for tickets and release notes. Maintenance windows are scheduled with 7-day notice for non-urgent changes; data export APIs and daily S3 snapshots enable customer-controlled backups and analytics.