Difference between revisions of "CE45/Canonical"
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|SolutionCategory=CE | |SolutionCategory=CE | ||
|Solution=Digital | |Solution=Digital | ||
| − | |Title=Genesys Contact Center | + | |Title=Genesys Contact Center Optimization |
| − | |Subtitle= | + | |Subtitle=Analyze journeys holistically or as individual flows to understand journey outcomes such as self-service, deflection, first contact resolution and use new insights to improve efficiency and lower costs |
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{{SMART Canonical | {{SMART Canonical | ||
| + | |BuyerPersonas=Business Analyst, Contact Center Supervisor / Manager, Head of Contact Center(s) | ||
| + | |DataSheetImage=CE11 - genesys outbound dialer - header.png | ||
|PlatformChallenge=Increasingly, contact centers are moving to provide both self-service and agent-led support. Agent-led support is more expensive, and many are looking for ways to increase self-service, reduce the need for agent escalation, while providing positive customer outcomes. Without knowing the current pattern of behavior across digital and agent-led channels, it is difficult to identify friction, escalation, and success. | |PlatformChallenge=Increasingly, contact centers are moving to provide both self-service and agent-led support. Agent-led support is more expensive, and many are looking for ways to increase self-service, reduce the need for agent escalation, while providing positive customer outcomes. Without knowing the current pattern of behavior across digital and agent-led channels, it is difficult to identify friction, escalation, and success. | ||
|PlatformSolution=Genesys Contact Center Optimization begins with the understanding of customer behavior patterns within and across flows. For example, analysts can quantify self-service, drop-off and escalation for an IVR flow. It also allows you to filter by specific customer journey flows to view the data for that flow e.g customers making a payment. Additional events can also be added to the journey for comparison. Ultimately, this enables deeper insights via customizable charts and conversion analysis, allowing you to determine which customer journey flows have high rates of self service and which ones don't, simplifying the effort to improve those self-service methods for your customers which will improve first contact resolution. | |PlatformSolution=Genesys Contact Center Optimization begins with the understanding of customer behavior patterns within and across flows. For example, analysts can quantify self-service, drop-off and escalation for an IVR flow. It also allows you to filter by specific customer journey flows to view the data for that flow e.g customers making a payment. Additional events can also be added to the journey for comparison. Ultimately, this enables deeper insights via customizable charts and conversion analysis, allowing you to determine which customer journey flows have high rates of self service and which ones don't, simplifying the effort to improve those self-service methods for your customers which will improve first contact resolution. | ||
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Latest revision as of 14:59, November 12, 2024
Contents
Administration Dashboard
Go back to admin dashboard to create and manage platform-specific use cases in the system:
Titles and Taxonomy
| Main Title | Subtitle | Taxonomy | Product Category | Draft | Published | Edit |
|---|---|---|---|---|---|---|
|
Genesys Contact Center Optimization |
Analyze journeys holistically or as individual flows to understand journey outcomes such as self-service, deflection, first contact resolution and use new insights to improve efficiency and lower costs |
Customer Engagement |
Digital |
No draft |
Canonical Information
Platform Challenge and Solution
Platform Challenge: Increasingly, contact centers are moving to provide both self-service and agent-led support. Agent-led support is more expensive, and many are looking for ways to increase self-service, reduce the need for agent escalation, while providing positive customer outcomes. Without knowing the current pattern of behavior across digital and agent-led channels, it is difficult to identify friction, escalation, and success.
Platform Solution: Genesys Contact Center Optimization begins with the understanding of customer behavior patterns within and across flows. For example, analysts can quantify self-service, drop-off and escalation for an IVR flow. It also allows you to filter by specific customer journey flows to view the data for that flow e.g customers making a payment. Additional events can also be added to the journey for comparison. Ultimately, this enables deeper insights via customizable charts and conversion analysis, allowing you to determine which customer journey flows have high rates of self service and which ones don't, simplifying the effort to improve those self-service methods for your customers which will improve first contact resolution.
Platform Benefits
The following benefits are based on benchmark information captured from Genesys customers and may vary based on industry or lines of business: No results
High Level Flow
Info needed
Data Sheet Image
Canonical Sales Content
Personas
- Business Analyst
- Contact Center Supervisor / Manager
- Head of Contact Center(s)
Qualifying Questions
Pain Points (Business Context)
Desired State - How to Fix It