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

What's the 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.

What's the 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.

Use case overview

Story and business context

Contact Centers managers are interested in identifying the quality of their customer interactions, improving efficiency and ultimately, reducing unnecessary costs. This often means increasing the efficacy of self-service.

The proliferation of channels that customers utilize in issue resolution has made it that much more difficult. Businesses require a way to tie their customers’ experiences together to effectively enable change.

Genesys Contact Center Optimization not only creates a cohesive customer journey across channels, it allows the business to measure, analyze, and augment customer journeys rapidly to improve the customer experience.

Use case benefits

Benefit Explanation
Improved Containment Rate Identify when customers are being transferred from self-service channels to an agent at a higher rate than anticipated and enable contact center managers to take action to ensure a high rate of self-service.
Reduced Administration Costs Identify low-value interactions that self-service channels could handle. These would be types of contacts with high volumes that do not need to be handled by agents or those that result in customers making repeated calls to agents. Identify how these calls could be routed and handled by self-service channels.
Reduced Handle Time Can identify where agents are not responding promptly or issues that take a significant amount of time to resolve using journey insights and can act accordingly to resolve.
Reduced Interaction Abandonment Can identify when customers’ abandonment rate is higher than anticipated and take action to ensure customers access their desired services.

Summary

Genesys Contact Center Orchestration maximizes self-service capabilities within omnichannel service journeys, seamlessly integrating Human Assisted and Self-Service Contact Center channels. Service Journey analysis emphasizes enhancing internal efficiencies and elevating the customer experience. With over 82% of customers utilizing multiple Contact Center channels to resolve issues, and more than 70% of companies measuring First Contact Resolution (FCR) and Issue Resolution (IR) without cross-channel metrics, the need for comprehensive measurement is clear. Besides CSAT, FCR and IR are the leading metrics for assessing customer satisfaction in Contact Centers.

Use case definition

Business flow

Conversion Analysis

  1. The analyst opens a journey with the intent to perform analytics
  2. Journey is refreshed, providing conversion rates at each step.
  3. Paths of interest are analyzed by:
  • Selecting the tiles representing the path you would like to explore, confirm the selections and the calculated results will up update to show you conversion rates at each step.
  • The analyst can update conversion figures as either numbers or percentages

Journey Analysis

  1. The analyst creates (or edits) a journey with the intent to perform analysis
  2. From the event list, the analyst selects those events that define the journey they want to measure
  3. Events are drawn from the event types that Journey Management supports and can be assembled in any order across channels
  4. Events can be filtered based on unique event properties. For example, a language for a bot will define a step where users interacted with a bot in a specific langue whereas a bot with no language filter will be those that engaged with the bot across all supported languages
  5. Analysts can narrow the connectors between events based on time between the events or limit the events to the same conversation
  6. Events are analyzed based on customers. Customers is the primary joining property between the events.
  7. Analysts save and then calculate to see the number of customers that progressed through each of the events assembled into the journey.
  8. Data represents at least 30 days but no more than a year and is based on the time Journey Management has been in use.

Business and distribution logic

Business Logic

For journey analyzer and conversion analysis, Customer will require journey management for the contact center SKU and permission from their company’s administrator. There are two different types of roles for permissions. These are view only and edit related permissions.

Channels & Events include:

Voice

  • Analytics Detail Events (ADE)
  • acdStartEvent
  • acdEndEvent
  • customerStartEvent
  • customerEndEvent
  • flowStartEvent
  • flowEndEvent
  • outboundInitEvent
  • userStartEvent
  • userEndEvent
  • voicemailStartEvent
  • voicemailEndEvent
  • wrapUpEvent
  • afterCallWorkEvent
  • contactUpdateEvent

Bots

Bot Events

  • botSessionStart
  • botSessionEnd
  • botSessionTurn

User interface & reporting

Agent UI

Conversion Analysis

Conversion Analysis will be able to take advantage of your organizations Analytics Detail Events and native Genesys Cloud Bot Events. A user can view conversion rates from any starting point and along any path; highlighting customers that completed the event and those that dropped out.

Reporting

Real-time Reporting

With Genesys Contact Center Optimization, you can get to the heart of your customer’s journey.

Build customer journeys and visualize customer behavior in aggregate to uncover journeys resulting in self-service, error, agent escalation, transfer to an agent.

Determine thresholds for each Contact Center metric you’d like to measure and be alerted when anomalies occur.

Genesys is working on providing more customer journey reporting in the future, including instant previews, custom KPIs, and behavioral segmentation.

Add pre-defined metrics to inform charts and track over time (Coming soon)

Simplify root cause analysis with AI, revealing reasons for high and low performing customer journeys. (Coming Soon)

Historical Reporting

Genesys Cloud includes performance views and dashboards that enable analysts to examine interaction data across time. We also have A3S, an expert application service, that can be used to explore and analyze historical contact center data.

Customer-facing considerations

Interdependencies

N/A

General assumptions

N/A

Customer responsibilities

For charts and conversion analysis, Customer will require Contact Center Optimization SKU and permission from their company’s administrator.

Related documentation

Document version

V 1.0.0