Customer Service Automation Solution Guide (Genesys Multicloud CX)

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Use AI-powered bots and Genesys Designer to listen to your customers, orchestrating their journeys across all messaging and voice channels. Agent Assist provides realtime transcripts and knowledge in the form of automatic lookup from an FAQ database—at the moment your agent needs them.

Bots to the Rescue!

How do you figure out what your customers need, without tying up your agents?

IVRs are a big step in the right direction. But each customer is calling you because they have a specific need. And with an IVR, each customer has to listen to the same set of menu options, hoping to find one that fits.


Even with today's high-quality text-to-speech capabilities, this can lead some people to give up on self-service and ask for an agent—or even to abandon the call. A customer is overwhelmed by your IVR options


But what if your software could simply ask, "How can I help you?"—and understand right away what each customer needed? A bot asks your customer "How can I help you?"

Natural language understanding

That's happening more and more often these days, thanks to voicebots and chatbots that use natural language understanding (NLU) to determine specific customer intents.

For instance, an automobile insurance company might receive many types of calls: about broken windshields, or to increase deductibles, or to set up new accounts. Traditionally, this company's IVR would include a large group of hierarchically structured conversations, each one following a specific set of questions and answers.

You can still do that with Genesys Multicloud CX.

But you can also create intent bots that listen to what each customer is asking for—in their own words—and determine right away how to handle their request.

A customer tells a bot that their windshield is cracked. The bot says, "Sorry to hear it! Let's file a claim."

Conversational AI

While it might seem to the customer that there is a single bot that magically understands what they need, the artificial intelligence (AI) behind this magic consists of several different components, working together to enable this conversational AI.

Designer

And though the bots themselves are a major advance, the heart of all this automation is Designer, which orchestrates the bots, telling each one when it's needed.

Designer works in tandem with your voicebots and chatbots, guiding the customer journey step by step, and relying on the AI that drives the bots to help lead that journey to a successful outcome. When a customer says that their windshield is cracked, Designer looks through the available bots to find the correct one to handle this task


Designer also controls your IVRs and your agents, blending them together with your conversational AI, and orchestrating each of these aspects of your contact center. Designer also controls IVRs and agents, choosing the right option for each customer's needs


As part of this orchestration, it passes customers—and all relevant information—from one context to another, providing a seamless customer journey. Designer passes all of the available and relevant information from a bot to an agent, as called for by this customer's needs

Agent Assist

There are times when a customer really needs to speak to or chat with an agent. Genesys automation can help with that, too.

Agent Assist is like a knowledgeable supervisor sitting over the shoulder of an agent and coaching them. As a conversation proceeds, Agent Assist is using natural language understanding to determine what the customer is asking for and then—in realtime—it’s providing that knowledge to the agent. Agent assist is depicted as a bot that tells an agent, "Here's the extra info you'll need." The agent says, "Thanks! Just in time!"

Benefits and opportunities

The main benefit of this automation is that your customers will be a lot happier—often without needing to talk to an agent. And so will your agents, since they can focus on the more interesting interactions, and will have such timely help from Agent Assist.

Correct use of the self-service automation components can also lead to reduced abandons and handle times, and higher first-call resolution rates.

Here are some of the ways you can take advantage of these automation capabilities:

Interaction Types Examples
Queries
  • Frequently asked questions
  • Account balance
  • Hours of operation
Transactions
  • Bill payment
  • Product or service orders
  • Guided technical support
Business processes
  • Address updates
  • Password resets
  • Callback scheduling
Routing
  • Agent
  • Channel (chat, email, SMS, phone)
  • Another bot

Use cases

Genesys Multicloud CX supports the following Customer Service Automation–related use cases:

Self-service components of conversational AI

Here's how your voicebots and chatbots provide conversational AI by working together with Designer and the other automation components:

This infographic shows Designer in the center. Designer carries out dialog management and orchestration, implementing logic to drive the next action and create a response. This logic determines things like whether all of the entities have been filled to execute a task, or whether a knowledge article is available. Designer also manages the self-service process. The upper-left side of the diagram shows customer input and describes how speech recognition is required for the voice channel, while automated speech recognition and transcription services provide the input for bots. Bot output is displayed on the lower-left side of the diagram, which notes that text-to-speech services provide the output for bots. To the right of Designer, the diagram describes the three primary AI functions: natural language understanding (NLU) interpretation, which translates a spoken or written utterance into a format that a machine can understand; intent classification, which learns how to transform user utterances into categories that an app can act on (for instance, “I need a cheap flight to Florida” can be mapped to a flight ticket search); and entity extraction, which defines entities that represent specific details from the text—such as the departure date—so they can be recognized and acted on. The lower-middle-right section of the diagram shows how the knowledge component acts in cases where a customer’s intent corresponds to a knowledge-based question such as an FAQ or article, in which case it retrieves that information from a knowledge management system. Finally, on the bottom-right, the diagram describes how backend integration—also known as fulfillment—retrieves context about customers and their customer journeys and executes various backend tasks, such as checking balance or order status, or placing an order.

Interaction Security

Learn more about how Genesys Multicloud CX safeguards your customers and your business.

Licensing Requirements

For more information, contact your local Genesys representative.

Component Requirements

Genesys components


Component Description
Genesys Agent Assist Surfaces frequently asked questions and real-time transcripts to agents
Genesys Designer Orchestrates bots and other elements—including IVRs and agents—blending them together to enable conversational AI, passing customers and all relevant information from one context to another, and guiding the customer journey step-by-step to a successful outcome
Genesys Dialog Engine Provides a natural language understanding (NLU) engine you can use to create bots that understand and process information provided by your customers

Third-party components

Component Description
Google Cloud Speech to Text A supporting service required for Voicebots.


The Voicebot per interaction and per minute bundles include this service and Google Dialogflow.

Google Cloud Text to Speech A Voicebot-capable service that converts text into natural-sounding voices, in several languages.


The Voicebot per interaction and per minute bundles include this service and Google Dialogflow.

Supported Third-party Bot Providers

The Genesys Multicloud CX AI platform supports the following third-party NLU and bot platforms:

  • Google DialogFlow
  • Microsoft LUIS
  • Amazon Lex

Links

Here’s how to put it all together:

Bots

First of all, you need some bots.

Designer

And then it’s time to set things up in Designer.

Agent Assist

To help your agents do their best, set up Agent Assist.

Analytics

Note that Designer includes powerful analytics you can use to ensure that your automation is working as expected. If you notice anything unusual, you can modify things right away.

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