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Conversational AI: 3 Systems You Need to Scale Your Customer Support Operations

Explore How Technology Enables You to Delight Customers and Empower Service Agents
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Introduction

Every organization wants to deliver exceptional customer experiences. Customers can be fickle and aren’t afraid to abandon a brand because of a perceived negative interaction.

Prioritizing the customer experience is imperative in today’s competitive landscape. Customers have high expectations. Just one poor experience can wipe away any loyalty. According to a study, companies lose more than $75 billion in revenue as a result of bad customer service.

To meet these demands and ensure consistency and quick responses, you need technology platforms that empower customers to self-serve and enable agents to answer questions faster.

The answer? Conversational AI.

The use of AI in business operations isn’t new. For example, customer service technology often uses chatbots—which, to be fair, are rarely powered by true AI. Chatbots are useful, but the issues with delivery of service occur when companies focus solely on these for simple queries, such as where their order history is. When companies fail to consider the rest of the customer journey and the human interactions with service, either automated or with an agent, it becomes a strategy that doesn’t address the big picture.

Technology should drive faster resolutions, convenience for customers, and greater agent productivity. Chatbots alone won’t help you achieve this. Human-centered, conversational AI will.

So, how can you apply this to your customer service operations to realize ROI and retain customers and employees? We’ll answer that question in this guide, where you’ll learn:

  • The state of customer service expectations
  • What conversational AI is
  • Why “human-centered” conversational AI is vital in customer service today
  • Three pillars necessary to enhance the customer experience with human-centered AI
  • Use cases for conversational AI in customer service
  • How to get started with human-centered AI

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chapter 1
Chapter 1

Why Customer Engagement and Delightful Experiences Matter

It’s no secret that customers have elevated expectations regarding the companies with which they do business. With high competition and the ability for buyers to find what they need in a few clicks, building relationships with customers matters and impacts whether they remain your customer. The customer experience is quickly becoming the make-or-break determinant of customer loyalty.

Consider these industry stats:

65 %

of U.S. consumers state that customer experience dictates buying decisions.

Almost 1/3

of customers will leavea brand they love afterone bad experience, and 59 percent of customers in the U.S. would completely
abandon it after several negative ones.

73 %

of customers identify customer service as a factor in their buying decisions.

The stakes are high when it comes to retaining customers for the long term. So, how does conversational AI help you do this?

chapter 2
Chapter 2

What Is Conversational AI?

Conversational AI delivers humanlike interactions between computers and people leveraging a set of technologies, including:

  • Automated speech recognition, which serves to listen in voice mediums
  • Natural language processing, which comprehends
  • Dialog management, which forms responses
  • Natural language generation, which delivers the response
  • Machine learning algorithms, which continue to learn based on new interactions

Conversational AI can communicate in this manner by recognizing speech and text and understanding intent and sentiment. It can then formulate answers that play out like human conversation.

chapter 3
Chapter 3

AI in Customer Support Today

The current landscape for AI in customer service shows increasing adoption. In 2019, Gartner predicted 25 percent of customer interactions would include AI in 2020. In another report, 54 percent of customers surveyed said they use AI daily—an increase from 21 percent who said the same in 2018. That number could be far greater considering the disruptions and transformations from 2020 and beyond.

But what kind of AI are companies using, and is it really helping them solve challenges?

Simple chatbots only follow rules.

What most companies are deploying is simple chatbots or manual tagging based on keywords in the tickets. Chatbots are cruder and more robotic. They do use AI in some ways but have limitations because they must follow the “rules” of decision trees to branch to possible answers to questions. Most of the time, these could be very simple, such as, “How do I do XYZ in the software?”

Chatbots focus on keywords but not much beyond that. They return answers; however, in too many cases, the answers aren’t relevant. Chatbots also have issues with “learning” because they only derive information from decision trees. If those don’t get updated, like when you add a new product or service, they’ll be of no help.

For chatbots to provide a great customer experience, the customer’s questions have to be super simple. Anything with the slightest complexity, such as changing a subscription or asking about an invoice, and the chatbot can’t respond.

Customers expect chatbots, and they are willing to use them. But they have low expectations of what the tool can provide.

Simply adding chatbots to your customer service flow could frustrate customers more and increase the time it takes to manage their problems.

image

 

But what kind of AI are companies using, and is it really helping them solve challenges?

Chatbots can act as “deflectors.”

Another issue with standard chatbots is their deployment in isolation. Their only purpose is to prevent customer requests from reaching a support team. This act of “deflection” is self-serving to the company’s metrics but doesn’t help customers. Yes, it will reduce ticket backlog, but customers don’t get answers.

Alternatively, “human-centered” conversational AI incorporates a chatbot as one part of a larger customer service strategy. Its purpose is to answer customer inquiries quickly and accurately. Only true AI can understand past ticket history to serve answers. It also knows when it’s best to route the customer to a human for more complex matters.

Not adopting this technology could jeopardize how customers see your brand. A company with minimal self-service and customer support options may appear to be behind the times or just too inconvenient for them to engage.

Here’s an example. Suppose a customer wants to inquire about specifics to a product not included on its page before they buy. With human-centered AI, a chatbot could provide the answer but also acknowledge the intent, which may color the message to drive that conversion. A decision-tree chatbot would likely only offer what’s already listed on the product page, leaving the customer frustrated.

Chapter 4

Conversational AI in Customer Support Drives Results with These Three Pillars

To reach the next horizon of leveraging AI in customer support, you’ll need these three pillars:

brain

Advanced self-service

headset

Support triage with smart routing and prioritization

quick

Suggested answers that improve agent productivity

Meet customers where they are: Self-service options must be engaging and accurate.

Many customers lean toward being self-sufficient. Many don’t want to engage with an actual agent. In fact, 69 percent of them prefer self-service over speaking to an agent. Customers are willing to find the answers on their own.

For simple questions, you can provide them with a self-service experience that doesn’t disappoint. While there are many types of customer self-service available, not all harness the power of conversational, human-centered AI.

Most chatbots only use keyword-based decision trees to navigate customers to answers. In many cases, customers don’t find the answers they need and grow frustrated. True conversational AI understands sentiment and intent, resulting in more accurate resolutions and happy customers.

 

Self-Service Powered by Conversational AI

With this solution, you can derive many benefits, including:

  • Faster ticket resolutions, leading to better customer satisfaction (CSAT)
  • Reduction of agent workload
  • Continuous accuracy improvements as the AI is always learning based on new ticket data
  • No need for special coding; the AI immediately ingests prior support tickets to build models on how to respond to customers who need assistance
  • Coverage of all channels, including email, chat, in-app, and help center
  • Workflows that can search customer accounts for key information to handle more complex requests without further strains on agents
  • Managing fluctuating ticket volumes to meet service level agreements and reduce first response time (FRT)—our client Acorn decreased their FRT from 96 hours to less than an hour!
  • Fast deployment without the limitations of running on a set of rules
  • Multilingual capabilities to support customer inclusivity
  • Analysis of ticket trends which delivers insights that can reduce ticket loads

image

Support triage enables routing and prioritization to accelerate first response time.

Not every customer will want to go through self-service. Their questions could be more complex, they may not have the time, or many still want to communicate with agents. In those cases where a human touch is necessary, human-centered AI can assist.

AI reads every ticket and prioritizes them accordingly. AI uses historical knowledge and intent and sentiment analysis to route the customer to the right team for resolution accurately. Additionally, AI can escalate issues based on sentiment and intent, not simply keywords. Models you put in place are trained by your data to ensure greater accuracy.

It also benefits your agents by auto-detecting spam, so they’re not wasting time on this. AI can also tag tickets about product problems to deliver feedback to product teams, which provides a proactive angle for customer support. For example, you may find that product directions are missing a crucial step. By adding that into future documentation, it could decrease calls related to that issue.

Assist agents with handling customer inquiries that make them more effective and productive.

The third pillar of applying conversational AI to customer service is how it helps your agents. As a result, it improves the customer experience. The average agent spends 35 percent of their time looking for information. That impacts their response time and puts unnecessary strain on them.

First, agents can create macros and templates that are huge time-savers. These often go unused, but with human-centered AI as the engine, ingesting historical data, it points agents to the right resources for incoming tickets.

Second, new agents can onboard faster. Hiring new employees requires a ramp-up time, no matter their previous experience. Decrease it with AI-powered suggestions that get workers up to speed faster.

Third, access is easy and directly in the browser via a plugin. There’s no need to log in to separate systems, which allows agents to act more quickly.

More Benefits of Human-Centered AI Technology

  • Integrate it into existing workflows, then optimize them.
  • Provide a smart search tool that uses natural language understanding (NLU).
  • Act swiftly with past solutions and answers at the top, allowing agents to apply them in a click.
  • Vote on answers to solutions, which enables continuous learning for the algorithms.
  • Filter knowledge sources.
chapter 4
Chapter 5

Use Cases for Conversational AI in Customer Support

How can various industries use conversational AI in customer support? Here are some examples:

Manage higher volumes of inquiries.

There are often fluctuations in inquiry volume. That could be after a new product release or other internal factors. Much of the time, there is an expectation that tickets will grow at certain times, such as during the holidays. For retailers, shipping companies, and others moving products throughout the ecosystem, their customer contact numbers can double or triple.

Conversational AI can help you tame that uptick in traffic and supply customers answers they need via self-service. You’ll likely see patterns in the same questions, so self-service can handle many of these. That will dramatically decrease the number of people that need human support, and you’ll be able to route more accurately.

Collective knowledge reduces time spent on tickets.

Your agents hold critical insights and information, and conversational AI can help you tap into that by sourcing pasting tickets, knowledge bases, and time-saving shortcuts. It solves the challenge of manual work involved in locating all these resources. It makes an agent’s job easier.

AI can pull knowledge from anywhere and centralize it, so it’s easy for agents to access. Having this in their corner translates to reductions in time spent on tickets.

Maintain a healthy CSAT while also increasing cases closed.

Organizations often have apprehension about how technology could impact the human element. Companies want to keep CSAT up while also improving efficiency. With conversational AI, you achieve both without compromises.

Assist technology enables agents to be ready to respond to questions as they arrive. There’s no need for special indexing or updating of data. When agents open a new case, AI automatically provides relevant past cases, knowledge articles, and macros. Customers receive accurate and friendly service, so the interaction is quick, accurate, and friendly.

chapter 6
Chapter 6

How to Get Started With ?Conversational AI

To deploy conversational AI into your customer service ecosystem, there are a few things you’ll need to do to be ready:

  • Develop a strategy of how the AI will support customer service and what goals you need it to accomplish.
  • Compare different platforms, the features they provide, and how they align with your strategy and goal
  • Prepare data from past tickets, knowledge bases, and other resources, whether structured or unstructured, for ingestion into the AI engine.
  • Train your agents and other users on how to use the tools successfully.
chapter 7
Chapter 7

Are You Ready to Revolutionize Customer Support with Human-Centered, Conversational AI?

The customer experience is now more important than anything else. Modernizing your processes with human-centered AI ensures you continue to delight customers while also increasing agent productivity. AI as a tool can deliver so many benefits—you’ll just need the right platform.

Forethought provides end-to-end customer support optimization with conversational AI. Our customers report faster resolutions, happier customers, less agent strain, quicker onboarding of new hires, and decreases in tickets.

Modernizing your processes with human-centered AI ensures you continue to delight customers while also increasing agent productivity.

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