getting customer satisfaction right with ai speech analytics · ai-driven speech analytics can...

White Paper

Getting Customer Satisfaction Right with AI Speech Analytics

http://www.nexidia.com

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ContentsAI Speech Analytics Isn’t Just for Call Centers Anymore ��3

The Art of “Listening” ��4

Hear What Customers are Really Saying ��5

Relate to Customer Feelings ��5

DYKWIA? ��6

Empower and Assist Call Center Employees��6

Use AI to Transform Your Organization ��6

Start Small ��7

Let Analytics Drive Quality ��7

Incorporate More Channels ��8

Drive Toward Full Customer Engagement Analytics ��8


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AI Speech Analytics Isn’t Just for Call Centers AnymoreWhen enterprise technology buyers are asked where their Artificial Intelligence (AI) investments are going in the near term, it is quite significant to see the high ranking given to speech recognition, speech analytics, and deep-learning platforms�

When applied to analyzing customer interactions in the call center, AI speech analytics is already providing a goldmine of information for helping enterprise brands get closer to their customers and deliver the kind of personal service that each customer wants� The prioritization of speech analytics dovetails nicely with the top AI investment target of “virtual agents�” Simple chatbots used for question/answer classification as well as advanced chatbots used for complex transactions know how to “talk” to customers and process natural speech� They are being used to reduce the load on call centers and expand the variety of self-service channels that customers can use to interact with a brand�

As chatbots replace human agents, the same concerns should apply for Quality Management� Enterprises should be thinking about QM tools to monitor and evaluate how their cadre of virtual agents is performing� What are the metrics to measure chatbot performance and how do those metrics fit into the overall performance metrics in the call center? Here too, AI speech analytics can be used to elicit valuable insights from chatbot interactions�

But that’s not all�

Today’s consumers can use an increasing array of digital channels beyond the call center to interact with a brand� These include email, chat, website, mobile apps, IVR, text, social media, video chat and electronic virtual assistants like Siri�™ And increasingly, consumers prefer those digital channels, especially Generation Z who have grown up using self-service apps on websites and mobile phones�

72% OF BUSInESSES

ARE FOCUSED On USInG

SpEECH RECOGnITIOn,

SpEECH AnALYTICS,

AnD DEEp LEARnInG

pLATFORMS nOW AnD

In THE FUTURE�

Top 11 AI building blocks shown. Base: 577 North American data and analytics decision-makersSource: Forrester Data Global Business Technographics® Data And Analytics Survey 2017

Virtual agents

Machine learning platforms

Decision management

Speech recognition

Speech analytics

Image and video analysis

Deep learning platforms

Facial recognition

Robotic Process Automation

Intelligent recommendations

AI-optimized hardware

28%

26%

25%

25%

24%

23%

23%

23%

21%

21%

21%

Which of the following building blocks are/will you be using for AI?


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While voice is still king in terms of customer preference, all the other channels combined add up to 3 times the number of interactions on the phone! Already, many customer interactions start on one channel and finish on another� As enterprises make more customer service channels available, seamless omnichannel Quality Management will be the only way to track and evaluate a customer journey that spans multiple channels�

the Art of “Listening”Many brands claim to put the customer experience at the center of their business and to be driven by customer satisfaction� To make good on that claim, they must be able to listen to what’s happening across all their interaction channels so they can:

• Understand customer intent, customer discontent, agent behavior, and so on�

• Understand which troubleshooting techniques work, work best or not at all

• Understand how to turn each customer interaction into a satisfactory experience

That’s why organizations who are serious about taking a customer point-of-view are investing in customer engagement solutions driven by AI analytics – and it starts with AI speech analytics�

Why focus on speech analytics when digital channels and virtual agents are starting to take off? The reason is two-fold� First, there are still many more voice interactions than digital interactions by volume� Second, as digital channels gain traction, the simpler customer interactions will be handled through self-service, leaving the more complex and emotionally-fraught problems for call center agents to resolve� Rather than easy scripts and pat answers, agents will need more advanced skills and tools to solve the “hard” problems to each customer’s satisfaction�

A GROWInG nUMBER

OF COnSUMERS ARE

CHOOSInG SELF-SERVICE

CHAnnELS OVER

AGEnT-ASSISTED�

NICE inContact customer survey, North America, 2018

WHY SpEECH AnALYTICS

REMAInS CRITICAL:

• THERE ARE STILL MAnY

MORE VOICE InTERACTIOnS

THAn DIGITAL BY VOLUME�

• MORE COMpLEx AnD

EMOTIOnALLY FRAUGHT

pROBLEMS WILL BE

HAnDLED BY AGEnTS AS

SELF-SERVICE CHAnnELS

GAIn TRACTIOn�

Source: Forrester Data Global Business Technographics® Data And Analytics Survey 2017

What channels do consumers prefer overall?

63%

Phone

53%

Email

54%

Chat

50%

Website

20%

MobileApp

20%

IVR

11%

Text

9%

SocialMedia

8%

Chatbot

6%

VideoChat

4%

Homeelectronic“Virtual

Assistant”

Agent-assisted

Self-service


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In this paper, we will demonstrate how technology advances in Speech and Language processing coupled with AI-driven Speech Analytics can provide customer-engagement insights to help you prioritize, analyze and quantify business challenges� As a result, you will be able to implement prescriptive, data-driven recommendations to improve customer satisfaction, and to gradually transform your organization to be customer-driven and analytical by nature�

hear What Customers are Really SayingAdvances in neural phonetic Speech Analytics™ are making it possible to achieve accuracy of 90% or better in speech processing rates, which far surpasses the 60-70% accuracy of traditional speech-to-text transcription� However, the real power to truly hear what customers and agents are saying is gained by combining the two technologies�

Speech-to-Text Transcription makes it easy to see and understand who is talking at any given moment� It’s a great way to probe the data to see the conversations that are occurring and to spot issues that warrant investigation� However, transcriptions are often inaccurate and search matches are confined to a predefined word lexicon, which will limit recall capability until new words are diarized� That’s where neural phonetic Speech Analytics™ comes in�

neural phonetic Speech Analytics™ eliminates dependence on a predefined dictionary or word lexicon� phonetic indexing and search capabilities are based on phonemes – the 200-300 core consonant and vowel sounds that make up any language� A typical conversation uses only 40-50 of those sounds� Clearly, it’s faster to search 40-50 commonly used phonemes to pull up data, than to search the entire word lexicon! phonetic speech analysis also includes acoustic models for a range of audio scenarios from rehearsed speech in a quiet place to spontaneous speech in a noisy place� As a result, low-quality audio with lots of background noise and heavily accented speech can still match and play search patterns vis-à-vis the speech-to-text transcription technology�

The combination of these two technologies lends a discerning ear to your organization as the AI listens to what is being said and tells you what customers want you to know�

Relate to Customer FeelingsWhat distinguishes a great customer service conversation from a mediocre or poor one? While ease and efficiency are important, the emotional state of both customer and agent will often determine the perception the entire interaction� Consider a frustrated customer who calls for assistance� Even if the problem is solved quickly, the customer may not be fully satisfied if the agent was brusque or interrupted before the customer could fully explain things�

The ability to correlate spoken words with pitch, tone, cadence, laughter and cross-talk can tell you volumes about how a customer feels� Employing “sentiment detection” within AI conversation analytics can help organizations understand the emotional side of the customer they are talking to and adjust agent interaction accordingly�

For example, analyzing different sentiments across the call can indicate that a customer is losing patience or getting angry, or on a more positive note, sounding relieved� perhaps a gradual rise in voice pitch and tone during the call, together with the use of certain words, points to customer emotions that might be getting out of control� With AI analytics, organizations can know how many of all their calls started out in a good tone but ended on a bad note, and vice versa, and why� AI analytics identifies speech and sentiment patterns as predictors of a customer’s emotional state or “sentiment score,” enabling agents to adjust accordingly�

One way to adjust is through predictive Behavioral Routing (pBR) which considers a caller’s “sentiment score” and then routes the call to the agent who has the best track record in handling that behavior profile� pBR not only increases first call resolution, it can reduce average handle time because the agent is experienced with that type of personality, speaks their language, and can get to the point quickly�


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DYKWIA?When customers ask “Do you know who I am?” organizations want to be able to say yes� For this purpose, AI speech analytics is an untapped gold mine� Just think of the things that can be known about people from the way they speak� AI speech analytics can pick up on personal demographics such as gender and age (voice tones), level of education (word choice), regional background (accent/dialect), etc�, while predictive AI algorithms shine a light on customer preferences and behaviors� Armed with this kind of insight, organizations can do even more to personalize the service and treatment given to each customer� For example, if a customer who normally uses self-service channels makes a call to the contact center, this anomaly in behavior can be flagged for possible dissatisfaction, so the call will be routed to the right agent to ensure an outcome with the highest possible customer satisfaction�

empower and Assist Call Center employeesAt some point digital channels and self-service tools will begin to have a significant impact on the kinds of interactions customers have with a live agent� As mentioned earlier, agent staff will work on more complex and emotionally fraught issues� Onboarding practices and burnout prevention will be critical to recruiting competent agents and keeping them happy on the job� By applying AI Speech Analytics to the agent side of the conversation, organizations can drive better agent performance and experiences�

• Use AI speech analytics to analyze 100% of agent conversations and get an accurate picture of both weak points and strong points in order to provide relevant coaching� With AI speech analytics doing the heavy lifting (in a matter of seconds), agents and managers no longer need to spend hours on subjective call sampling, freeing them from burdensome and inaccurate processes, while creating transparency and better conversations across the organization�

• Use AI speech analytics to dissect successful interactions by top agents in order to train and coach others on best practices that have proven successful� Bottom line – empower agents to adopt the behaviors and techniques that will make them more successful�

• Analyze agent interactions to elicit an emotional profile and use that to coach them toward better conversations and outcomes with customers�

• Monitor agent follow-up activity to ensure that what is promised to the customer is actually delivered� Tag desktop fields and include them in the AI interaction analytics�

• provide agents with their own personalized dashboard so that they can monitor their performance and regulatory compliance in real-time�

Use AI to transform Your OrganizationIn the competitive markets of today, every business must use the Big Data information at hand to take action on relevant insights in order to address the ongoing challenge of customer satisfaction� Traditional data sources such as IVR, HR, Billing systems, data warehouse, CRM systems, etc� provide incomplete information� These data sources will tell you what transpired but not why a particular event happened,

WHEn IT COMES

TO KnOWInG YOUR

CUSTOMER, IT IS JUST

AS IMpERATIVE TO

KnOW YOUR AGEnTS�


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such as why did a customer churn� This missing information can be found in the actual conversation between customer and service rep and how the interaction was resolved� Insights from these interactions can shed light into events that affect almost every aspect of a business�

The motivation to capture and analyze these interactions is clear� But with hundreds if not thousands of customer interactions per day, an organization’s ability to introduce artificial intelligence and realize its benefits can seem like a daunting challenge� Our experience has shown that the best practice is to take it one step at a time�

Start SmallWhen introducing AI to drive a successful customer engagement programs it pays to start small, but with an eye on laying the groundwork for expansion� Use AI Speech Analytics to focus on use cases that deliver fast ROI and show management that it’s working�

• How can we increase first call resolution (FCR)?

• How can we decrease repeat calls?

• How can we shorten average handle time (AHT)?

Those are simple ways to demonstrate success so the whole organization believes in it and wants to continue on to loftier goals, like customer journey optimization�

Additional options for fast results are Word Cloud discovery and Automatic Categorization, which sift and lift the most relevant data insights to the top� Many times, these AI tools help organizations realize that “you don’t know what you don’t know” until suddenly they are able to see it�

AI speech analytics can create “Word Clouds” of the key words, key phrases and surrounding words that are spoken during interactions with customers� The word clouds highlight the customer conversations that occur most often, which may point to business process issues, product defects, service issues, agent performance problems, or other problems that had been going unnoticed�

Automatic Categorization is an AI tool that deepens the insight from Word Cloud discovery by isolating the interaction topics that surround key words and phrases� For example, when a product issue is being discussed in reference to a billing issue, it could mean that the product is not being priced as the customer expects� Understanding whether those product-and-billing discussions are driving negative customer sentiment is also very helpful in discovering previously unknown topics that may need further investigation�

Let Analytics Drive QualityFocus on analytics-driven quality rather than sample-driven quality� Search for positive outcomes as well as negative outcomes� Use positive outcomes to train agents and, in effect, to “clone” the best agent behaviors� not only will organizations drive efficiency gains in their quality management team, they will reap experiential gains by not wasting an agent’s time with superfluous coaching to overcome a weakness that the agent does not really have�

TRAnSFORMInG YOUR

ORGAnIZATIOn InTO A

DATA-DRIVEn, AnALYTICAL

MInDSET DOESn’T

HAppEn OVERnIGHT�

START WITH A FEW

EASY TECHnIQUES

FOR QUICK ROI:

• InCREASE FIRST CALL

RESOLUTIOn (FCR)

• DECREASE

REpEAT CALLS

• SHORTEn AVERAGE

HAnDLE TIME (AHT)


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A critical aspect of quality management is gaining buy-in from the agents who are being monitored� Sample-driven quality is a proven dissatisfier that eats into morale and employee turnover rates, because it is perceived as unfair and unrepresentative of overall performance� With analytics-driven quality that looks at 100% of interactions, agents respond more positively because they are more in control� They are able to flag reviewed interactions as needing more discussion, to help understand their personal strengths and weaknesses, and to measure their own individual progress� The subjectivity of the reviewer is also removed from the equation in large part, so the disparity in a manager’s opinion versus an employee’s opinion is greatly reduced�

Incorporate More ChannelsOnce the organization starts to see the ROI benefits of speech analytics, data from digital channels can and should be added to the mix� For example, is a customer hitting the website over and over before giving up in frustration and calling you? Once you can see cross-channel data you will know that customer so much better� Moreover, once you can query and analyze all customer interactions, you will know if the problem is a one-off or if others are experiencing the same difficulty with your website� Ultimately, the goal is to analyze interactions quantitatively and qualitatively across all channels be it voice, chat, email, app, direct feedback, etc� to get a complete picture of each customer, as well as overall customer satisfaction KpIs�

This is also where laying the right AI analytics foundation is important� The data from different channels will have different formats, fields, etc� It is critical to start with a system that can incorporate and process all kinds of data sources as you expand to omnichannel business analytics and Quality Management�

Drive Toward Full Customer Engagement AnalyticsArtificial Intelligence has changed the economic model that used to make Customer Engagement Analytics implementation prohibitive� Today you can start with just a few, well-defined speech analytics use cases that provide fast ROI while establishing a data-driven mindset within the organization� Then, the advance to omnichannel analytics or AI-driven automation becomes the natural next step to gaining a full spectrum of actionable business insights�

As you travel the AI path, it is important to choose industry-leading building blocks, such as those offered by nICE nexidia, that provide the technologies, platforms, applications and managed services to help you advance gradually and steadily toward becoming an organization that leaves nothing to chance when it comes to understanding what each customer wants and delivering complete customer satisfaction with every interaction�

Join the analytics revolution. Learn more at www.nice.com.

Copyright © 2019, nICE Ltd� All rights reserved�

Information herein is proprietary information and trade secrets of nICE Ltd� and/or its affiliated companies� (Affiliates)� This document and the information herein is the exclusive property of nICE and its Affiliates and shall not be disclsed, in whole or in part, to any third party or utilized for any purpose other than the express purpose for which it has been provided�

All information included in this document, such as text, graphics, photos, logos and images, is the exclusive property of nICE or in Affiliate and is protected by United States and international copyright laws� permission is granted to use, view and photocopy (or print) materials from this document only in connection with the products to which this document relates and subject to the terms of license applicable to such products� Any other use, copying, distribution, retransmission or modification of the information in this document without the express prior written permission of nICE or an Affiliate is strictly prohibited� In the even of any permitted copying, redistribution or publication of copyrighted material, no change in, or deletion of, author attribution, trademark legend or copyright notice shall be made�

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getting customer satisfaction right with ai speech analytics · ai-driven speech analytics can...

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