Speech Analytics in the Call Center


Speech Analytics in the Call Center










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Speech Analytics
in the Call Center

by Faulkner Staff

Copyright 2021
Faulkner Information Services. All Rights Reserved.

Docid: 00011265

Publication Date: 2106

Report Type: TUTORIAL

Preview

Speech analytics solutions are at the forefront of the corporate push to make
intelligence gained from Big Data not only valuable but actionable in
real-time. Speech analytics offers the ability to create meaningful voice data and
interaction trends to help companies improve services, reduce costs, and
grow revenue in their contact center and other business areas.

Report Contents:

Executive Summary

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The speech
analytics market has been growing at a strong clip since it came on the scene
in 2004. Barriers to growth have included low consumer awareness and a
lack of understanding about quantifiable return on investment (ROI). Vendors
now are targeting different segments, including small- to mid-market centers, and
are providing more customized solutions to boost adoption rates. In addition,
hosted or SaaS solutions can significantly reduce the initial investment and
financial commitment to deploying a speech analytics product.

Contact Center Market Trends

The advent of real-time speech analytics solutions is helping to
drive rampant growth, especially in the healthcare and account collections
segments. Despite the market developments, the flagship segment for these
systems continues to be in the security, law enforcement, and intelligence
gathering communities. In the traditional call center market, only 20 percent
of all call center seats have the benefit of speech analytics packages.1 But the
ability of speech analytics to convert unstructured data – which
represents about 90 percent of all enterprise data – to structured
metadata and the capability to work throughout the organization make speech
analytics a viable investment.

Originally
called audio-mining, in which audio files were converted to text to enable
searches of specific words or phrases, speech analytics now involves in-depth
searches based on phonetics with the ability to detect certain emotions
expressed on a phone call as well as trends within a call such as hold times,
silent patches, or agents talking over a caller. Old audio-mining techniques
offered matching accuracy rates of around 50 percent. Current speech analytics
technology boasts accuracy to a significantly greater 80 to 90 percent2. With
improved accuracy, speech analytics have been working diligently to improve the
speed at which results are delivered. Intelligence can be provided in near real
time to the business decision makers. As a result of improved technology and
capabilities, speech analytics is beginning to mature, but it is still in the
early adoption phases within the call center market.

With the
ability to increase revenue and customer loyalty and to provide direct and relevant
feedback to other areas of the enterprise – coupled with the current boom
in the Big Data segment – investments in speech analytics are expected to
continue on a steeply upward trajectory.3 Now that service
providers are offering real-time speech analytics solutions, the interest that
companies have is increasing because they can impact the outcome of a customer
interaction that is occurring in that moment. As with any technology
implementation, however, caveats exist. Processes, good management practices,
and other technologies must already be in place to ensure successful
deployment.

Description

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Originally,
speech analytics was used by government organizations to track the use of key
words or phrases to help identify security risks or threats by individuals or
entities under surveillance. The earliest versions of this technology were
quite simple and known as audio-mining or word spotting. Audio-mining
applications indexed the speech from an audio or video file by processing it
through a large vocabulary recognizer and by converting it into searchable text
files. The words or key phrases were predefined, and an operator was notified
only if a match existed. Accuracy rates were generally less than 50 percent.
Thankfully, accuracy rates using speech-to-text systems have increased dramatically in
recent years, however.

As
technology improved, organizations demanded search capabilities based on
phonetics to improve audio-mining accuracy. With this phonetics-based method,
an index of phonetic content, as opposed to the word content requiring
letter-for-letter matches, is created. As a result, the search has only to
match speech that sounds like the predefined key words or phrases. Phonetic
searches offer the flexibility of mining words, phrases, or proper names that
are not already listed in the dictionary database. Phonetics-based audio mining
tends to deliver results with accuracy from 80 percent up to 98 percent. Figure
1 provides a diagram comparing the two approaches.

Figure 1. Comparison of Two Audio-Mining Methods

Figure 1. Comparison of Two Audio-Mining Methods

In the past
several years, call centers have become interested in these technologies,
although about 80 percent of organizations still do not make use of the
technology within their customer-facing call centers.4 Many
centers have struggled to develop consistent, robust monitoring processes that
include formal feedback and coaching sessions with agents. One of the most
common reasons for poor performance in this area is because the demand on
supervisor time is too great in other operational areas. Some call center
managers began to view audio-mining as a way to better use the limited time
resources of their supervisors by having the technology identify which calls
should be monitored, for example, calls in which a reservation is booked, a
complaint is lodged, or a cancellation is requested. Until recently, however,
these solutions had not taken hold in the call center market. Enter speech
analytics.

Speech
analytics includes the audio-mining technologies described above, but typically
refers to a broader range of speech products, such as speaker identification,
emotion detection, and talk analysis. Speaker identification in combination
with audio-mining highlights specific items call center managers are trying to
focus on, such as anytime a customer tries to cancel a reservation, close an
account, or file a complaint; when an agent does not offer a greeting or close
to the call; or when an agent neglects to cite required phrases for legal compliance
purposes. Emotion detection can alert a supervisor or manager if a customer
begins to get upset or agitated with the agent. Talk analysis can identify
patterns within calls, such as long hold times or periods of silence, as well
as the frequency of an agent cutting off a caller. Speech analytics can be used
to research positive trends as well, such as when an agent presents a new
program effectively or a caller is thrilled with the service they received. For
example, Federal Express launched a program to identify instances in which
customers provided a "wow" response to the service they received.

The use of
emotion detection in speech analytics tools has been extended to deliver
analysis to agents in real time. This new capability enables agents,
supervisors, and quality specialists to get a live analysis of the choice of
words or phrases the customer uses on a call, alerting them to a growing client
sense of irritation, desperation, anger, and other emotions.

Traditional
speech analytics solutions allow organizations to search for calls by keyword,
phrase, or business category, helping users find relevant conversations quickly
to determine the underlying causes of rising call volumes, costs, and customer
dissatisfaction. A new generation of speech analytics can now help
automatically identify changes in customer behavior using technology such as
Customer Behavior Indicators. These next-generation solutions can proactively
index every single word and phrase, and can create a baseline of all dialogs
that occur within customer interactions. This capability automatically surfaces
the increases/decreases in the use of terms and phrases that may reflect a new
potential trend, without the need to predefine terms in advance.

In
conjunction with other call center technologies, such as Integrated Voice
Response (IVR) systems, speech analysis tools can help classify call types by
determining the root cause of the call, which can identify trends not readily
apparent to supervisors performing simple random call monitoring. Management
analyses and response to developing trends promote tactical changes to reduce
calls and customer complaints in cases of defective products or drive revenue
when competitors are sold out or have increased prices.

Increasingly,
speech analytics is being deployed to share the structured data derived from
raw, unstructured customer interactions with various business disciplines, such
as marketing, sales, product development, and manufacturing, to refine the
approach to rectifying core business issues and for targeting key product
improvements. Executives can examine the complaints that come
into call centers that are not related to agent performance to facilitate
strategic planning processes. As more companies pursue Big Data solutions, they
will turn to analytics to get a handle on the meaning and trends in all the
data they collect. Speech analytics is expected to play a large role in the Big
Data boom.

Speech
analytics solutions are now going beyond call data, delving into interactions
across multiple channels. Customer contact via email, text, online chat, Skype,
Twitter, Facebook, and other social media sites can now be cataloged and
analyzed to provide meaningful and actionable intelligence to the business.

Speech
analytics solutions have been purported to aid in many business functions, chief
among them being root-cause analysis. Other activities supported by speech
analytics today include the following:

  • Call classification and trend analysis
  • Customer experience risk analysis
  • Quality assurance automation
  • First-call resolution
  • Call volume reduction
  • Self-service IVR utilization improvement
  • Training needs analysis
  • New product and feature development
  • Consistent product branding and brand management
  • Incremental sales growth
  • Customer retention
  • Collections improvements
  • Identifying operational deficiencies
  • Fraud detection
  • Regulatory or script compliance validation
  • Competitor information gathering

Current View

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Since
technology companies started offering what is now the full breadth of speech
analytics, versus simple audio-mining, they have started to gain recognition
and adoption with traditional call centers. In addition, executives not
immersed in call center operations have begun to see an opportunity for other
parts of the organization, such as marketing, product development, legal,
R&D, risk management, collections, corporate security, and manufacturing,
to connect with customers in a direct way that was previously almost
impossible.

Below is a
look at some of the main competitors with speech analytics solutions. Some
well-known organizations claim to offer speech analytics; however, they simply
represent or repackage solutions by one of the providers below. In addition,
many players are now offering hosted, managed services, or Software-as-a-Service
(SaaS) solutions, including Uptivity Call, Castel Communications, and Avaya Aurix.
Again, most of these allow you to tap into their speech analytics engine
powered by one of the following platforms.

CallMiner

CallMiner, based in Fort
Myers, Florida, offers its CallMiner Eureka platform which includes Search, Report, and Analyze modules in an
on-premise or cloud-based solution format. The
platform analyzes words used to categorize each call by reason, product,
competitor, and other items; measures acoustics like call duration, silence,
noise, and stress; creates key performance indicators and statistical indices;
and integrates with other call center technologies. CallMiner
has a managed service offering for organizations looking for a low initial cost
investment that provides access to the same speech analytics capabilities.
Currently, the Eureka platform is offered as an open architecture and integration
layer package supporting all levels of call centers. CallMiner
provides the integration of speech analytics with other business data,
generates reports, provides searching tools for key terms, and customizes call
reports to meet customers’ specific needs.

In 2010 and
2011, CallMiner has added functionality that enables
Eureka to operate in a cloud environment and to redact sensitive data for
confidentiality and full PCI compliance. With the most recent Eureka launch, CallMiner
added customizable alerts based on chosen phrases and satisfaction levels, as
well as real-time streaming transcription with speaker preparation, AI-driven
next action guidance, and more. CallMiner boasts Holiday Inn, SiriusXM, The
Unlimited, and many other customers and strategic partners.

NICE

NICE
, based in Israel, combines audio-mining, emotion detection, and talk
analysis with text analysis into its NICE Cross-Channel Interaction Analytics
platform to analyze customer interactions from the phone, email, chat, social
media, and Web. The platform can provide contact center management with a
unified view of speech and other channel communications, call flows, surveys,
and agent desktop activity. NICE comes from a heritage of providing recording
compliance to organizations and security solutions to government agencies, such
as analyzing audio, video, and web content, to proactively identify security
threats. NICE has tailored its solutions to benefit the call center industry
over the past several years, as evidenced by its recent acquisitions of IEX, a
workforce management solutions provider, Nexidia, a competing voice analytics
company, and Performix Technologies, a leader in
the performance management segment of the call center market.

NICE is the worldwide leader in speech analytics with an estimated 40.3 percent market
share.5 During an intensive third-party review, NICE received perfect scores in
customer satisfaction in the innovation and speech analytics categories as well
as the top performance rating for ease of configuration, flexibility, root
cause analysis, and discovery. NICE announced in June 2010 plans to acquire eglue, a leading provider of real-time decisioning
and guidance solutions, for approximately $29 million. The combination of eglue’s solutions and NICE’s SmartCenter
suite of intent-based solutions – now marketed as the Real Time Guidance product
– allows contact centers to turn data from customer interactions into real-time
business impact by providing agents with a next-best action recommendation
during a call or chat session based on the real-time analytics of the
interaction that had occurred to that point. This kicked off a series of
acquisition that consistently expanded the company's offerings and capabilities,
including those mentioned above.

Genesys: Contact Center Solutions

Genesys, a leader in
the workforce optimization space, acquired UTOPY in 2013. UTOPY offered on of
the leading speech mining and analytics solutions as part of the SpeechMiner suite, which allowed users to process and index
audio files, translate and categorize speech data, conduct ad hoc and
drill-down reporting to better analyze event information, and segment data into
user-defined categories based on business need. SpeechMiner
also offered a customizable workflow feature that establishes executive-level dashboards
for core initiatives.

Genesys has rolled the SpeechMiner capabilities into the workforce optimization
suite. They are marketing it now as their patented “Speech-to-Phrase”
Recognition engine. The company currently claims to service more than 10,000
customers in more than 100 countries, including major entities like the US Postal Service,
P&G, and British Telecom.

Verint Systems

Based in
Melville, New York, Verint Systems offers a host of
contact center and performance management solutions, including its speech
analytics products Impact 360 Speech Analytics and Impact 360 Speech Analytics
Essentials. Impact 360 Speech Analytics is a full suite of call mining,
analysis, and reporting solutions. The Essentials product includes basic speech
analytics capabilities needed by and targeted to smaller call center
operations. Verint also offers the Impact 360
Advanced Speech Analytics solution for enterprise customers. These offerings
combine the historical expertise of both Verint and
Witness Systems, whom Verint acquired in 2007. In
2011, Verint acquired Global Management Technology
(GMT) Corporation. In 2013, Verint bought out
majority owner Comverse Technology. In 2014, Verint
acquired KANA Software, a provider of on-premise and
cloud-based customer engagement optimization solutions. Lastly, in 2018, Verint
added ForeSee, a customer relationship management firm, to the growing list of
acquisitions expanding its capabilities.

More than
9,800 "blue chip" organizations in more than 175 countries, including more than 85
percent of the Fortune 100, use Verint solutions to
capture, distill, and analyze complex and underused information sources, such
as voice, video, and unstructured text.6 For small and medium companies, Verint offers the Impact 360 Speech Analytics Essentials
product, an out-of-the-box solution.

Outlook

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Although the broadening of its target into the call center industry will
increase revenues, speech analytics providers will continue to count on
government agencies managing security and intelligence or enforcing laws, such
as the National Security Agency, the Federal Bureau of Investigation, and the
Central Intelligence Agency, to name a few in the United States, to make up the
bulk of the sales in the next several years, particularly with today's
heightened worldwide security and counter-terrorism needs. As more call centers,
however, begin to invest in this cutting-edge technology, actual results and
applications will begin to take shape, causing other centers to adopt the
solutions quickly.

Some firms that have implemented speech analytics specifically in the contact
center are touting return on investment within seven to nine months; however,
those organizations that take their time to plan for their speech analytics
solution to impact the whole enterprise are boasting investment returns within
four months. If that is indeed true, it bodes well for the industry. Early
adopters, however, tend to put a lot of resources into ensuring that their
investment is beneficial by applying it to gain an advantage over their
competition. Later adopters are often more lax in how they train managers and
supervisors to apply the technology, and may even neglect to commit dedicated
resources to leverage the technology to improve processes and quality delivery.

To improve
sales of speech analytics products, vendors have been working diligently to
improve the usability of their products and offer post-sales assistance. For an
expanded use of speech analytics products, firms could use the products to
analyze conversations held by sales team members with clients and align sales
and marketing procedures with the extracted information. Although product differentiation
has taken precedence over technology innovation in the speech analytics market,
innovation is still critical. Currently, vendors are offering stripped-down
products to meet the needs of small- to mid-market firms, pricing the product
to improve acceptance from potential clients.

The capital
investment costs can be reduced or eliminated by selecting a hosted or
SaaS-based speech analytics solution. Of course, starting with a hosted service
can allow a company to test drive the product and the service quality of the
vendor managing the implementation and providing the ongoing support.

Recommendations

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Before
selecting and deploying a speech analytics solution, a call center manager
needs to assess, and perhaps modify, current processes. For example, does a
mechanism exist today that provides a flow of critical information and customer
feedback from the call center to other operating areas such as marketing, engineering,
or executive management? What type of call monitoring process exists, and how
effectively is coaching provided to each agent? What information is vital to
supporting clients and improving operations? How will new information be used
throughout the organization? Answering these and similar questions can help an
organization better prepare for a successful speech analytics deployment.

In addition,
if a call recording solution is already in place, managers must know whether
the quality of the recordings is good enough to index and search and whether
the speech analytics solution is compatible with the recorder. When
interviewing potential vendors, evaluate how compatible a solution is with the
entire technological environment, whether the product is flexible and easy to
use, and whether changes can be made without having to hire a technical team.

Call center
managers should consider current and future operations when implementing speech
analytics. Solutions should be scalable to meet changing needs. For example,
ensure that search terms, phrases, or categories are not limited; verify that
the solution supports multiple languages; and review standard and ad hoc
reporting capabilities to validate that they meet your growing business
requirements. Some vendors are resellers of speech analytics solutions. If a
manager prefers purchasing a system directly from a manufacturer, some research
must be conducted to know who the players are, which directs them to check
references with partners and with other organizations that have deployed the
solution.

Finally,
call center managers must consider how they will staff the speech analytics
team. Speech analytics is not a plug-and-play system. It inherently requires
customization and solution must be "trained" to meet your operational
needs. In addition, dedicated resources are required to review and take action
on the intelligence these solutions provide. Without those dedicated resources,
companies are playing fire with the ability for the solution to deliver the
intended return on investment.

References

1. "Benefits of Speech Analytics for Customer Support Call Centers."
Tenfold. Retrieved June 2021.

2. "Speech Analytics Transcription Accuracy." Verint. Retrieved June
2021.

3. Ibid.

4. Ibid.

5. "NICE Maintains Its Top Position as CC Workforce Optimization Market Share
Leader, According to DMG Consulting." NICE. Retrieved June 2021.

6. "Our Company." Verint. Retrieved June 2021.

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