Analytics Turns Its Sights on Interactions

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MarketsandMarkets projects the worldwide speech analytics market to grow from $1.8 billion in 2021 to $4.5 billion by 2026, at a compound annual rate of 20.5 percent.

The same firm expects the contact center analytics market alone to reach $2.9 billion by 2027, representing a compound annual growth rate of 11.7 percent.

Speech analytics has a long history in the contact center space, and today’s solutions can do a lot to automate the delivery of insights from customer interactions, extracting valuable information from multiple customer conversations, sifting through unstructured call data to identify the probable causes of failure and success as well as identify relationships. These solutions provide a complete analysis of speaker separation, customer discontent, root-cause analysis, call topic, and visual context.

Leading capabilities include customer experience management, call monitoring and summarization, agent performance monitoring, sales and marketing management, risk and compliance management, sentiment analysis, competitive intelligence, business process monitoring, and predictive analysis. Of those, the customer experience management segment holds the largest market share, driven by the need to identify agents who need training and support and to reduce business bottlenecks.

The reduction in operational costs, better customer experiences, improved network security and privacy capabilities, enhanced visibility into processes and operations, and improved real-time decision making are the key business and operational priorities expected to drive the speech analytics market, according to MarketsandMarkets.

The technology itself, along with how it is being used in contact centers around the world, continues to evolve, opening the doors to more valuable insights for a much wider variety of uses.

“Contact center analytics is more important now than ever,” says Kathy Sobus, senior director of customer experience strategy at ConvergeOne, a digital modernization, collaboration, and cloud services and solutions provider. “Historically, organizations have tried to slice and dice information—mostly operational—on the performance of a contact center, with most vendors calling this ‘analytics.’ But to me this is more along the lines of reporting. It is still widely used and necessary for those operations but doesn’t drill down deep enough to truly be considered analytics.”

While MarketsandMarkets expects on-premises deployments of contact center analytics to continue outpacing cloud-based ones for the next few years, the move to the cloud is very significant. In fact, at Verint, one of the largest providers of interaction analytics solutions, the biggest change in the past year has been moving transcription for speech into the cloud, according to D. Daniel Ziv, Verint’s vice president of go-to-market for speech and text analytics. And there’s a good reason for it:

“Going to the cloud allows us to get significantly higher accuracy,” Ziv says. “And it makes it much easier to deploy both post-call analytics and real-time analytics,” both of which can require a lot of computer hardware, software, and processing power.

Ziv says that installing such solutions on-premises is also much more expensive and time-consuming. Conversely, with a cloud-based model, the business owner simply needs to turn on analytics, without any expensive hardware to buy.

“I think that’s a game changer,” Ziv says. “You have higher accuracy and a lot less effort.”

Verint has offered post-call analytics in the cloud for more than a year, and more recently it added real-time call analytics to its cloud-based technology.

Beyond the deployment model, Verint has also seen the market shift toward a unification of speech and text within interactions. “Voice is still a very rich channel, but we see more and more organizations adopting chat in live support,” Ziv says, noting that chat is less expensive for organizations and can be used to service many interactions simultaneously. “The volume of chat is growing, so adding text analytics for chat has become super important,” he adds.

However, before melding any data, consider what business customers are actually saying and doing, Sobus recommends. “This is still mostly historical in nature and involves teams of data scientists and those rare individuals that know what they’re looking for. This is where modeling takes place, pulling together information like operational elements, inventory levels, and customer database information to start.”

Sobus also maintains that companies can really start seeing the benefits of analytics when they start melding that data with other items, including geographical location, global events, weather, and what the competition is doing,

Analysts are using the data from chat, voice, and other sources to build an executive-level view of customer interactions, complete with various analytics, Ziv adds.

And there are many other companies, both old and new, that now offer similar technologies. One is Intermedia Cloud Communications, which in late June released Intermedia Interaction Analytics, an artificial intelligence (AI)-based feature added to Intermedia Intelligent Contact Center to extract business insights from patterns within high volumes of customer calls.

Intermedia Interaction Analytics transcribes every call (including voicemail) that comes through one or more designated call queues. It then uses artificial intelligence to analyze the call and assign sentiment tags based on the ratio of positive to negative words. Those with access to call recordings can use the recording search filter to search by sentiment or even by keyword or phrase. Supervisors can also automatically flag calls for further evaluation based on key phrases.

“Intermedia Intelligent Contact Center gives businesses and the partners that serve them the tools they need today to deliver an outstanding customer experience without the cost, complexity, resource requirement, and prolonged implementation time experienced with competing solutions. With the addition of Intermedia Interaction Analytics, business leaders are now able to sift more easily and efficiently through all of the calls within their sphere of control to identify the customer conversations that have the biggest impact on their success. And for partners, Intermedia Interaction Analytics adds even more value to a solution built to help their customers deliver exceptional customer experiences,” said Koray Parmaks, Intermedia’s vice president of contact center-as-a-service (CCaaS), in a statement at the time.

The vendor community for such solutions is actually quite large. Among the companies identified by MarketsandMarkets as key players are NICE, Micro Focus, Verint, Avaya, OpenText, Google, Vonage, Genesys, Calabrio, CallMiner, Amazon Web Services (AWS), Qualtrics (following its recent acquisition of Clarabridge), Almawave, Talkdesk, Alvaria, Castel, VoiceBase, Intelligent Voice, CallTrackingMetrics, Five9, 3CLogic, CloudTalk, Deepgram, Gnani.ai, Observe.ai, Speech-i, Batvoice, Kwantics, Speech Village, and Salesken.

Sales and Marketing Aids

Analytics are being used for everything from improving internal contact center efficiencies to marketing to fraud detection, and one of the biggest technological innovations in the past few years has been the incorporation of artificial intelligence into the basic analytics functions. The ability to have AI-based analytics in real time or near real time is driving additional investment interest from technology vendors. Invoca, for example, just last month raked in $83 million in funding to advance its platform to analyze interactions between companies and their customers to find sales opportunities, determine sales conversion metrics, optimize marketing materials, and a variety of other uses.

“When consumers look for value-added expertise in buying the right product or resolving an urgent service issue, they often escalate from digital self-service to speak with a human expert,” Invoca CEO Gregg Johnson said in a statement. “We’re using data, automation, and AI to integrate these digital journeys with conversations in the contact center, helping brands deliver a delightful experience, drive revenue, and strengthen customer relationships.”

At the NICE Interactions virtual conference in May, company CEO Barak Eilam said that after digitizing communications channels, companies can apply analytics to massive datasets to find patterns of conversations and to provide agents and bots important intelligence about customers and their issues.

“Removing friction from experiences is going to be the main catalyst for the technological innovations and strategic investments that we will be seeing over the next 25 years,” Eilam said at the time. “You know you’re doing things right when you don’t have to start with ‘How can I help you?’”

Indeed, technology innovations around analytics are quickly advancing measurement capabilities, enabling organizations to understand experiences at key moments in the customer journey, according to a Harvard Business Review Analytic Services/Genesys study.

According to the study, 81 percent of organizations believe being able to measure customer experiences along key points of the customer journey is important to their organization’s business strategy. Instead of relying on tools that provide limited visibility, leading organizations are turning to advanced analytics and machine learning to measure earlier and more often throughout the customer journey, equipping them with the insights needed to create more fluid experiences for customers.

Robust contact center analytics are also being used to measure the customer experience, with Net Promoter Score taking more of a back seat, according to Genesys.

“While NPS can provide a valuable snapshot into the customer experience, today’s technology provides opportunity for a deeper understanding of which aspects of an experience enhance or limit long-term relationships between customers and businesses,” said Peter Graf, Genesys’ CEO, in a statement. “That’s why Genesys is pioneering new ways for organizations to understand what their customers are trying to tell them about their experiences through the data they leave along their entire journey. It is those insights that organizations can leverage to action the path to creating empathetic experiences that breed trust, loyalty, and, ultimately, a competitive advantage.”

The study also found that CX leaders are the most likely to use the newest technologies, like predictive analytics and AI, to track metrics and identify actionable insights. The strategies are paying off, with 65 percent being considered more adept in linking CX metrics directly to business outcomes than those in the middle of the pack (29 percent) and laggards (8 percent).

Genesys pointed out that technology’s ability to help companies identify pain points along the customer journey greatly expands the opportunity to make each experience more fluid while improving customer satisfaction and building loyalty at every step along the way.

Compliance Confirmation

Beyond the customer service-related insights that analytics can uncover, a newfound use for analytics is to ensure that agents, bots, and other automated technologies stay in compliance when answering calls. This is particularly important in financial services, healthcare, insurance, and collections, which have very strict requirements regarding disclosures. In these industries, any deviations from the script need to be corrected as soon as possible or companies could face fines or other penalties.

Analytics technology vendors have mobilized to add these capabilities to their solutions portfolios. In May, for example, Verint partnered with Intelligent Voice to enable financial services firms to improve compliance oversight with profiling data captured by Verint Financial Compliance solutions.

The new solution, Verint Financial Compliance Profiling, combines Verint’s communications capture, data management, operational assurance, and analytics offerings with Intelligent Voice’s speech-to-text, voice analytics, voice biometric identification, and sentiment and behavior analysis capabilities.

This solution is needed more in the distributed workforce environment, according to Verint, because traders collaborate via virtual meetings, oftentimes with multiple people who speak different languages. This unique mix of dialogue creates an analytics and compliance predicament for traditional speech analysis solutions.

As important as analytics solutions are for tracking customer journeys, conversions, and compliance, companies are finding internal analytics to keep track of contact center agent performance as well.

Technology vendors like CallMiner have been big movers in this area, and in June the company unveiled expanded workforce intelligence capabilities designed to help companies improve the performance of their contact centers as a whole and individual customer service agents.

Among the new capabilities included in the solution are analytics designed to help companies optimize average handle time (AHT) by measuring acoustic signals for silence, tempo, speaking rates, and other factors that affect how long an agent is on the line. The solution can also identify the root causes for repeat contacts.

According to CallMiner, “Analyzing the interaction journey and common contact drivers, combined with shorter average handle times, identifies opportunities for call deflection, channel optimization, and self-service and informs virtual agent development, allowing agents to focus on the most important interactions. With the insight provided through automated contact dispositioning, organizations can optimize workforce planning based on call drivers and volume analysis.”

And the innovation isn’t expected to stop there, either.

“Over the next year and beyond, contact center analytics will prove that contact center automation is a revenue opportunity, transforming contact centers from cost centers to centers of excellence,” says Gadi Shamia, CEO and cofounder of Replicant, a contact center AI provider. “Contact center analytics will continue to be an important part of operational excellence for customers who want to achieve both efficiency and customer satisfaction.” 

Phillip Britt is a freelance writer based in the Chicago area. He can be reached at spenterprises1@comcast.net.

Additional Analytics Provide Added Value

RA Fischer, a medical device company, is just one of the many companies to turn its contact center analytics into an engine to better target its marketing efforts.

The company has outsourced its call center operations to 1Path, a move that Dan Moyer, its sales and marketing vice president, says was driven by a desire to create a 24/7 experience for patients instead of forcing them to leave voicemails.

“From an analytics perspective, it was important for us to see an increase in the overall new patient flow to justify the increase in spending,” he says.

RA Fischer also wanted to track where the calls were originating relative to geographics, paid Google campaigns, and organic SEO, according to Moyer. “Understanding where you are maximizing your spending is a key statistic to consider when outsourcing any of your operations,” he says.

Using analytics, 1Path was able to compile a list of the top questions that customers had when calling in.

“We used this data to drive content creation across social media,” Moyer says. “1Path created standard escalation procedures for our treatment specialists and different internal departments according to who was calling in. We receive standard, customized reports on a monthly basis that include analytics on call volume and issues—both resolved and that were escalated to our team. We then analyze the data to identify opportunities to further reduce calls to our treatment specialists, allowing them to focus on other patient responsibilities that can help us grow.” —Phillip Britt

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