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Without the aid of being able to read body language, call center staff are at a disadvantage for picking up on emotional cues in calls or text communications that are obvious to sales reps when they're meeting customers face to face. But new emotional analytics technology can help overcome this deficit.
Leading enterprises are now starting to weave emotional analytics and emotional intelligence into their CRM strategies. This can lead to improved call center communication with customers. Moreover, integration with back-end CRM databases can improve customer interaction and engagement across other channels.
"Emotion is the most significant driver of loyalty, so it's important to understand how your customers are feeling," said Bruce Temkin, managing partner at the Temkin Group, a customer experience consulting firm. "If your customer experience is starting to make people feel confused or upset, then it's good to see that happening as soon as possible so that you can correct any issues before you lose too many customers."
Numerous vendors entering space
CallMiner, NICE Systems and Beyond Verbal Communication Ltd. have all developed emotional analytics integrations directly into front-line call center CRM systems.
More recently, several other vendors have started integrating a wider variety of emotional analytics for measuring emotions in facial expressions, text communications, social media and customer surveys. For example, Confirmit has integrated together Salesforce and Affectiva, a facial emotional analytics service, to bring emotional analytics to its customer survey process.
Earlier this year, Apple purchased Emotient, an early player in facial emotional analytics, which brings new legitimacy to the field, said Gabi Zijderveld, chief marketing officer at Affectiva.
Other vendors offering innovative emotion tracking solutions included in the Temkin Group's Intensify Emotion Showcase include BigEars, Cogito, Confirmit, CrowdEmotion and Mattersight. Leading cloud vendors, including IBM, Microsoft and Amazon, are beginning to provide emotional analytics and sentiment analysis APIs, as well.
Improving customer service interactions
The most obvious use case for emotional analytics is to improve call center interactions.
"Emotional recognition gives managers an efficient and cost-effective way to receive a detailed overview of all calls managed by an agent during a shift over a period of time, rather than [being] limited to random call monitoring," said Tatiana Shchertsovsky-Sherfi, marketing manager at Beyond Verbal.
Performing an analysis of recorded contact center sessions provides a detailed evaluation of an agent's emotions and reactions during interactions with customers. The engine determines an agent's effectiveness and the quality of service provided, together with a detailed evaluation of the atmosphere in which the call was conducted (empathetic, arrogant, patronizing, apathetic, etc.) It is also an effective personalized self-improvement tool, furnishing a comprehensive assessment for each agent, thus providing a positive framework for improvement.
Shchertsovsky-Sherfi said some of the ways emotional analytics has been integrated into CRM to improve call service include:
- Speeding up the review process by focusing on the most problematic calls and behavior patterns.
- Removing the subjectivity of staff assessment.
- Facilitating a review of basic parameters, such as efficiency and aggressiveness, for each call on a daily or weekly basis; thus easily identifying trends, such as degree of improvement over time.
- Increasing the quality and productivity of a contact center's workforce.
Overcome consumer fears with better service
Implementing an emotional recognition strategy could lead to some consumer backlash.
"In the end, the backlash will go away," Temkin said. "And companies that use the data appropriately will likely outperform their peers."
If enterprises can provide people with value, they will overcome their trepidation about emotional analytics, similar to the way concerns about Facebook privacy have since waned.
Going forward, experts expect emotional analytics technology to become more ubiquitous.
"We will see more emotional analytics technology in more consumer-facing solutions, like education and online learning," Zijderveld said.
The technology could also bring vast improvements to healthcare services.
"The ability to extract vocal biomarkers in a nonintrusive, continuous and passive manner is going to revolutionize conventional patient care," Shchertsovsky-Sherfi said. "This shift will be achieved by gathering an additional layer of personal data, which can support the tailoring of healthcare services to individual needs -- a service which is challenging for all healthcare providers to deliver today."
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