25 tips for optimizing your contact center's QA practices
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October 23, 2014
Speech analytics isn’t a new concept; the earliest versions of this technology, known as audio-mining or word spotting, came on to the scene more than a decade ago. However, DMG Consulting predicts the speech analytics market, which has been growing at a rapid clip since 2004, will continue to expand over the next several years, growing by roughly 20% in 2014 alone.
As noted in a Smart Customer Service article, “current speech analytics technology boasts accuracy significantly greater than 80 to 90 percent. With improved accuracy, speech analytics have been working diligently to improve the speed at which results are delivered.” But, while many vendors now offer real-time speech analytics solutions, a quantifiable ROI depends on actual results, not just the capability to uncover voice data and performance insights that will lead to results.
The following is a look at 3 reasons why it’s important to see results from speech analytics in a timely manner:
1. Speed to Intelligence
In an interview with Frost & Sullivan, clearCi CEO Joe Levy defines speed to intelligence as the “heart rate of an organization.” It’s about being able to monitor proactively combined with the efficiency of being able to react as quickly as possible, Levy says.
While speech analytics solutions are currently in use in roughly a quarter of organizations (predominately used by services, outsourcing, and finance organizations), meaningful, actionable intelligence requires information that can be synthesized and acted on in a timely fashion. In other words, if it takes three months for information to get out of the system, it defeats the point of having speech analytics technology in the first place.
2. Key Information Across the Organization
Information captured from speech analytics solutions isn’t meant to be disseminated to company leadership alone; in fact, a key benefit of this technology is being able to uncover performance insights and agent satisfaction metrics that can be used to motivate and empower agents to improve their performance. In that sense, it’s critical to be able to turn voice data into intelligence so that everyone, from agents to key decision makers, can promptly act on it.
With CallMiner RPM, the industry’s first results assurance program for interaction analytics, companies pay only 85% of their analytics subscription price until their desired benchmarks are achieved. This multi-step results assurance program is designed to help customers achieve quick wins and targeted returns with speech analytics.
3. Information-Capture Across Channels
With customers now relying on multiple communications channels (voice, email, live chat, social, etc.), it’s becoming increasingly important for companies to meet customers on the channels they prefer to use. Research shows the multi-channel analytics market is predicted to more than double over the next five years, indicating that companies are embracing multi-channel analytics in an effort to unify the view of the customer across channels.
However, efficiently collecting and analyzing data (including metadata) across channels can be challenging, especially when the customer experience is on the line (i.e., a customer who has to repeat information already provided via another channel may become frustrated, thus escalating the call). For this reason, it’s important to have a cross-channel speech analytics system in place, which can quickly and easily capture information across channels in one application.
As speech analytics technology continues to evolve, it’s likely that the speed at which results are delivered will also improve. As mentioned above, it’s critical to get results from speech analytics in a timely manner so that everyone across an organization can react to information captured as quickly as possible. This is especially important in today’s consumer-driven landscape, with customers expecting responses and solutions to their queries and concerns in close to real time.
Image Credit: ©iStockphoto.com/borisyankov
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