6 Best Practices for Speech Analytics Success

6 Best Practices for Speech Analytics Success

2 min read

Contact center operations are not only expensive but also fraught with compliance risk that can negatively impact an organization’s reputation, competitive standing, and revenues. A real-time Speech Analytics solution is a powerful tool for mining customer-agent interactions and driving actionable intelligence aimed at improving interaction efficiency, agent productivity, compliance and customer satisfaction. In a survey by Opus Research, 72% of the respondents said the primary benefit of Speech Analytics is enhanced customer experience, while 68% regard the technology as a cost-saving mechanism, and 52% believe it can boost revenues.

If you are considering deploying Speech Analytics, here are six proven best practices to fine-tune your strategy.

#1 Tackle high-priority areas first: Aligning Speech Analytics efforts with pressing business challenges is key to driving early ROI. For instance, if your ‘service to sales’ function is not yielding enough cross-selling or up-selling opportunities, use Speech Analytics to analyze those interactions first and identify the factors that lead to poor customer interest. Leverage the insights to accordingly modify your customer service modules.

#2 Understand the context of customer conversations: Speech Analytics systems must go beyond keywords to capture customers’ intent and emotions. Advanced systems can identify the root cause of problems from the context of the conversations and enable multi-level drill down to refine searches and reveal issues that may not crop up in a high-level search.

#3 Integrate agent’s desktop data with Speech Analytics: Call recordings alone do not provide enough customer history. For instance, using call data, a mortgage provider cannot ascertain if people from a certain geographical region are more likely to default on their loans. However, integrating desktop data with Speech Analytics can help uncover the specific age-group, employment history, and other details of people from that specific region – a crucial enabler in improving ROI.

#4 Make Speech Analytics and quality monitoring work in tandem: Use Speech Analytics to transform quality monitoring processes by enabling supervisors to quickly filter interactions that don’t convert or end satisfactorily, rather than having to skim through all interactions to identify the pain points.

#5 Deploy the right resources: Build a cross-functional team of professionals and empower them with the right skills to lead the Speech Analytics program. Do include members from the customer-facing teams so you can leverage their expertise to enhance analytics.

#6 Test, review, and revise: Once deployed, be sure to continuously monitor and measure the pre-defined metrics to optimize your strategy.

Not All Speech Analytics Solutions are Created Equal – Choose Yours Wisely

The Opus Research survey indicates that businesses are increasingly preparing to invest in Speech Analytics solutions over the next 1-3 years. For organizations looking to deploy the technology, the key is to look beyond keyword searching of call recordings and siloed solutions. Instead, opt for an automation-driven analytics platform that enables enterprise-wide integration across channels for a 360-degree customer view.

Download the Opus Research Speech Analytics survey report commissioned by Uniphore for in-depth information.


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