Automating Quality Assurance in Contact Centres
The advent of social media, chatbots and email are mere examples of how digitalisation has transformed the way companies interact with their customers. Throughout the inclusion of these mediums, phone support still remains a popular option for customers and the primary touch-point for engagement; therefore accounting for a prominent piece of the Customer Experience (CX) puzzle.
A cross-section of day-to-day call centre operations will likely reveal an animated leadership team scrambling towards the alignment of quality assurance, metrics and the rapid implementation of process improvements. In an attempt to fill the communication gaps, major efforts are attuned to the support and training of customer service staff who are tasked with quickly and accurately resolving customer queries. Increasingly, customers are demanding better service and faster resolution times. These heightened expectations present a two-fold scenario in which brands will either innovate to thrive, or stagnate and fail to meet customer needs.
The role of Quality Assurance
Quality Assurance in the call center environment functions as a support sentinel charged with consistently gauging customer satisfaction by monitoring calls. With access to countless customer calls and customer data, QA analysts have the power to recognise potential issues presented as themes throughout customer communications, and they can then use this information to validate an intervention, remedying the situation swiftly. QA teams are also useful in generating significant insights that will inform short and long-term strategies across the company.
How QA thrives when leveraging voice analytics
Previously, QA analysts were limited by the number of calls that they could successfully monitor. While call recordings seem unending, the capacity to analyse them simply isn’t. As such, a large number of customer calls are lost in the feedback void. Technological developments in the field of speech analytics and automation have yielded countless opportunities for use within QA roles. For one, you have the ability to "listen" to far more calls and glean deeper, more actionable insights for the benefit of both the customer and the organisation.
Seeing further with customer Sentiment Analysis
While Speech Analytics represents the process of analysing recorded calls for the purpose of extracting insights from customer interactions, Sentiment Analysis speaks to the advanced ability of deep-learning algorithms to contextually mine and ascribe subjective meaning to voice and text. As a result, QA teams are able to automate the task of listening to hours of recorded conversations for meaning, and instead, outsource the labour. Speech analytics will lead you to insightful information which can be used to make important business decisions.
Flag bad sentiment faster
Automation, speech analytics, and sentiment analysis make it easier to flag issues in real-time conversations with customers. This means that individuals tasked with QA duties are able to "listen" to more calls as they happen, thereby exposing problems for faster solutions and the potential to upend a widespread issue.
Transform audio data into text
Speech analytics presents the added utility of turning voice data into text. The benefits of which cannot be overstated, specifically in call centres that go through large volumes of customer data and activity. For teams, text is a simpler format for sharing as well as searching through a great deal of information. Whether for process improvement, conducting audits, or the act of customer discovery, this data is now available to relevant stakeholders within the organisation when they need it.
The bottom line: Big Impact Innovations
The road to operational excellence is paved with customer insights. For your organisation to gain high-level intelligence that can be used across the board, innovative solutions are a necessity. With powerful analytics tools at your disposal, your organisation can reap the benefits of speech analytics and context-sensitive sentiment analysis; making it simple to gain an accurate understanding of your customer’s needs and wants. Use customer discovery tools to uncover trends, solve problems, and discover new ideas for products and service offerings.
With Voyc, customer feedback is processed using Natural Language Processing (NLP) and voice analytics in order to analyse customer calls for the purpose of gleaning actionable insights. We offer seamless integration with all conversational inputs at your contact centre, in turn creating new benefits and opportunities for your organisations.
Interested in a platform demo? Our team is ready to guide you.