Download our Smart Guide to discover 10 ways using voice technology can improve your contact center customer experience.
Contact centers strive to improve customer experiences across the customer journey. From evaluation and product purchase to delivery and after-sales support the need to ensure customers are happy is an ongoing priority.
According to research from Magnetic North, bad experiences cost UK businesses billions of £s a year in lost sales. It is in their best interest to offer exceptional customer service.
While it can be difficult to extract customer emotion data from text-based interactions, for voice it’s a little easier. Sentiment analysis can be performed to determine the mood of customers and which agent responses evoke positive or negative emotions based on the tone, pitch and frequency of their voice. This information can be used to inform best practices and improve the customer experience.
When people speak, often the words they use are not enough to understand what they really mean. The way people talk including word emphasis, rate of speech and volume is indicative of their feeling about a certain situation. For example, someone speaking quickly and loudly is likely to be feeling annoyed.
Call Centre Helper suggest that contact centers analyze less than 3% of customer calls due to factors such as costs, time and employee effort. This leaves 97% of voice data untouched within the contact center.
With so much voice data passing through the contact center, it is important to take as much metadata from those calls to feed into analytics systems. Sentiment data can be combined with other optimization metrics such as hold time, silence, call duration and net promoter scores to get a holistic understanding of the customer from their interactions. Spotting trends in these data points in real-time enables contact centers to make the necessary changes that impact customer engagement.
Voice technology enables companies to accurately capture spoken data which can be fed into systems that can extract sentiment from those utterances. Contact centers can perform sentiment analysis to determine the mood of customers and to inform best practices. Sentiment analysis extracts data to enhance customer experiences through continuous improvement and quality assurance.
Sentiment helps organizations truly understand customer interactions. Companies can use this information to evaluate, change and improve the perception of a brand, product, service or interaction. There is no better source of data than the voice of the customer and so capturing both what is said and how it is said is important.
Accurate speech-to-text underpins the process of transforming the customer voice into a usable format for sentiment analysis. Even the best analytics systems and sentiment engines require the right input to reach their value potential.
Sentiment analysis can be performed to understand customer’s emotions based on the way they talk, including the tone, pitch and frequency of their voice. This understanding can be used to improve customer experience in many ways.
Providing real-time insights into customer feelings enables agents to manage expectations and emotions. Engagements and issues can be escalated to managers or specialized teams to ensure the call has a positive outcome.
Agents can measure themselves against company and personal goals. They can identify areas for training and opportunities to implement new strategies to improve customer engagement and reduce customer churn.
Sentiment analysis helps organizations with product, service and brand validation. It gives organizations quantifiable data about customer perceptions. This informs campaign decisions through the evaluation of customer sentiment.
Companies can make informed decisions within the interactive voice response (IVR), based on words, speech acoustics and sentiment. Callers can also be routed from an agent to a manager or specialized team that is better equipped to resolve particular issues, in real-time. Sentiment analysis also enables mood-based training for staff to deal with challenging situations such as unhappy or angry caller.
A study from PwC found that 32% of customers are likely to move to a competitor after just one poor experience. It’s therefore important for brands to find root causes to issues to prevent other customers from having bad experiences too.
For compliance and monitoring, it’s not always enough to rely strictly on the words used in a call. A better understanding of what was meant by the words by analyzing how things were said is also important. Sentiment analysis provides a tool to identify truthful conversations, ensuring an organization’s reputation is maintained and engagements comply to legislative rules.
Sentiment and emotional analysis enable accelerated issue and dispute resolution through a better understanding of a customers’ emotional state.
For many brands, customer experience is one of the most important elements to get right. The ramifications of bad customer experience costs brands billions of pounds a year in lost sales.
Contact centers are looking for new ways to better understand their customers, improve their experiences and eliminate bad ones. Sentiment analysis is being used to understand more about customer feelings and emotions. Previously, sentiment engines have been used for text-based interactions, focusing solely on the words that were rather than how they were said. If someone says ‘great’ the sentiment engine will label this as a positive outcome. In reality, the engine hasn’t taken into account other contextual understanding of human interactions such as sarcasm.
Contact centers are using voice technology to transform customer interactions into text. This text data can be combined with other acoustic elements and fed into analytics platforms to determine the mood of customers and which responses evoke positive or negative emotions. This information can be used to inform best practices and improve the customer experience through continuous improvement and quality assurance.
Voice technology underpins the transformation of customer interactions into valuable insights for sentiment analysis. Remember, even the best analytics systems and sentiment engines require the right input to reach their value potential.