Subscribe to our FREE monthly newsletter
Rapide revolutionises call centre customer feedback with Speech to Insight analysis
Rapide has launched its new “Speech to Insight” analysis system, helping businesses and big brands to gain stronger insight into customer perceptions.
Rapide’s latest real-time feedback solution provides highly accurate analysis of recorded verbal feedback without the need for human transcribers. It also cuts the time taken to review feedback, allowing brands to achieve a more comprehensive overview of their customers’ opinions in a much shorter space of time.
HTML Comment Box is loading comments...
“Accurate analysis of customer feedback is imperative at a time when companies are increasingly realising the value of engaging directly with their customers and using this insight to fine tune their product and service offerings,” commented Nigel Shanahan, Managing Director at Rapide.
“Our new “Speech to Insight” functionality offers businesses the opportunity to capture call centre customers’ feedback at the critical moment when the customer is most engaged with the brand. Since we perform the analysis as well, businesses receive a full service from data capture to analysis report, which ensures that the process is both time and cost efficient.”
Traditionally, capturing feedback from call centre interactions has involved manual transcription, after which a brand would review feedback in text form. Alternatively, many call centres simply conduct surveys on a “marks out of ten scale” and do not gather further information as to why a customer has selected a particular rating.
“Speech to Insight” works by transcribing verbal feedback or audio files into text digitally. Comments are then processed through Rapide’s Rant & Rave Sentiment Engine (providing real-time analysis) and results are presented on a bespoke dashboard, allowing companies to see real-time graphs, statistics, categories and league tables as well as individual comments.
The system also has the ability to recognise a “confidence” level in feedback gathered. This means it is intelligent enough to recognise any uncertainties or misunderstandings in feedback, which can be flagged up for human input. This removes the element of computer error.
