The ability for speech to text conversion and insight extraction can make a major difference for contact centres, especially as more than 90% of interactions still rely on voice. That’s why the relatively young speech analytics market is all set for a boom. From $1.5 billion in 2020, it will more than double by 2025, at a rapid growth rate of 20.2%.
Early implementations of speech analytics show consistent ROI, in various areas of contact centre operations. 81% of speech analytics users in 2019 reported a positive ROI, and just 2% said they saw no clear benefits. Among the important benefits derived was knowledge management – the ability to capture data and information from voice, assess and organise using analytics algorithms, and aid its utilisation. Nearly half of companies (49%) already report tangible impacts on their CX after speech analytics implementation, and this number will grow further, thanks to application for knowledge management use cases.
What is Knowledge Management in a Contact Centre?
Knowledge management can be defined as the practice of capturing, organising, storing, and utilising data that are either generated or received via external sources in an integrated manner. Some of the key contact centre tasks that rely on knowledge management include:
- Validating caller identity by looking up existing customer information
- Updating customer data profiles after a call
- Retrieving different assets like catalogues during customer communication
- Accessing and adhering to brand guidelines during a call
- Providing agent training that addresses knowledge gaps
How Can Speech Analytics Improve Knowledge Management?
A contact centre’s knowledge repository can be large and complex, making it difficult to navigate and come up with results on time. Speech analytics adds an element of speed, accuracy, and ease of use to knowledge management by:
- Automating knowledge capture from calls – It removes the need to manually jot down notes, create summaries, and update the data fields in a customer profile after a call
- Enabling more intuitive segmentation – You can look up interactions based on customer sentiment level – “happy” customers, “uncertain” customers, “frustrated” customers, etc. This is also helpful for marketing teams to launch targeted campaigns
- Assigning agent performance scorecards – The contact centre knowledge repository also includes data on agent performance. Speech analytics evaluates each call to generate/update these scorecards
- Highlighting improvement areas – You can index and search calls using extremely targeted keywords like “upselling language.” This makes it possible to break down the most and least profitable interactions to fine-tune agent performance
- Introducing voice-based knowledge search – This is particularly helpful for field agents who may not be able to look up data on a traditional desktop interface when providing customer support
- Recommending knowledge insights in real-time – Speech analytics can listen in on a call to automatically fetch a piece of information the customer requires – e.g., fetching warranty information if the customer utters the keyword
- Using previous data to deliver predictive insights – Using ML, speech analytics can be trained to associate specific utterances with a certain action. This means your existing knowledge repository fuels future interactions, making every customer conversation more contextualised