Capturing customer intent is a crucial part of ensuring companies know how to effectively serve their target audience. Unfortunately, the methods used for capturing and understanding intent in the past haven’t always been particularly effective. Traditionally, contact centres would capture intent either by asking agents to input “call disposition codes” into the CRM system or by tracking IVR inputs.
Both of these methodologies have their issues. The disposition method, for instance, suffers significantly from potential for human error. When rushing to deal with high numbers of calls, agents can often fail to enter codes accurately, and often choose the option closest to the top of the list to save time. In other instances, agents may not receive the right coaching to understand what each disposition means and why they are important – meaning the importance of getting it right isn’t front of mind. This leads to an inaccurate analysis of intent.
Disposition codes also frequently need to be reviewed and updated, using lengthy analysis strategies, as emerging forms of intent continue to arise in the contact centre.
When collecting data from IVR inputs, similar problems persist. For example, customers don’t always input the correct information into a system. They can make mistakes or push buttons at random in an attempt to reach an agent as quickly as possible. As well as this, using this as your data for decision making means basing it on the options that the organisation has made available – and that is a limited number.
Fortunately, developments in AI and automation have led to the creation of more effective ways to capture customer intent in the modern contact centre.
Why Capture Customer Intent in the First Place?
The difficulties associated with capturing and using customer intent may leave some companies wondering why they should invest in this strategy at all. However, learning from customer intent offers a host of crucial benefits for brands.
Understanding the most common demand drivers in a contact centre is crucial to improving business efficiency and service experiences. When companies dive into the intent behind a customer’s calls, they can gain a better understanding of what customers are actually calling for.
This makes it easier to determine how to address customer needs and requests through automation, and process changes. Companies can split CX KPIs across demand drivers to highlight new opportunities for improving customer service and eliminate broken processes.
For instance, a contact centre may discover customers are constantly making multiple calls to ask about the setup of a new device. Implementing new tools to assist customers with this initial process can reduce the number of technical calls agents need to handle.
With customer intent to guide the business, contact centres can measure the results of their targeted improvements. Monitoring how intent evolves and changes over time allows business leaders to determine whether process changes have effectively eliminated common problems or contributed to a better customer journey.
Capturing intent accurately, before the conversation also helps companies improve their routing strategies. When a business can automatically detect the intent behind a call, they can use AI and automation technology to ensure customers are directed to the right agent to handle their call. This improves the chances of a high first-time resolution rate, reduces handling times, and boosts customer satisfaction by minimising the need for multiple transfers.
How Can Contact Centres Capture Intent?
Using AI and automation techniques provides contact centres with a more streamlined and efficient way of capturing and understanding intent. Prominent CCaaS vendor Sabio Group runs “intent capture and analysis” programs on a recurring eight-week basis with its clients to expand their understanding of customers.
During these analytical events, Sabio diverts a portion of its customers to a voicebot which automatically asks open call-steering questions about why the consumer is calling. The AI system then collects the verbatim reason for the interaction from each customer to offer a clearer insight into the various reasons behind a call, which is impossible to do in a typical IVR system.