As Google correctly pointed out, customer demographic data isn’t always enough to tell you the full picture. The company’s research shows that 40% of all buyers of baby products live in households without children. 68% of personal care influencers were men, while 45% of people searching for home improvement tools/ideas were women. These insights contradict our common inferences from demographic data, indicating the need to look deeper.
That’s where customer intent comes in.
What is Customer Intent and Why it is Important for a Contact Centre?
Customer intent can be defined as the root cause or motivation behind a specific aspect of customer behaviour, beyond what is evident from demographic data analysis, direct customer requests, and documented feedback. Given the proliferation of products and services online, it is inevitable that customer drivers will evolve as well.
Today, we bring a wide range of expectations and motivations to our online activity, just as we do in real life. Customer intent analysis tries to break down these behavioural patterns and signals to answer one key question: what made the user click?
In the context of a contact centre, knowledge of customer intent could dramatically improve your service capabilities. Agents will spend less time beating around the bush, as it were, and tackle the root cause of the issue whether or not it was explicitly mentioned by the customer. For example, if a customer has purchased several non-satisfying products from an e-commerce store and finally calls the store to complain about what is seemingly a minor defect, customer intent will surface the root cause of their emotion.
The principle of analysing underlying intent applies to every step of the customer journey, right from a person’s interest in your product to their service expectations.
How to Leverage Customer Intent to Build a Better Contact Centre
The ability to understand intent can exponentially improve contact centre operations. To begin with, you can predict intent based on past purchase and interaction records, thereby matching an inbound caller with the right agent. It also reduces the amount of effort the customer must put into explaining their doubts and queries to the agent. This helps you solve queries faster, and reach FCR.
Further, you can leverage customer intent to drive upselling and cross-selling. For example, if you know that a frequent buyer of baby products lives in a household without a child, you might be able to gauge their needs better and generate interest around products for gifting, etc.
Finally, customer intent analysis is extremely useful for forecasting your staffing requirements. Intent patterns can suggest the peak periods when customers are most likely to face a sense of urgency, frustration, interest, or any other kind of emotional impulse, and how you should staff your contact centres to avoid customer frustration while maximising opportunities.
What Do You Need for Customer Intent Analysis in a Contact Centre?
Look for AI/ML-enabled CX analytics technologies, particularly those focused on behavioural profiling. You could also leverage sentiment analytics to identify hidden intent irregular customer communication.