Improving Customer Interactions
We‘ve seen the rise of omnichannel, sentiment and artificial intelligence (AI) everywhere; vendors have thrown their weight behind these concepts — pushing them front and centre in their product offerings. However, many contact centres still measure performance with traditional quantitive metrics. This way of thinking overlooks that we have moved to new and more agile ways to work. You need an “in the moment” understanding of customers’ perceptions of their experiences throughout the entire engagement.
Volatility, Uncertainty, Complexity and Ambiguity (VUCA) is used in many different industries and can also be used to describe how customers and their interactions have evolved — and continue to do so. Deploying innovative ways to engage customers is important for offering the bespoke and personalised experiences customers expect.
By combining the ever-increasing number of data sources relevant to the customers journey and ensuring it provides an appropriate level of insight, organisations can make accurate decisions on how to improve the experience as perceived by their customer. An approach overly focused on traditional operational measures could run the risk of reducing the ability to identify and anticipate the need to radically alter course “in the moment.”
Continual feedback loops, such as Net Promoter Score (NPS) and customer satisfaction (CSAT) are very important for the purpose of hearing the voice of the customer. However, these metrics are based on the overall perception at the end of the current engagement. Today, many contact centers continue to focus primarily on choices made within the IVR system — directing a call through a predefined process that’s only measured for efficiency. This creates a gap between the start of the engagement and the end.
As perception changes with each new individual experience, a customer’s perception on what is good or bad, will most certainly change. Therefore, customer engagement must become more dynamic. Generating more data throughout the engagement process will provide additional insights that can validate improvement initiatives.
Our current traditional operational focus misses this dynamic element, as the process is no longer linear and predefined. It becomes dynamic and, therefore, is continually changing. Efficiency and effectiveness are no longer enough; relevance needs to be added into the equation. This will allow you to visualize the entire journey — operationally, organizationally and from the customers perception.
Fine-Tune with Predictive Routing
Machine learning automates consistent parts of the process — and that enables the routing to become predictive. This ensures decisions are continually fine-tuned to improve the customer experience.
Integrating disparate systems lets you mix emerging technologies to gain insights quickly. As such, today’s leaders want continual innovation that meets today’s rapidly shifting business demands and increases business agility.
Developing such capability within your organisation ensures business agility while developing an ongoing future-proof platform. Using data analytics tools to provide actionable insights for both real-
time and historical data lets the user analyse the customer journey — and measure the experience in greater detail. This creates successful outcomes within digitally mature organizations.
Increase Agility and Visualise the End-to-End Value Stream
Using emerging technologies like sentiment analysis and predictive routing throughout the customer journey gives you a deeper understanding of the customer with a more bespoke and personalised journey. You do not have to wait for NPS or CSAT scores that are usually provided after the fact. In the end, these steps will empower you to better serve customers and gain complete visibility for intelligent decision-making.
