The key to ensuring customer satisfaction is a digital-first contact center strategy with systematic escalation to managers for handling the challenging requests and agents for human connection.
Every contact center team aims to respond to consumer requests as fast and effectively as possible. To do that, teams occasionally move the customer journey through digital channels, or requests are escalated to management or specialized contact center agents for more help. But determining the best course of action in a special circumstance is not always easy.
For customers, spending too much time on digital channels that do not address their concerns can feel ineffective or impersonal. However, sending customers to agents or management for simple issues that automation can handle can waste valuable time that could be used on more complicated instances.
The goal should be to develop a contact center customer journey that is digital-first and places agents where there are opportunities or gaps to foster more personal connections and utilize an agent’s highly developed skill set.
Here are some contact center data components and how each affects customer satisfaction:
Contact Centers Inundated with Data
Due to the high volume of calls, contact centers have access to crucial data, including the time a customer called, how frequently they called, why they called, and more. Each of these data points describes a customer’s journey in search of assistance or support, enabling businesses to monitor the situation and decide how to respond to requests most effectively.
Although monitoring the customer journey and responding accordingly have become fundamental requirements because of modern technological breakthroughs, businesses must take their strategy to the next level. A more sophisticated approach uses Machine Learning to anticipate the customer’s future needs to reach a successful outcome or the highest degree of satisfaction and then proactively and automatically initiate agent involvement. Machine Learning models provide a high level of confidence in predicting whether something will go wrong or a customer may want to speak to an agent due to the large volume of call data that has been collected.
Data Helps Forecast Customer Satisfaction
There is a wide variety of data inputs that are fed into Machine Learning models. Helpful data components can include comments or case notes in the CRM system. In addition to removing words and word clusters from these notes, sophisticated Machine Learning models can also detect the sentiment, inflection, and tone of customer voice recordings.
But out of all the data points, the time component might have the biggest impact on how a customer journey turns out. Most customers find that extended holds and wait times are the most aggravating aspects of a service experience. Businesses can leverage Machine Learning to estimate how long it will take to complete a customer’s request rather than waiting for that time to elapse.
Additionally, by facilitating greater consumer access to self-service assistance, digital communication channels can streamline processes and increase efficiency, including mobile applications, online web portals, and on-demand apps. Customers can essentially skip the line by using these channels.
Moving Customer Requests to Agents
Digital communication channels can handle straightforward and easy requests, but more challenging requests need agent assistance. Agents can be informed that certain requests require a higher level of visibility when a Machine Learning model identifies input variables that are probably indicators of a poor outcome.
It’s also crucial to remember that while some customer requests may necessitate the assistance of an agent since they are complex issues, others are only situational. This is why it’s crucial to have a variety of communication channels available. When possible, it is crucial to direct customers to a digital channel, but if they need human assistance, they shouldn’t be forced to stay there. It all comes down to striking a balance between effective digital channels and human connection.
Raising Customer Requests to the Management
Although agents are often thought of as the first line of intervention, there can be instances where they have used every resource at their disposal and need management involvement. Additionally, management escalation can raise the visibility of more challenging requests within the company. The executive team can assess these requests and aggregate data logged into the CRM throughout the escalation process to assess issues and opportunities and for business process improvements.
Building Contact Center Journeys for Better Customer Satisfaction
Every company must focus on giving customers prompt, helpful support. There are time-bound milestones that a consumer must meet at each stage of the contact center customer journey to ensure a good outcome. Businesses will be one step closer to satisfying customers and fostering loyalty if they use data to predict those inflection points and take proactive action on them.
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