Support is one thing. Proactive support is another. Take a look at the scenario.
Imagine it’s the launch of a major product from a thriving software company, and the product, a cutting-edge tech software, has gained significant interest in the industry. As the launch date approaches, the company suddenly experiences an overwhelming surge in customer inquiries, mostly about technical specifications. While this scenario can be challenging, an organisation with proactive support would have anticipated this, and put in place the systems needed to ensure that the scenario does not result in an evident state of overwhelming.
To achieve such support, the company would have had to employ various means to identify potential pain points and common queries likely to arise during the launch period. This can be described as a state of proactive support, as teams are positioned ahead to ensure future problems are easily resolved as soon as they are encountered.
This proactive approach not only ensures customers receive immediate answers to their inquiries, but also alleviates the stress bound to arise from support tickets, ensuring a more satisfactory experience during product use.
Simply put, proactive support in customer service revolves around the process of anticipating customer needs and issues before they arise. The entire aim is to enhance the overall customer experience, by providing the solutions to customer’s problems even before they happen. Unlike reactive support models whereby solutions to customer problems are worked upon as they occur, proactive support takes a preemptive approach to avoiding dissatisfaction experienced during wait periods. This is achieved through the use of data analytics tools, research, and AI technology. The utilisation of AI tools can help businesses identify potential pain points, common questions, and issues that customers might encounter during use.
In customer service, proactive support serves as a healthy soil for project incubation. Statistically, users are 71% more likely to stick with the service providers they believe are constantly working on improving their services, than those who they feel are “comfortable” in their current position. This is obvious in the digital software market where software users are 100% confident in proactive management. This makes it very important for companies seeking the advantage of user trust, by creating proactive support systems that cater to their audience needs.
Creating a proactive support strategy is the first step to take when aiming to create a proactive service system for an organisation. Through meticulous planning and structuring, businesses can outline processes, i.e stages to follow, and tools to use, to provide their user audience with proactive support services. These include;
Monitoring Tools
Monitoring tools are implemented to track product performance, user interaction pattern, and other necessary areas of the product/service operations. These tools, such as Splunk, DataDog, Nagios, etc, are used in various aspects to monitor product performance, record user feedback, and process other data elements to produce suggestive results from noticed characteristics.
Data Analytic Tools
Data analytic tools are used to study obtained data to identify patterns, trends, and anomalies in user experience. The use of analytic tools like Apache, Microsoft tools, Google Data studio, etc, enables businesses to process and create suggestions used to proffer preemptive problem resolution. These tools save businesses from unforeseen risks, mitigating possible damage, and offering insights for informed decision making.
Predictive Analysis
To achieve a proactive support system, businesses utilise predictive analysis models to forecast potential issues based on historical data. Similar to data analytic tools, predictive analysis studies user data to predict possible complaints. The use of predictive analysis reduces the likelihood of future disruptions, giving support teams a heads up on what users may complain about, and guidance on how to resolve these issues.
Customer Feedback Loops
Customer feedback loops are mechanisms established for the collecting and analysis of customer feedback. These loops are created to automate the process of collecting feedback, as well as the process of identifying areas for improvement to address concerns before they escalate.
Development of FAQs & Knowledge Base
Since proactive support is about finding solutions to problems before they arise, FAQ and Knowledge base sections are very important for achieving this. When support teams find these possible loopholes, creating content to serve as guides for users when they experience the issues is the easiest way to overcome the burden of repetitive requests and support demands. Comprehensive FAQs and knowledge bases not only empowers users with solutions, but also reduces the burden support teams have to bear.
The combination of these tools and practices help organisations identify, anticipate, and create solutions to address issues before users encounter them, improving their support system from a reactive one, to a proactive one.
Summarily, proactive support has gone beyond a “should have” to a “must have” for businesses. The era of reactive support services no longer meets with the standard of our world today, and has become obsolete. Proactive support systems now help businesses thrive in terms of customer satisfaction, operational effectiveness, and user satisfaction. For businesses, it also presents benefits such as reduced overhead cost, advanced operational standards, and staff who are abreast with latest technologies to propel the business into the future. All of these, sum up to show the benefits of proactive support services over reactive support services, and why businesses need to evolve with the demands of modern time.
