4 min
Call centers that offer customer self-service often measure contention, which can seem like an odd tactic to users. However, this is a key measure of self-service effectiveness, as it represents the percentage of customers using these tools without being transferred to an agent.
Organizations need to focus on making customers successful in their self-service journeys by leveraging Artificial Intelligence (AI), analytics, and automation. This requires a mindset shift to empower users, which will enable businesses to optimize the customer experience (CX) and fully reap the benefits of effective self-service.
Do Customers Really Want to Solve Their Problems and/or Queries with Self-service?
The answer is a resounding yes. In today’s era of instant gratification, users expect companies to be available 24/7 through self-service channels. They are no longer as willing to wait for a contact center to open for help.
Most problem resolution journeys begin before a customer contacts the call center. Search engines and the company’s website are often the first places people look for help. In fact, 8 out of 10 consumers attempt to handle matters themselves before contacting an agent.
However, keep in mind that when it comes to simple tasks like scheduling an appointment or ordering a pizza, more than 60% of consumers prefer to use self-service instead of agent assistance. That is, to be self-sufficient when, where and how they want.
Consumers also factor self-service into decisions about whom to buy from. According to Statista, 84% of users are more willing to do business with companies that offer self-service options, and 89% of them now offer at least one self-service app.
How Do Companies Earn Customer Loyalty with Self-service?
Implementing effective self-service is a growing priority. It has been discussed within the contact center circuit for years, but now more and more companies are investing in multichannel.
But consumer demand and competitive equality aren’t the only reasons companies should implement self-service, as having multiple channels for users to resolve queries can also deliver significant business benefits. Organizations that offer self-service experience beneficial results, such as:
- Improved customer experience and satisfaction.
- Higher earnings.
- Lower service costs through lower volume assisted by agents.
- Improved agent experience (AX).
How to Make Self-service Effective Using AI, Analytics and Automation
The first key to effective self-service is helping them successfully meet their needs autonomously. When you focus on customer success, results come naturally. In this sense, the use of modern technology to design self-service solutions and improve CX is important.
Additionally, analytics can help companies avoid the trap of automating the wrong tasks because, according to McKinsey, most organizations “are not applying advanced analytics in a way that truly puts the customer first and the best tools to help them achieve their goals.”
Advanced analytics can help organizations better understand the customer journey, analyze what customers want and how they feel when they try to transact with the company, and why they contact customer service, all that can help organizations identify self-service opportunities. By automating tasks from the start, companies accelerate time to value and avoid repetitive and costly cycles of trial and error.
Thus, taking advantage of agent-assisted interactions can help companies identify the “best tasks” to perform for them, but manual analysis and the use of high-level reporting data are not enough. Such important work requires AI-powered analytics tools.
Interaction analytics software analyzes interactions across all channels and provides a wealth of insight into what customers are saying and feeling. These tools focus on common keywords to identify contact drivers at a very granular level. This improves the speed and accuracy of identifying the right self-service tasks.
Artificial Intelligence also improves the self-service tools themselves. For example, when virtual agents use AI and natural language processing (NLP), they offer more dynamic interactions than static, menu-driven bots, and can even understand the intent of what customers say they’re trying to do.
Similarly, conversational IVRs using AI and PLN allow callers to say what they want to do in everyday language. This provides a more natural customer experience and allows callers to avoid the endless pausing of poorly designed phone menus.
Self-service solutions also become more effective thanks to automation. When applied to back-end processes, it allows companies to expand the number of tasks customers complete through self-service. For example, for customers to activate a new debit card or submit a claim through self-service, there needs to be back-end processes to support those tasks. Using automation streamlines the entire process and self-service experience and also increases accuracy.
Finally, you want to design self-service solutions to make it easy and frictionless for customers to make their way to agent support. Half of customers who start their resolution journey on self-service end up with an agent, so businesses must plan and design the path of least resistance to resolution. Consumers expect omnichannel experiences, which means that when a self-service customer is transferred to an agent, the agent expects the agent to have access to the details of the conversations and interactions that took place in the previous channel.
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