Self-service has undoubtedly been a boon in CX. The benefits are numerous. Aside from the clear increases in efficiency, 24/7 availability and consistency – it also decreases operating costs by reducing the need for human agents to deal with mundane tasks and routine queries. But, as with most technological improvements – there are pitfalls. A recent high-profile case - as reported in CX Today - saw McDonalds discontinuing its AI drive-thru ordering experiment after viral TikTok videos highlighted its failures.
How can enterprises avoid these costly and potentially embarrassing limitations, while continuing to reap the benefits self-service delivers?
1. Overcoming Usability Problems
If a self-service option is difficult or unintuitive to use, customers may abandon it and seek human interaction. That again puts pressure on human agents, adds to call waiting times and gives the customer a poor experience. Self-service platforms are often built to deal with mundane tasks or routine queries. If a customer is dealing with a more complex problem that the self-service cannot tackle, they will feel dissatisfied with the interaction. A well-tested, intuitive platform needs to be developed to avoid such issues. A thorough testing process ensures roadblocks can be identified and overcome before customers use it.
2. Improving Accessibility
Self-service options that have poor accessibility are frustrating and discriminatory. Given that not all customers have the same digital access, self-service options at their heart may be inaccessible. Providing a platform that works across a range of devices, browsers and for customers of varied literacy is a basic must-have.
3. Deepening Support for Complex Issues
Self-service platforms like FAQs and Chatbots are largely effective for dealing with routine queries but are not always equipped to deal with more complex problems. If a customer is stuck in an automated system that does not understand a nuanced query, they will become frustrated and – again - possibly abandon the service.
Generative AI is the key to unlocking smoother, more meaningful interactions. It generates data from interactions, identifies patterns and uses its data to deliver more efficient customer interactions. This saves costs in the contact center – as fewer human agents are needed – and ensures a more satisfactory customer experience.
Local Measure's pre-built contact center platform, Engage, is an example of the power of generative AI in action. It is built on AWS and is infused with Generative AI from Amazon Bedrock. Engage offers advanced features including automatic message drafting and form filling, next-best-action recommendations, chatbots, skills-based routing, and real-time translation. Engage supports voice, and messaging via email, SMS, Facebook Messenger, WhatsApp, LINE, and direct messaging on Instagram – ensuring asynchronous, always-on availability for customers.