Guest Blog by Krishna Raj Raja, Founder and CEO, SupportLogic
Do you hate taking customer surveys after you buy something or had a service request? Whether you’re buying clothing, airline tickets, a car, a laptop, or shopping for a mortgage, you’ve probably been asked to take an e-mail survey shortly after your purchase was completed. Afterward, did you think about how honest you were? According to Customer Thermometer, 70% of people say they’ve abandoned a survey before finishing and only 9% answered thoughtfully. If only 9% of your customers are answering your survey thoughtfully, the data you are receiving isn’t the most accurate and representative of your customer satisfaction.
Companies are constantly looking for data to measure their customer service experience, but customers get so many surveys now that our email inboxes are getting overwhelmed, and many people have simply had enough. There’s even a term for it — “survey fatigue.” And this fatigue is having negative effects.
In addition, there are fundamental challenges common to most – if not all – survey metrics, including:
Repeated survey requests and follow-ups might even make a (currently) happy customer turn unhappy, with the solicitations becoming an annoyance and sometimes viewed as an invasion of privacy. Unhappy customers usually end up costing companies more money than the customer spent if they have a poor experience. It makes you wonder if customer surveys are still effective and if they should be abandoned altogether. However, what would be a better alternative?
Analysing your customer signals using Artificial Intelligence (AI) might be the answer to survey fatigue. AI can now detect how customers react and feel during the service interaction at the moment, without the extra step of taking a survey later. AI saves time, gathers more authentic feedback, and makes service teams more effective at proactively addressing customer issues. Having the raw unbiased data from each customer interaction is a better gauge of how your company’s customer service department is actually doing. It helps save an organization time and keep its customers happy.
For chats and email-based service requests, AI can scan and detect keywords that map to certain feelings or issues – sensing anger or frustration, as well as satisfaction or gratitude. Phone calls with service and support representatives can be converted to text and detected in the same manner. The keywords are then tracked and analysed and can be used to develop customer satisfaction scores and reporting that deliver useful customer information that executives, service teams, and service agents can all use and take action on.
If the above process can eliminate post-sales customer surveys, this could lead to fewer emails and happier customers, which should really be the goal at the end of the day. And, as noted earlier, if only 9% of people are answering surveys in a truthful manner anyway, they are not accurate, and this information will not truly help a service team improve over time. In addition, this customer signal-based AI can also help to improve service representative performance in real-time while they are helping a customer, which can help get more service requests resolved on the first interaction, which also leads to happier customers.
In all, it’s time to leave surveys behind and move on to something better, and AI has found a way to make this shift happen. By embracing AI to improve the customer service experience, we can make life better for customers, companies, and service representatives, so everybody wins.
Krishna Raj Raja is the founder and CEO of SupportLogic.