August 3, 2022
August 3, 2022
It doesn’t matter what industry you’re in: whether you work in retail, hospitality, banking, or any other industry selling products or services, you know how important it is to gather your customers’ feedback.
Bad customer experience costs companies a lot of money—a study estimated that U.S. companies typically lose $75 billion a year due to poor customer experiences. Therefore, feedback plays an important role.
According to a Microsoft report, almost 4 in 5 consumers (77%) have a more favorable view of brands that ask for and accept customer feedback. In other words, not only customer feedback allows your company to be aware of the Voice of the Customer and make the necessary changes, but it also fosters a positive brand reputation among consumers.
In this article, we’ll go over the most common ways to collect customer feedback and we’ll explore Voice AI as the most innovative, efficient and cost-effective solution for feedback collection.
As you can see in the table above, we’re considering three key factors when analyzing feedback collection methods: response rate, qualitative results (through open-ended questions), scalable and cost-effective.
Depending on the scope of the survey, there are many different types of feedback a company can seek out, from a very basic 0-10 customer satisfaction (CSAT) survey to a more in-depth, qualitative questionnaire.
Here are the most common feedback collection methods:
It’s frequent for companies to collect feedback by sending an email or a text message, which usually includes a link to a customer satisfaction survey.
Depending on the type of purchase or service, the timing of these requests may vary. For smaller services, like a food delivery, the request should come right after the service takes place. Instead, for a larger purchase—like a piece of furniture or a kitchen appliance—the company may request the feedback a couple of months after the transaction.
This type of survey is not only quantitative, as it often allows customers to leave their comments and express their feedback in their own words.
The drawbacks: Email and text surveys are notably unpopular among consumers, with low click-through rates. If many customers don’t even open the email, fewer will click on the link, and even fewer will complete the survey. According to MailChimp, the average click-through rate in emails across most industries is only 2.62%.
The purpose of feedback collection is to listen to the voice of the customer and make the appropriate changes to the service and product when needed; but if the feedback you collect is so small in volume, you are likely to base your business decisions on an irrelevant data sample.
For mobility services like Uber and food delivery services, it’s easy to request feedback directly from the same mobile application through which users have requested the service itself. As soon as the service is complete, the app can notify the user asking to submit their feedback, which is usually as simple as a 1-5 star rating.
This method, when applicable, ensures a very high response rate. It’s easy and user-friendly, and most customers will be excited to provide their feedback through the app.
The drawbacks: In order to make the feedback collection user-friendly and avoid consuming the user’s time, the feedback collected through mobile apps is usually very simple. A star rating may be a good indicator of the overall customer satisfaction, but it won’t inform the company of the quality of the customer experience on a deeper level.
Many companies use the traditional IVR system to request feedback from customers, either through an outbound call or at the end of an interaction with an agent. A common use of IVR is for a company to automate outbound calls after performing a service, like repairing your car.
IVR is not expensive and easily scalable, but due to its limited technological capabilities, the type of feedback it’s able to collect is very narrow.
For example, an IVR system might ask: “Was your issue or concern resolved? For Yes, press 1, for No, press 2.” Or: “How likely are you to recommend our service to others, from a scale to 1 to 5, 1 being not likely at all, and 5 being very likely?”
The drawbacks: IVR only registers responses as digits, giving you quantitative feedback and not enabling you to get a more complete and complex picture of the customer experience.
Let’s say 34% of your respondents are unhappy with your service and express it in their satisfaction survey; if you don’t know why they are unhappy, there is very little you can do to improve your score.
Sometimes, a company will employ a number of agents to reach out to customers on the phone and gather their feedback on products and services. This is one of the most in-depth methods for feedback collection, as customers are more likely to engage with the agent and provide detailed feedback about their customer experience.
This type of feedback is more qualitative than quantitative, allowing for more nuance and personalization. Whenever you let your consumers express themselves freely, you get richer insights. Open-ended questions are therefore very helpful.
The drawbacks: While phone interviews may lead to excellent results, they are expensive, time consuming, and not scalable. You can set up an IVR to call as many customers as you need, but you can’t employ an infinite number of agents to manually call every customer and request in-depth feedback. Therefore, this method is the least practical to implement.
Even Stanford University says it: Speaking is three times faster than typing. Therefore, implementing an intelligent Digital Voice Agent powered by AI to connect with customers over the phone and gather their feedback in a short and friendly conversation is a winning strategy for product and service companies.
Let’s say you want to set up feedback collection outbound calls with Voice AI for a food delivery service. You can easily automate the Voice AI platform to initiate outbound calls to customers about one hour and half after the food has been delivered. The Digital Voice Agent will proceed to ask a couple of questions to the customer; for example, “How was your food?”, “Are you satisfied with our service?”
Another example would be feedback collection after a prospective customer does a test drive at a car dealership. After the customer leaves the dealership, the Digital Voice Agent will reach out and ask: “How was your test ride?”, “What was missing?”
One more example. Many companies selling consumer durables like kitchen appliances, whenever repairs are needed, send technicians from third-party companies. With Voice AI, they can collect feedback on the third-party company to ensure that it has met the needs of the customer.
Thanks to the qualitative and versatile nature of the questions Voice AI can ask, the feedback the company will get is likely to be different for each customer, focusing on different topics and issues. This will allow the company to get a much wider picture of the customer experience.
Let’s take it one step further. Not only Voice AI is an excellent solution to gather the feedback, but it’s also an ideal tool to analyze the feedback.
Voice AI solutions like Skit’s Augmented Voice Intelligence Platform can easily aggregate the data and help you identify insights and takeaways that will ultimately lead to data-driven decision-making.
This is the direction the customer experience industry at large is moving towards:
If you want to learn more about Skit.ai’s Augmented Voice Intelligence platform and speak to one of our experts, you can book a demo using the chat tool below.
In a debt collection industry ripe for innovation, the introduction of Conversational AI is revolutionizing the agencies’ recovery processes as well as consumer experiences. For debt collection agency leaders looking to streamline and accelerate their collections, transitioning to an omnichannel, AI-powered platform undoubtedly marks a significant shift. In this blog post, we are focusing on […]
In the high-stakes world of commercial (B2B) debt collections, where high call volumes and rising staffing costs are common challenges, the integration of AI-powered technology can be a game-changer for collection agencies. Here’s where Conversational AI—in the forms of omnichannel automation, including voice, email, and text—can transform a business’ recovery prospects. This technology can enhance […]