By: Joshua Finley

Lihong Hicken is at the front line in rediscovering how companies collect and put customer feedback to use in this fast-evolving era of artificial intelligence. The concept of static surveys we are very much used to—a couple of questions at times amounting to interrogation—is becoming a thing of the past. Instead, this AI survey concept from Hicken looks to drive interactive and insightful conversations between businesses and their customers. 

Rethinking the AI Survey 

“A lot of people don’t know what AI service is,” Hicken shares. Traditional surveys are static, with customers ticking off checkboxes without capturing the reason behind the feedback. Hicken’s AI approach flips this on its head by engaging customers in real-time, contextual conversations that mimic human interactions. “Your product has context, and that is amazingly delightful,” Hicken adds. The AI picks up the ability to ask follow-up questions, using user response data to fuel appropriate next questions—in other words, turning feedback into richer insights. This can give businesses insight into “why people rate and comment the way they do.”

Product Success & User Engagement 

In late August, Hicken’s team launched their AI survey tool on Product Hunt, reaching up to the second top product of the day and week. The latter underlined a fast-increasing demand for new ways to get hold of customers for feedback and assurance analysis. “It is hard to get feedback these days let alone get more profound insight,” she notes. The AI Survey Tool makes it easy for any user to construct insightful feedback mechanisms without necessarily having business experience. Hicken jokingly says it can be used outside business use cases, such as gauging feedback on a dating profile.

According to Hicken, the emerging trend in the customer feedback and user experience arena is AI; people approach this from several different directions. “There are laggers who are afraid of AI, those embracing it, and those interested but unsure of how to use it best,” she says. The need for education is obvious, and Hicken urges industry leaders to step forward and share experiences with AI. “Here’s what I learned, here’s what didn’t work, and here are some tips on how to use it,” she says, discussing the actual need for knowledge sharing with transparency and pragmatism to build confidence in adopting AI solutions.

Integrating Customer Feedback and Business Growth

Hicken views AI as the inevitable future but realizes not all employees would embrace it equally. She used her AI chat survey for the demonstration, showing how the tool doesn’t merely collect feedback but can also schedule sales meetings based on identified customer pain points. This all-inclusive capability is a new opportunity for small business owners who can envision real-time customer interaction translating into revenue growth. However, Hicken emphasizes the importance of businesses understanding that their employees, too, are at different comfort levels with AI. “When there’s a new thing, it’s totally worth investing time to educate your employees on ways to use AI to make them more productive,” she advises. In other words, creating a community where employees can share their experiences—what worked, what didn’t, and the challenges faced—will accelerate AI adoption and utility.

Gathering Real-Time Feedback: Data-Driven Decisions

One of Hicken’s strongest beliefs is the need for data-driven decisions, particularly with customer feedback as the guiding force. Most companies make decisions driven by either the HiPPO—the person with an opinion who is paid the most—or a democratic vote, both of which can dilute innovative ideas. However, Hicken insists that the richest data comes from real-time customer insights. “Traditionally, this kind of data is very hard to come by,” she says, adding that most businesses have to rely on surveys taken once a quarter or even once a year. By contrast, continuous, real-time feedback allows companies to improve and grow alongside the needs of their consumers.

Common Pitfalls in Feedback Systems

Despite the numerous feedback systems available, companies often make mistakes when implementing them. “A lot of times, people don’t know how to properly get customer feedback,” Hicken notes. She identifies a common error as relying too heavily on Net Promoter Score (NPS) questions simply because they are popular rather than continuously seeking deeper customer insights. Businesses often treat customer feedback like “a pile of laundry” – something to tackle in bulk rather than continuously improving upon.

Conclusion

Hicken’s insights underline the transformative potential of AI in creating engaging and effective user experiences. Whether using real-time feedback to drive business decisions, educating employees on AI adoption, or overcoming common pitfalls in customer feedback, her approach is leveraging technology to create better outcomes for companies and their users.

For more insights on AI and customer experience, connect with Lihong Hicken on LinkedIn.

Published by: Martin De Juan