Not too long ago, when businesses wanted to understand how customers felt about a product, service, or experience, they would have to conduct time- and resource-intensive customer research (surveys, focus groups, etc.) or tediously scour online reviews, forums, social channels, or support logs to capture voice-of-customer (VoC) feedback. Researchers and analysts would then painstakingly analyze and interpret the feedback to recommend improvements (which might or might not get implemented).
It was a similar tedious, time-intensive approach for voice-of-employee (VoE) feedback.
But AI has fundamentally changed all that.
What is VoC (and VoE) Feedback Management?
Voice of the Customer (VoC) feedback management refers to collecting and analyzing customer feedback to understand their experiences, expectations, perceptions, and pain points. Then, using it to make improvements to products, services, and experiences.
Voice of the Employee (VoE) feedback management is all about gathering, understanding, and acting on employee feedback to improve employee engagement and experiences.
The Business Value of VoC and VoE Feedback Management
VoC and VoE feedback management provide a deep, comprehensive view of a company's performance from two critical perspectives—the customer and the employee.
VoC programs provide businesses with numerous actionable insights for improved customer satisfaction and retention. Companies can address customer pain points, leading to increased loyalty, repeat business, and positive word-of-mouth referrals. These outcomes not only help secure a larger market share but also contribute to sustained revenue growth.
On the other hand, VoE initiatives help create an engaged and motivated workforce. Employees who feel heard by management are more likely to be productive, committed, and less prone to turnover, reducing the costs associated with hiring and training new staff. Moreover, a positive and inclusive work environment can enhance a company's reputation as an employer of choice, attracting top-tier talent.
VoC and VoE Feedback Management Frameworks, Processes, and Tools
VoC and VoE feedback management follow a cyclical framework consisting of three main steps:
Listen by collecting feedback across various channels and listening posts.
Analyze and interpret the collected feedback to produce actionable insights.
Act on the insights by resolving issues, implementing improvements, or completely redesigning products, services, or experiences.
VoC and VoE feedback management processes are carried out in two main loops:
The inner loop addresses individual feedback items, ensuring that concerns are promptly addressed at the front line.
The outer loop involves analyzing feedback at a macro level, identifying trends, and fixing recurring issues or implementing systemic improvements.
Various VoC and VoE feedback management platforms and tools exist to facilitate these processes. For instance:
InMoment
Medallia
Qualtrics
Question Pro
Survey Monkey
Survey2Connect
Verint
These tools offer robust capabilities for capturing and analyzing customer and employee feedback across multiple channels, displaying metrics and insights in dashboards, and distributing insights and assignments to team members to carry out inner loop and outer loop processes.
The challenge? Although these tools make it much easier for businesses and teams to regularly and consistently capture and centrally manage VoC and VoE feedback, the process of analyzing and interpreting feedback is still time- and resource-intensive, making reviewing and responding to feedback through inner loop and outer loop processes slow and costly.
How AI Impacts VoC and VoE Feedback Management
The AI revolution of 2023 is significantly impacting VoC and VoE Listen, Analyze, Act, and inner/outer loop processes.
Interpretive AI
Interpretive AI is specifically designed to understand and interpret complex data sets. It sifts through millions of data points, identifying patterns, trends, and meaningful insights. Interpretive AI for VoC and VoE feedback management can quickly analyze and make sense of both structured data as well as unstructured data, including open-ended survey responses, social media posts, and audio recordings from customer support calls.
As a result, businesses that embrace interpretive AI for feedback analysis will see dramatic time and cost savings. Teams will not only get actionable insights much faster, but they will also have more time to respond to customers, resolve issues, fix problems, and enhance products, services, and experiences.
Generative AI
Generative AI learns from large data sets to generate new outputs. Based on natural language requests or prompts, generative AI can produce diverse and creative content, including text, images, music, and even entire realistic scenarios. When combined with interpretive AI, generative AI can recommend customized solutions and improvements based on the analyzed VoC and VoE feedback.
By leveraging the insights provided by interpretive AI, generative AI can suggest innovative ideas, tailored responses, or product enhancements to address specific needs and pain points. This combination of AI capabilities empowers businesses to not only understand sentiments and preferences but also take proactive steps towards refining their offerings and optimizing products, services, and experiences.
Future Outlook
As AI continues to evolve, so too will its impact on VoC and VoE feedback management. The future promises even more advancements, with AI algorithms becoming increasingly sophisticated in understanding human emotions, sentiment, and context. Imagine a world where businesses can proactively predict and respond to customer and employee needs and preferences, preemptively addressing potential issues before they arise.
Conclusion
AI has ushered in a transformative era for VoC and VoE feedback management. Gone are the days of tedious and time-consuming manual analysis of customer and employee feedback. Today, businesses can leverage the power of interpretive AI and generative AI to revolutionize the way they understand, analyze, and act on feedback.
As we look ahead to a future where AI continues to evolve, businesses must embrace this change and opportunity. Adopting AI-driven feedback analysis and action will give them a competitive advantage as they forge deeper connections with customers and employees and drive sustained growth and success.
About the Author
Daniel Roundy is Chief Experience Officer at nxtting, a strategic design and innovation firm. Daniel is a transformation leader focused on value creation through human-centered, technology-enabled customer and employee experiences. He loves applying empathy, data and insights, and innovative technology to solve gnarly problems for (and with) people and businesses.