AI can analyze thousands of customer feedback comments in a matter of seconds. But for a company, simply obtaining a result is not enough. When AI identifies a pain point, an emotion, or a trend, teams need to understand why.
That is the whole purpose of explainable and traceable AI analytics: enabling users to understand the results produced and trace them back to the data that generated them.
An Analysis Is Only Valuable If It Can Be Understood
Imagine that an automated analysis reveals a significant increase in customer feedback related to a delivery issue. Before taking action, a team needs to be able to verify this finding: Which feedback is concerned? What expressions were identified? In what context does the issue arise? Why were these comments associated with this particular category?
Without this information, an insight can be difficult to challenge and put into context.
viavoo’s proprietary AI explainability makes it possible to maintain a clear link between an analytical result and the elements that led to that result. Teams can therefore better understand the analysis, verify it, and use it with greater confidence.
From Insight to Customer Feedback
Traceability can be summarized simply:
Insight → analysis → textual elements → source feedback.
This capability makes it possible to trace results back to the original data, verify a finding, and understand what customers are actually expressing. This is particularly important when analysis is used to inform product, CX, or strategic decisions.
At viavoo, proprietary AI analytics is designed to be both explainable and traceable, giving teams visibility into the results generated by automated analysis.
AI That Adapts to Business Needs
Not all companies face the same challenges. A retailer may want to monitor delivery-related pain points, while a telecom operator may be more interested in network issues or reasons for customer churn.
Analysis therefore needs to adapt to the specific challenges of each organization. Customizing AI analytics makes it possible to build analyses that are relevant to each business, while maintaining the ability to understand and verify the results.
This transparency becomes even more important when customer feedback is analyzed across multiple dimensions. A single piece of feedback, for example, may be associated with a topic, an emotion, a pain point, and a stage of the customer journey. Teams need to be able to understand these different classifications and ensure that they accurately reflect what the customer actually expressed.
AI Does Not Replace Human Judgment
Explainability is above all about creating an effective complementarity between AI and human teams.
AI can analyze the entire dataset and uncover emerging trends. People can then verify the results, put them into the context of the business, and decide what actions to take.
AI detects. Humans interpret. Businesses act.
This approach makes it possible to benefit from the power of automation without giving up control over the analysis.
Trust AI Without Giving Up Control
The value of AI analytics does not lie solely in its ability to process large volumes of data. It must also enable teams to understand what was analyzed, how it was analyzed, and why.
With explainable and traceable proprietary AI, automated analysis becomes a genuine decision-support tool rather than a black box.
👉 Want to discover how viavoo can turn AI analytics into a genuine decision-support tool? Fill out our contact form to speak with our experts.