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Consumer Voice Analyst: Decoding Sentiment at Scale
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September 15, 2025 5 min read Client: Retail Brand

Consumer Voice Analyst: Decoding Sentiment at Scale

Retail NLP

A multinational retail brand was sitting on a goldmine of data they couldn't read: 200,000+ open-ended survey responses per quarter. They knew what their NPS score was, but they didn't know why.

Beyond Keyword Counting

Traditional word clouds showed them that "delivery" was a frequent keyword. But was it because delivery was fast? Slow? Expensive? Or damaged? The context was lost.

We deployed the Consumer Voice Analyst, an agent capable of semantic coding. It doesn't just match keywords; it reads for intent and emotion.

The Semantic Clustering Engine

The agent grouped feedback into actionable clusters even when customers used different vocabulary. "Shipping took forever" and "My package was delayed" were correctly grouped under Logistics Latency, while "The box was crushed" went to Packaging Integrity.

Cluster A: "Eco-Friendly"

Customers praising sustainable packaging.
+15% Sentiment

Cluster B: "Size Fit"

Customers complaining about inconsistent sizing.
-22% Sentiment

Strategic Impact

The brand used this intelligence to launch a "True Fit" guarantee campaign, directly addressing the sizing concern identified by the agent. This single initiative reduced returns by 18% in the following quarter. The agent continues to run 24/7, providing a real-time pulse on brand perception.

What are your customers actually saying?

Stop guessing. Start decoding. Our sentiment agents reveal the hidden drivers of customer behavior.

Launch Sentiment Demo