The Question: How Do People Actually Feel About AirPods Pro?
Instead of describing what Sentyment's Market Intelligence module does in the abstract, it's more useful to just show a real run. We pointed it at "airpods pro", pulling recent comments from Reddit and YouTube, and let it classify sentiment, emotion, and the specific quotes behind each score. This is the exact query shown live on the Sentyment homepage; here's the full breakdown of what came back.
The Headline Number
A net score alone is a headline, not an insight. The useful part is what is actually driving each bucket, which is where the comment-level evidence comes in.
The Comments Behind the Score
Four representative comments pulled directly from the sample, classified individually:
- "Noise cancelling is genuinely unreal, worth every penny." (r/headphones, ↑1.2k, Positive)
- "Switching between my devices is seamless now." (r/ios, ↑612, Positive)
- "Setup was fine, nothing special but it works." (r/apple, ↑340, Neutral)
- "Mine started crackling after 3 months, disappointed." (r/AirPods, ↑880, Negative)
This is the part a raw percentage cannot give you: the noise cancelling and cross-device switching experience are the two threads driving the positive share, while a recurring "crackling after a few months" complaint is the specific, actionable signal behind the negative 15%: not vague dissatisfaction, but a concrete quality issue worth tracking.
Beyond Positive/Negative: The Emotion Layer
Sentyment classifies emotion, not just polarity, across five buckets. For this query, on a 250-comment sample:
- Joy: 34%
- Trust: 27%
- Neutral: 24%
- Concern: 9%
- Anger: 6%
The net read: this conversation leans joy. Trust (comments about reliability and consistency) outweighs concern by a wide margin, and anger, the emotion most associated with a real reputational problem, sits at just 6%. That distinction matters: a product can have real, specific complaints (the crackling issue above) without the overall conversation reading as angry or hostile.
What This Took
- Query: one URL/keyword, no manual scraping or spreadsheet work
- Turnaround: under 10 seconds for the full 250-comment pull and classification
- Cost: 1 credit on the Free plan for a Reddit or YouTube query
- Output: net score, emotion spread, and cited comments, exportable as CSV
Why Show the Raw Output
Most product pages describe what a tool does. It's more convincing to just show what comes back from a real query, including the parts that are mildly inconvenient, like a real, specific hardware complaint sitting inside an otherwise positive conversation. That's the point: evidence-backed sentiment doesn't round off toward a clean story, it shows you the actual texture of the conversation.
Run Your Own
This exact workflow is available on the Free plan: 20 credits a month, no card required. Point it at your own brand, a competitor, or a product launch and see the same breakdown: net score, emotion spread, and the comments behind it.