What sentiment analysis can't see: Measuring whether customers were helped, and what went wrong, across 70,000 support conversations

arXiv:2606.19698v1 Announce Type: new Abstract: Most companies read their customer support data at scale using sentiment analysis, which measures how customers sound rather than whether they were satisfied with the result. We tested a richer alternative on 70,450 support conversations from a leading online fundraising platform: alongside tone, we used GPT-5.4 to estimate each customer's satisfaction and to flag whether they reported a concrete problem, then validated all three readings against the 1-to-5 ratings customers left on the conversations they rated. The satisfaction estimate tracked

Source: arXiv cs.CL — read the full report at the original publisher.

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