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How Much Does Persuasion Strategy Matter? LLM-Annotated Evidence from Charitable Donation Dialogues

Which persuasion strategies, if any, are associated with donation compliance? Answering this requires fine-grained strategy labels across a full corpus and statistical tests corrected for multiple comparisons. We annotate all 10,600 persuader turns in the 1,017-dialogue PersuasionForGood corpus with a taxonomy of 41 strategies in 11 categories, using three open-source large language models (Qwen3:30b, Mistral-Small-3.2, Phi-4). Strategy categories alone explain little variance in donation outcome (pseudo R-squared approximately 0.015, consistent across all three annotators). Guilt Induction is the only strategy significantly associated with lower donation rates (approximately -23 percentage points), an effect that replicates across all three models despite only moderate inter-model agreement. Reciprocity is the most robust positive correlate. Target sentiment and interest predict whether a donation occurs but show at most a weak correlation with donation amount. Logistic regression with sentiment, interest, Guilt Induction, and Reciprocity achieves nearly the same fit (pseudo R-squared = 0.080) as the full model with all strategy categories. These findings suggest that strategy identification alone is insufficient to explain persuasion effectiveness, and that guilt-based appeals may be counterproductive in prosocial settings. We release the fully annotated corpus as a public resource.