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Measuring influence beyond likes: the performance of the “Paris é Brasa” case study in numbers and sentiment
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This dissertation aims to propose an outcome analysis framework for influencer marketing campaigns by combining sentiment analysis with traditional metrics and social media analytics. Anchored in the “Paris é Brasa” campaign, the study offers a multidimensional approach to evaluating campaign effectiveness beyond surface-level metrics.
The case study encompasses data from 8 brands, 20 influencers, and 148 Instagram posts, enriched with planning documents and over 26,000 public comments classified via large language models (LLMs). Results show that while mega influencers generate more reach and total engagement, macro influencers often achieve greater efficiency. Sentiment analysis reveals that emotional alignment with brand values is not always reflected in performance metrics. Some brands drew positive sentiment from influencer content even without strategic fit, while others achieved high alignment despite modest reach.
The proposed framework triangulates strategic intent, quantitative results, and audience sentiment. It addresses gaps in the literature related to the lack of integrated models that evaluate influencer campaigns across emotional, strategic, and performance dimensions. These findings suggest that campaign success depends not only on reach, but also on resonance, coherence, and alignment with brand values.
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Digital marketing Influencer marketing Marketing metrics Sentiment analysis Strategic goals