Case Study: LocalResponse achieves 300% higher click-through rates with DataSift

Local Response - Customer Case Study

LocalResponse, a marketing company that uses social signals to measure intent and improve ad targeting, needed a scalable way to listen to, filter, and process massive volumes of Twitter data. To stay focused on refining its natural language processing approach, it turned to DataSift and its Twitter Firehose access, enrichment, and filtering capabilities.

DataSift enabled LocalResponse to ingest only the social data it needed, add richer context such as sentiment and language detection, and use historical data for audience discovery. As a result, LocalResponse could keep improving its core product while delivering better-targeted campaigns; in one campaign, DataSift helped drive a 300% increase in ad click-through rates.

Local Response

Michael Muse

Co-Founder and VP of Product and Operations, LocalResponse