The BirdEye platform scales thousands of locations in real-time, and BirdEye’s Natural Language Processing (NLP) engine, Athena, humanizes big data so you can understand the sentiments expressed in feedback — both company-wide and location-specific.
Layers of insights
BirdEye structures insights in 3 tiers: Business drivers, sentiment drivers, and customer verbatims. Insights are designed to spur decisive action from executives down to the frontlines. Category analysis tells a restaurant its food has negative sentiment. Digging deeper, the restaurant finds a surge in negative mentions for “pizza”.
Sudden shifts detected in negative feedback sentiment can uncover emerging trends in customer experience that threaten a brand. In the above example, a closer look reveals the restaurant’s pizza is frequently described as “burnt”. Location analysis shows which locations received the most mentions of “burnt pizza” in the past 7 days. Corporate can call these locations’ managers to fix this problem before it escalates.
Drive improvement and growth
Activate customer insights found in all sources of feedback and let the voice of the customer guide company-wide decisions. Measure ROI by tracking how sentiment trends progress across time periods, locations and products.