While a top automotive company had a large staff monitoring social media messages, they recognized a need to optimize the process in order to more efficiently identify potential customers and respond to them. To do this, the automaker utilized the Interactions Digital Roots social media engagement platform to classify social media posts, label engagement opportunities, and offer auto-suggestions based on customer intent. This led to twice the number of customers engaged per hour for agents using the auto-suggest feature and 35% faster responses.
While the Interactions Digital Roots platform offered these three key results, the entire process was optimized and enhanced from start to finish compared to the previous agent-driven system. The platform started with real-time classification and engagement labeling, so customers could be identified based on intent. Additionally, the automotive company saw optimization and adaptation from the auto-suggest feature. The AI not only learned from agents to enhance its automated responses, it also understood brand voice—ensuring that customers received a cohesive, on-brand experience every time.