It’s tough to be a community manager. Nearly half of all customer outreach occurs over social channels like Facebook, Twitter and YouTube. By 2020, 85% of all consumer interactions will be handled without a human representative. Consumers increasingly expect brands to answer their customer service questions accurately, and in real-time. That’s why our product & technology teams built Q - an enterprise platform that uses machine learning and A.I. to streamline any brand’s social customer service operation.
We spent over a decade building and managing the social communities for the world's largest brands. On social media, customer service requests are usually received in a non-linear fashion. They can take the form of comments on a post, or replies to other customer comments, and increase in volumes that make it hard for community management teams to accurately triage, assess, and respond, in real-time.
Q solves these issues by using machine learning and natural language processing (NLP) to improve accuracy and efficiency of community management operations. By detecting the intent of what’s being said, Q is able to recommend responses and delegate them to the right community moderator, significantly decreasing the amount of time it takes to reach the consumer.
Every new query further trains Q. With every response, Q becomes smarter, and the customer experience is improved.
In a recent 3 month pilot with a major pharmaceutical client, our teams found that Q’s overall response time was 93% quicker compared to the brand’s manual community management operation. Q’s overall response rate was consistently double or triple that of the brand across 3 months, averaging 45% vs. 14%. This increase in accuracy can be expected to continue to grow over time beyond the pilot period as the NLP engine continues to learn and respond to consumer intents.
Q can also be extended to other applications beyond day-to-day social community management; from conversation and trend analysis, to driving commerce and facilitating employee communications - the possibilities are endless.
Is this the kind of work you’d like to do? If you have a pointed view on the future of media, and the skillset to help realize it, we’d like to hear from you.