The $300B voice customer service industry has long been ripe for disruption. The typical Customer Service agent fields 1,000 calls per month, but due to outdated manual processes, only ever receives feedback on three or four of those calls. 40% of agents churn each year, in large part due to poor coaching. And only half of customers are satisfied with their customer experience, which in practice means countless lost opportunities to humanize brands and build emotional connections with customers.
Now add Observe.AI to the mix. Observe.AI is the leader in using next-generation Natural Language Processing to improve call quality. Observe.AI analyzes 100% of calls (up from today’s standard of just 1-2%) to provide performance insights for agent coaching. The platform allows contact centers to replicate what top agents do best while automating parts of the quality assurance process like compliance monitoring.
Today we are pleased to announce that Scale will lead Observe.AI’s Series A funding round and join the company’s Board of Directors.
The Business Impact of Voice AI
Observe.AI uses a machine learning approach known as ensemble learning to combine voice and text classifiers, an approach that outperforms traditional transcription and enables sentiment analysis by measuring intonation and rate of speech. For their customers, this means new ways to understand the full experience of every customer on every inbound call.
They also offer the industry’s first functional audio search. QA agents use it to find the exact moment when a particular topic was mentioned and then understand the content and sentiment surrounding it. This is key for contact centers with compliance requirements as it makes it easier to ensure regulatory standards are being met.
That same functionality enables better agent training as well. One key use case relates to an agent missing a compliance check during a call. Using audio search, supervisors can quickly find that moment then give the agent specific feedback and guidance.
Call centers have never had access to such high-value speech analytics before. One executive told us, “because Observe.AI delivers better compliance, the regulatory protection is enough to justify purchasing the product. When you add all the other benefits, it’s a no brainer to buy Observe.AI”.
Tangible Value from Day One
Observe.AI’s customers talk about the value of analyzing 100% of the conversations that happen between customers and call center agents. We repeatedly heard from customers that the product is easy to deploy and adds value from day one.
We also heard how Observe.AI provides visibility into the key behaviors of contact center agents that executives have never had before, such as what topics lead to long hold times or how specifically top agents turn negative customer sentiment into positive sentiment. Their customers talk about discovering new ways to use Observe.AI to improve operations and, ultimately, provide the memorable customer experience that is such a key different differentiator across industries.
Looking ahead, Observe.AI is laying the foundation for a future where voice insights can be used on live calls. Today, for example, voice insights can be used to coach agents, but in late 2020 they will be used to augment agents on live calls by providing relevant information like suggesting next steps or measuring a customer’s churn risk.
Human + AI Done Right
We’ve all experienced terrible customer service. We call for help but instead receive irrelevant answers that waste our time. Observe.AI leverages deep learning to automate tedious tasks and give new tools to help contact center agents deliver better customer experiences. Their technology is a great example of what we mean by the next-generation “helpful software” that defines the Intelligent Connected World.
We are happy to partner with Observe.AI and its founders Swapnil Jain, Sharath Keshava, and Akash Singh on their journey to build the best voice AI product–and help companies in a growing list of verticals deliver the best possible customer experience.
Oana Olteanu contributed to this article.