Countless tech platforms are setting out to help call centers automate conversations with their customers. But U.S-Indian startup and Y Combinator alum Observe.ai is bucking that trend by using AI to help improve human call center workers, rather than replace them — and it today announced it has raised $26 million in a series A round of funding to help with its mission.
Founded in 2017, Observe.ai’s platform uses natural language processing (NLP) to analyze conversations between human agents and customers. It then automatically transcribes each call, and carries out a sentiment analysis to determine customer satisfaction, while drawing correlations between the words and actions of the support agent and the happiness of the customer.
Top-performing agents can be used as benchmarks to determine what works, which can then help train new or under-performing support staff. Elsewhere, the Observe.ai platform can detect so-called “dead air,” including what caused the silence and how long it lasted for, to figure out where there the agent may have knowledge gaps. Interestingly, Observe.ai said that it can differentiate between different silence types, so that if an agent puts a customer on hold, for example, it will know that this isn’t the agent simply not having a quick enough answer to a question.
Above: Observe.ai dashboard
The platform can also prove useful for compliance purposes, as it can automatically find which agents are not using the correct phrases during each call. This is actually hugely important in certain industries, and helps to illustrate how Observe.ai more than simply about improving customer service — it can also help companies meet legal requirements.
“We can automatically surface a list of agents who did not follow the proper compliance protocols, for example, which are critical in healthcare, and re-train them,” Observe.ai CEO and cofounder Swapnil Jain told VentureBeat. “Or, we can identify agents with the most efficient ‘handle time’ or the fewest ‘supervisor escalations,’ and learn what they’re doing well and replicate their best practices.”
Above: Observe.ai: Agent feedback, including adherence to compliance phrases
In terms of pricing, Observe.ai operates a software-as-a-service (SaaS) model, and charges roughly $75 per month for each agent.
In its 2 years so far, Observe.ai has raised around $8 million in seed funding and amassed some big-name clients including Tripadvisor and recently-public companies Peloton and Farfetch. To help grow its teams in the U.S. and India, and accelerate its product development globally, the company raised a fresh $26 million in a round of funding led by Scale Venture Partners, with participation from Nexus Venture Partners, Steadview Capital, 01 Advisors, and Emergent Ventures.
“This investment will fuel our mission to elevate agent performance through coaching and voice insights,” Jain said.
The problem
With companies such as Google increasingly investing in automated call center smarts, it would easy to assume that human call center agents are on the high road to oblivion — but not according to Jain.
“Our perspective is that customers still want to talk to agents and there will always be scenarios in which customers prefer calls,” he said. “Agents are increasingly one of the only human connections people have with brands in a digital world, so we want to coach them to improve their performance with AI and augment them on live calls with insights that can be used to personalize the customer experience.”
According to a L.E.K report last year, voice-based customer service alone is a $300 billion-plus market. And although customer service spans multiple channels, with social media or live chat often the first port-of-call for more straight-forward enquiries, call centers tend to be where the most complex queries end up — automated voice bots might not always be the best solution for those scenarios. But ensuring quality at scale is a tough nut to crack for larger contact centers, which is why Observe.ai is pushing a different kind of automation.
Moreover, in competitive industries, the quality of customer care is often the one big differentiator, making it all the more important to optimize agent feedback and coaching through analyzing large pools of data.
“To drive operational efficiencies agents need to be even better trained, and the organization needs to be able to access insights from conversations and put them to work in an agile way to continue to refine their products and processes,” Jain added. “This is because brands are being forced to push out new products and services faster than ever, and many are only competing on the quality of their customer service.”
Alongside today’s funding news, the San Francisco-headquartered startup also announced that it has entered into a “long-term strategic partnership” with Microsoft, which will see Observe.ai’s platform promoted through Microsoft’s Azure marketplace. This is in addition to other existing technology partnerships and integrations such as cloud-based contact center software provider Talkdesk, which Observe.ai teamed up with last year.
Since then, Observe.ai has grown its headcount from 5 to 45 across its U.S. and Indian hubs, and is on track to double that figure in 2020. And although it hasn’t revealed its current income or profit figures, the company is projecting a four-fold increase in its annual recurring revenue (ARR) next year.
Lay of the land
There are a number of other players operating in this sphere, including legacy systems from the likes of Verint and Nice Technologies, while a number of companies offer various elements of Observe.ai’s platform such as speech and sentiment analytics. Cogito, which recently raised $20 million from big-name backers including Salesforce and Goldman Sachs, is perhaps one good example of how AI is being used to help customer service agents — Cogito, however, focuses more on detecting emotion in phone calls, to help agents develop empathy and improve their rapport with customers.
Observe.ai pitches itself as a more extensive platform that focuses on improving every facet of the phonecall, by looking at the “how” and the “what” — including digging down into specific problems the customer had, and the efficacy of the agent in dealing with it.
“Legacy speech analytics and talent management systems are simply not meeting the needs of the world’s top brands,” Jain said. “Today’s customer service agents have a unique ability to emotionally connect with customers and are often a brand’s only frontline representatives.”
Other companies worth noting include Gong, which does something similar to Observe.ai but with a focus on sales calls — Gong announced a $65 million round of funding led by Sequoia just last week. Chorus.ai, which raised $33 million last year, is of a similar mold to Gong.
Author: Paul Sawers
Source: Venturebeat
