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AI-powered customer service analytics platform SupportLogic announced today that it has raised $ 50 million in Series B financing led by WestBridge Capital Partners and General Catalyst, with the participation of Sierra Ventures and Emergent Ventures. CEO Krishna Raj Raja says the funds, which bring SupportLogic’s total fundraising to over $ 62 million, will be used to support the company’s growth and ongoing platform development.
Santa Clara, California-based SupportLogic was founded in 2016 by Krishna Raj Raja, an early support engineer at VMware and the first employee in the company’s office in India. Raja says he initially observed that customer intentions were lost among organizational silos and customer relationship management and support ticketing systems.
“[I] founded SupportLogic with the mission to transform the role of customer support as a proactive change agent in companies by being able to capture and act on the customer’s true voice to grow and protect customers’ revenue, ”Raja told VentureBeat via email. “Our new funding will help SupportLogic add more customer interaction channels to the solution set – for example, more data sources such as Chat, voice, discussion forums, surveys and emails. We will also expand our agent coaching and customer health management functions. ”
AI-powered customer service
The pandemic brought sharp relief to the value of AI in customer services. Gartner predicts that 15% of all customer service interactions globally will be fully powered by AI by 2021. And according to Deloitte, 56% of companies are investing in conversational AI technology to enhance cross-channel experiences.
SupportLogic specializes in extracting customer signals from business communications with case evaluation and agent coaching tools. Using natural language processing, the platform provides recommendations to managers to get ahead of the escalations and helps identify the best cases in a backlog to be reviewed. SupportLogic also provides intelligent case management using its AI engine to determine the best available agent to handle a case based on factors such as emotion and churn risk. In addition, the company’s product supports non-support features, including product management, that provide visibility to customer challenges that customers can act on.
“High emotion analysis and device extraction machine learning models are trained in a completely different corpus and do not work on these datasets. Most of the tools in this space focus on case degradation cases, such as chatbots, robotic process automation, and knowledge management, ”said Raja. As such, there have been no software-as-a-service solutions that do what SupportLogic does to date. In fact, many of our customers initially started building their own solutions, and SupportLogic often displaces these homemade projects. ”
SupportLogic designed its platform using an ensemble method – a machine learning technique that combines multiple base models to produce an optimal prediction model – running on Google’s BERT. The model and its predictions, trained from millions of customer interactions, are tailored to each customer using a core signal extraction engine built on a common framework.
SupportLogic claims that it has thousands of users across “many large corporate accounts.” In 2021, the startup’s customer base grew by 300%, while the number of interactions analyzed by its AI grew from 15 million in 2020 to over 60 million in 2021, the company says.
“When the pandemic hit, as in all other industries, we thought we would be negatively affected. But surprisingly, we were not, ”said Raja. “The support engineers for our customers all started working more remotely and collaboratively. SupportLogic provided an immediate benefit to these organizations – e.g. Agent coaching became easier to do … We also developed the product to help our clients manage the impact of the pandemic in their own companies. For example, a few customers asked us to help them track pandemic-related keywords like ‘COVID 19’, which we quickly activated in our product. “
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