Aquant customer service automation platform raises $ 70 million
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Aquant, a platform leveraging AI to support customer service workers, today announced it has closed a $ 70 million Series C funding round led by Qumra Capital, Insight Partners and Pitango Growth with the participation of Lightspeed Venture Partners and Angular Ventures. The capital brings the company’s total raised to date to $ 110 million, and CEO Shahar Chen says it will be used to strengthen product development and expand the engineering, customer services and build teams. the Aquant market with positions in the United States, Europe, and Israel.
Customer service teams are increasingly embracing AI and automation as the pandemic continues to strain daily operations. According to Gartner, 37% of managers drive or use AI robots and virtual customer assistants, while 67% believe they are high-value tools in the contact center. Early adopters of AI solutions are reporting a 25% improvement in customer experience and accelerated innovation rates, along with higher competitiveness, higher margins and a better employee experience, reports IDC.
New York-based Aquant, which was founded in 2016 by Chen and Assaf Melochna, aims to proactively provide managers, representatives and teams with the information they need on demand. Aquant turns unstructured data into structured data, then predicts solutions to service challenges.
“By providing in-depth analysis of a company’s service data, Aquant is able to present a full body health report that shows strengths, weaknesses and opportunities for improvement,” Chen told VentureBeat by e. -mail. “The platform provides a clear map of a service organization. The same service data also helps provide specific service recommendations, helping field engineers correctly resolve the root cause of the problem the first time. From an executive standpoint, Aquant helps direct managers where to look, shows them what needs their attention, helps them set priorities, helps them develop training plans – all of which ultimately leads to a better and more magical service.
Make sense of data
There is a long list of common challenges in the customer service industry, especially in the after-sales service arena. In a 2018 survey, managers’ biggest concern is to ensure that their workforce in the field is operating at peak efficiency and productivity. An estimated 66% of the workforce uses knowledge bases, such as online FAQs, compared to 82% of customers. That’s why 70% of service organizations believe they will be burdened by the loss of knowledge of a retiring workforce over the next 5-10 years, reports the Service Council.
Aquant seeks to meet the challenge by extracting data from a variety of sources to learn the unique service languages of manufacturing, utility and telecommunications companies. At a high level, the platform captures the knowledge of subject matter experts by extracting information from data silos such as customer relationship management platforms and enterprise resource planning software. According to Chen, Aquant only takes a few days to learn a service language from millions of customer tickets, parts catalogs, inventory, supply chains, Internet of Things alerts, and more.
Aquant’s AI algorithms identify patterns and make decisions by interpreting differences in how service issues are described. The platform then extrapolates context and intent and maps problems to solutions by prioritizing technicians’ work schedules based on business goals. For example, Aquant can predict when customer complaints are the result of error or environmental factors in relation to product failure. Additionally, the system can automatically prompt team members to respond, recommending cost-effective solutions while looking for anomalies in warranty claims.
“[Our] platform… maps everything from employee performance to parts and asset performance and can create real-time customer risk alerts. Managers, directors and vice presidents can now see very clear links between their team and department performance levels and how these factors contribute to department results, ”explained Chen. “[We also provide] intelligent triage, which turns tribal knowledge into prescriptive intelligence, enabling call center agents and field technicians to resolve issues. A customer explains the problem and answers a few short additional questions, and our AI then recommends the most likely or cost-effective solution for the problem.
Aquant recently launched Service Insights, a tool that provides a window into factors that impact customer experience as well as recommendations, industry benchmarks, trends, workforce performance statistics, customer risk scores and training strategies. And in August, the company deployed Intelligent Warranty Audit, which categorizes data to help warranty officials process or reject “high risk” claims.
“Our customers, the service managers, are faced with a major problem: a shortage of skilled labor. This problem is the result of an aging workforce, a lack of interest in the skilled trades by the younger generations, higher turnover of millennials and millennials, and the acceleration of the labor shortage caused by the pandemic, ”Chen continued. “Managers struggle to find and retain qualified service technicians and, as a result, the quality of service and the customer experience suffer. Aquant offers a solution that captures and disseminates the knowledge of our customers’ most skilled employees, so new and low performers have the knowledge to deliver a great service experience every time.
Aquant’s competitors in the global customer service automation market include Cleverly.ai, supported by Zendesk, Kustomer, Directly, Zinier and, to a lesser extent, TechSee and CareAR. But the company has managed to carve a niche, with more than 30,000 users among customers including The Home Depot and Siemens Healthineers in industries such as medical devices, food equipment, capital goods, automation. industrial and appliance manufacturing.
“The most common competitive decision we face is that many service organizations try to build their own AI platforms in-house, but this can often take several years and require a whole team of data scientists, IT analysts and integrators, ”Chen said. . “In addition, they do not have the historical knowledge of other Aquant customers that is built into our data algorithms. Aquant’s AI takes industry knowledge and data and combines it with data from a service company, meaning our results are able to deliver solutions based on a dataset and a broader industrial context.
Aquant currently has 90 employees and plans to have more than 120 by the end of the year.
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