Enterprise

Neuron7 raises $10M to help customer service agents find solutions

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Woman with headset is sitting at her computer and talking with client. Clients assistance, call center, hotline operator, consultant manager, technical support and customer care. Vector illustration.
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In the customer service arena in particular, enterprises are facing a historic labor shortage. Owing to burnout, flexibility and customer satisfaction challenges, agents are quitting at a faster rate than in the past — a problematic trend in a high-turnover industry. According to a February 2022 Salesforce report, 71% of customer service agents have considered leaving their job in the past six months. The impact is becoming clear. Forrester’s annual study on customer service found that 19% of brands in the year through April 2022 saw their customer experience rating fall — the highest proportion to drop in one year since the study’s inception.

Vinay Saini and Niken Patel, the co-founders of Neuron7, say that they observed this firsthand — Patel in advisory roles at Deloitte and Fujitsu and Saini as the CFO and COO at Oracle software partner Serene. (Patel also worked at Serene, moving his way up from the role of EVP to CEO.) According to Patel, the organizations he and Saini consulted with often collected massive amounts of customer service data yet struggled to use it effectively, leading the data to become stale and unused.

“The real insight on how to [address customer] issues was spread across multiple silos — and, usually, in experts’ heads,” Patel told TechCrunch in an email interview. “They’d spend tons building knowledge bases and search applications on top of the data, but those systems just weren’t sophisticated enough to find resolutions to customer issues quickly and consistently.”

Frustration led Saini and Patel in 2020 to launch Neuron7, a startup that parses customer service records to help agents and technicians resolve product issues. As Patel describes it, Neuron7 uses natural language processing to guide users step by step, analyzing metadata from knowledge bases, product documentation, customer support call logs and transcripts to create a “collective intelligence” that can help diagnose and solve problems.

Neuron7 isn’t the first to market with a recommendation engine for customer service — far from it. Beyond incumbents like Salesforce, the vendor has rivals in Zingtree and Talla, which combines customer content with automation and machine learning to help agents get at information they need. Ultimate.ai also provides an AI-driven service that delivers real-time help to staff dealing with customer queries.

Neuron7
Image Credits: Neuron7

It’s not surprising that the segment is rife with competition. According to one estimate, customer service is a $350 billion-a-year industry — and the stakes are high. Ninety percent of Americans responding to a 2020 Microsoft said that they use customer service as a factor in deciding whether to do business with a company; 58% said they’ll switch companies because of poor customer service.

But Patel notes that Neuron7 can power self-service portals for both customers and employees beyond the customer service division. That’s one differentiator, in his mind — the other being Neuron7’s algorithmic innovations. Investors were evidently won over by the pitch, with Battery Ventures and Nexus Venture Partners co-leading Neuron7’s $10 million Series A (which closed today).

Drawing on existing systems like Salesforce Service Cloud, ServiceNow, Microsoft Dynamics 365, Neuron7 attempts to understand the context of a question to find an answer from within a body of customer service documents. To inform future recommendations, the platform also tries to capture how technicians diagnose and solve issues, in part by monitoring data streams from relevant connected devices.

“We believe it’s important for AI to go way beyond analytics and high-level AI predictions. We don’t want to just give a report card that shows how service organization is doing — we want to help change the report card by impacting the most crucial service metrics,” Patel said. “Customer service data is often siloed across geographic locations, product areas and even within different customer service departments and systems. Neuron7 solves an expensive problem for IT, by putting it to work without developing custom search applications or funding expensive data integration and curation projects … The beauty of AI is that it continuously improves with each outcome — nothing ever gets stale.”

Patel didn’t reveal the number of customers Neuron7 is currently servicing, but named Sofftek, an IT and business process consultancy, as one of them. He said that the proceeds from the Series A will go toward client acquisition efforts as well as expanding Neuron7’s 20-person workforce, with a focus on the go-to-market and product teams.

“The pandemic hit customer service organizations very hard by increasing employee turnover, and with each departure, years of expertise leave the team. It also forced companies to not roll trucks and send field service engineers on site, unless absolutely necessary,” Patel said. “These situations make customer service productivity and collective intelligence building tools like Neuron7 extremely valuable due to its ability to make new employees as productive as experts and to increase customer service KPIs across all tiers of service. Unless customer service productivity and profitability go out of style, Neuron7 will be fine.”

Neuron7 has raised a total of $14.7 million to date inclusive of the Series A.

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