Anuj Bhalla is the founder and CEO of serviceMob, the MIT-connected startup using cloud-based analytics and machine learning to improve the customer service experience at every level.
Customer service is a nightmare, but there is an MIT-connected startup with a novel approach that is transforming the industry as we know it. That 45-minute wait on hold to speak to the next available agent, the circular conversations with chatbots that don’t understand our wants and needs—all of it can be traced back to the fact that customer service operations rely on a set of disparate systems that muddy the waters for everyone involved. The founder and CEO of serviceMob, Anuj Bhalla, aims to change all of that.
Explaining the situation, Bhalla says, “This is not our parents' customer service, where calling a 1-800 number is the only way you can talk to a company. Now, you can call, SMS, email, text, or tweet your discontent to a company. These represent different systems that companies have to reconcile in order to paint a coherent picture of the customer service journey.” Whether you are a VP of customer service or a frontline agent working with what Bhalla aptly refers to as “a Franken-stack of systems” it is extremely difficult to obtain a coherent view of the end-to-end customer support experience. The result: we all suffer.
But Bhalla and his team are helping companies make sense of all the systems, all the data, to provide operators with the best possible information at every level of their business to make better, more informed decisions. ServiceMob’s platform gathers the information from these disparate systems across the entire customer service ecosystem and organizes it into a unique, coherent data ontology that allows its users to understand the cause-and-effect relationships that make the operation tick.
For example, many customer service operations are hyper-focused on increasing efficiency. Although this saves the company money in the short term, quality service is sacrificed. Agents might be motivated to get the customer off the phone as soon as possible. Which means resolution rates plummet, and the same customer calls the center several times to resolve the same issue. By looking at a holistic view of resolution—balanced with efficiency and effectiveness—customer service can deliver great service at a reduced cost to serve. From disparity to clarity, all thanks to serviceMob’s platform, which is underpinned by a systems dynamics framework created at the Institute.
A data scientist by trade, Bhalla studied applied mathematics at UC Berkeley before joining Accenture, where he headed up its service analytics practice, helping Fortune 500 companies get the most out of their customer service information. In other words, he spent years grappling with the disparate data problem of customer service. When he moved on from the corporate world, it was to earn his MBA at the MIT Sloan School of Management. As a Sloan Fellow, he realized that the disparate data problem was becoming more profound as more venture technology entered the customer service ecosystem. More interesting technologies (e.g., chatbots, conversational AI, next-best-action, sentiment analysis) were entering the landscape. but they were contributing to the disparate data set conundrum, making it harder to understand how customers moved through the customer service ecosystem. Working with MIT Professor Bill Aulet in his class on new enterprises, Bhalla crystallized his ideas for improving customer service and launched an early version of serviceMob.
Data analytics shouldn't just be accessible to data scientists
Today, serviceMob’s customer base represents a diverse number of industries, from software as a service (Saas) to healthcare, travel, and hospitality to shipping and logistics. With its tech-stack-agnostic platform, serviceMob delivers the goods—whether you use Salesforce, ServiceNow, or Microsoft Dynamics for your CRM, serviceMob’s platform recognizes the system and extracts the necessary data to feed into its universal data model.
Among their early customer base is a Cloud 100 SaaS company that used serviceMob's platform to drastically improve inefficiencies in its call center, saving over $13 million in the process. Bhalla points out that beyond bottom-line savings, his platform also impacts top-line results. “When you provide better service, that improves stickiness with brands. So as better service is provided through the insights and intelligence that serviceMob delivers, we've also seen improvements in top-line benefits, such as churn reduction, as a result of that better service.”
Transparency is an essential aspect of the startup’s success. “Data analytics shouldn't just be accessible to data scientists,” says Bhalla. “We believe that the best recipients of analytics in this specific industry are the agents themselves.” With serviceMob’s solution, frontline agents can track their own performance in real-time, measure their improvement over time, and even see how they compare to the floor and the rest of their team. The ability to understand where they need to improve helps drive customer-centric metrics toward the goals defined by their supervisors and managers, all the way up the hierarchy to the VP or chief customer officer. “When everyone has that same North star, the same metrics, you hit your targets faster, which ultimately improves the end-customer experience,” Bhalla explains.
And for the MIT alum, joining STEX25 is an honor and a tremendous opportunity. He notes that MIT ILP has already played an essential role in providing his young company with exposure to a host of Fortune 500 companies. He also recognizes that becoming a member of the elite MIT STEX25 cohort will allow serviceMob to showcase its technology while accelerating its message and gaining traction. And it really is a must-have. “At the end of the day, who doesn't want a better relationship with their customers? It’s a theme I should hope that every C-level, every CEO, should be thinking about today,” he says.
We want operators to have the best available data sets to understand who their customers are
“The current state of customer service is painful,” says Bhalla. And his long-term vision is to improve customer service at every touchpoint. “Analytics is the lifeblood that connects the disparity in how customer service works today,” he says. This is serviceMob’s bread and butter. “If I simplify the consumer world,” says Bhalla, “it works like this: We search for things, then we buy things, and then we need service for the things we buy.” For some time now, Google has dominated the search category. In the purchase category, the dominant player has been Amazon.
But the service category, according to Bhalla, is still a blank space, a world of opportunity. “That's where I see serviceMob playing a part to improve service at every level. We want operators to have the best available data sets to understand who their customers are, what issues they have, how we fix them, and then at the end of the day, how we improve customer service and the economic relationship between customer and brand. If we're doing that in the grand scheme of things, 10, 20, 30 years from now, I'll say we were successful.” All signs indicate that they are well on their way.