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Why AI Isn’t Reducing Contact Demand AI was supposed to reduce the number of customer inquiries, but demand has only increased.

September 23, 2024

The Real Reason Customer Service Is Still Failing: It’s Not AI, It’s Your Data

"Multivalent Ontological Blocks (MOBs) provide the foundation for Large Ontological Models (LOMs), fueling AI systems to revolutionize service and support by addressing the root causes of contact demand.

September 23, 2024

There is no LLM(ing) your way out of Service and Support ... not without MOB(s)

"During his tenure at Accenture, he led the Service Analytics practice and filed three patents in the customer service field, demonstrating his innovative thinking."

September 2, 2024

Los Angeles Times names Anuj Bhalla a 2024 CEO Visionary

The current solutions in the market are failing to address the core issues plaguing customer support.

Customer Support Doesn't Cause Demand ... They Solve It... Right?

I’m super excited and humbled to join an esteemed panel and workshop for Irvine Tech Week for the second consecutive year representing serviceMob!

serviceMob Kicks Off Irvine Tech Week with Joshua Lee and Somasundaram Subbu

The Excellence in Entrepreneurship Awards celebrate individuals who embody the American entrepreneurial spirit, and Anuj is among a distinguished group nominees representing the best in Southern California.

Nomination Alert for the 2024 Excellence in Entrepreneurship by the Orange County Business Journal

With a shared commitment to fostering inclusivity and empowering individuals to succeed, MSIVL's support has been instrumental in fueling serviceMob's growth and success.

Gratitude to Morgan Stanley: Empowering Startups Through the Inclusive Ventures Lab

For years, teams have used operational efficiency metrics, case/ticket metrics, and subpar perceptual survey data with response rates well below 15% to make any decision about suppor

The Hamster Wheel Dilemma: Why Support Metrics Aren't Changing

Now, you might wonder, why does data entropy matter in the realm of customer service and support? The key lies in the partitions of your tech stack.

Data Entropy - The Mission Impossible of Service & Support

Seriously—I still cannot believe in 2024 here we are, still thinking surveys are the best dataset we can get. When it comes to cases, we create no common linkage to the behaviors of customers, nor do we collect all the data in a meaningful way to truly reduce OPEX, improve Gross Margin, and drive consistent service outcomes.

Why Piles and Piles of Cases and Tickets - Suck the life out of support...

Forcing channels on customers prescriptively vs. understanding issue and customer preferences really creates a multitude of problems, including repeat contact demand, re-work, poor CSAT, and ultimately churn. Its still baffling to me that accessing the voice channel for customers is still harder than ever.

Answer Contacts, Solve Problems: Making life easier for Experience & Support Executives

Despite the wealth of cases, tickets, and interaction insights, businesses face a fundamental challenge – the struggle to model data from the customer's perspective.

In a galaxy not to far away: serviceMob's Odyssey to Experiential Support

The industry acknowledges the importance of improving customer experience, yet it largely lacks the conceptual data needed to understand customer behaviors and experiences

The Hidden Dilemma in Customer Support: Quantifying Customer Experiences

Data visualization tools struggle to explain the data of service in a manner that echoes the customer's voice.

The Tech-Mirage & Analytics Illusion of Service/Support

Frustration with customer service is experienced at the customer and enterprise level as a result of “Bad Data.”

February 10, 2023

How analytics failed the world of customer service

Frustration with customer service is experienced at the customer and enterprise level as a result of “Bad Data.”

February 10, 2023

99 Problems with Customer Service and this is #1

The promise that we would AI our way to automating the service journey has in fact, not ... happened... and likely will not. This begs the question: how effective are the analytics of service today if we are still hiring more agents, still talking with customers, and still getting the same contact demand?

Transforming the Service Analytics Landscape: A Solution to Dark Data and Technical Debt

The program was also listed as one of Global Finance’s Best Innovation Labs of 2023. We look forward to be a part of this accelerator program!

October 11, 2023

Unlocking the Data Dilemma: A Call to Redefine Service and Support

The fragmented data within the Franken-stack makes it nearly impossible to measure resolution effectively. Instead, it becomes a wild goose chase, with customers making multiple contacts to solve a single issue.

October 11, 2023

The Franken-Stack of Customer Service: A Monstrous Challenge for Executives