Marcel Barrera
Co-Founder & CSO
Marcel leads product strategy and development. He defines business initiatives, plans implementation efforts, and drives financial growth.
Marcel is a strategic customer experience executive with a commitment to helping clients solve some of the toughest challenges impacting growth, marketing, sales, customer experience, digital engagement, and operations.
He believes digital engagement and customer centricity are not only the standard for how companies engage consumers but believes more than ever, the human aspects of service experiences are hyper-critical to how businesses will differentiate themselves amongst the marketplace.
Prior to joining Anuj, Marcel was a Specialist Master at Deloitte where he led engagements for clients surrounding service transformation, CRM, and customer experience. Marcel has spent time at Accenture as well as Cognizant where he led the creation and framework for digital customer experience offerings and L'Oreal as a strategic leader for their Active Cosmetic Division providing acumen and guidance in consumer operations strategy and customer experience.
Marcel holds a Bachelor of Science in Business Administration with a minor in Marketing and received his MBA from the University of Phoenix. Marcel has spent over 20 years helping businesses meet the ever-changing demands of cross-industry customer expectations.
Articles by Marcel
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Articles
Software with a Service: Why Platform-Only Fails in Customer Service Intelligence
SaaS gives you software. SwaS gives you outcomes. Learn why Forward Deployed Engineers are essential for building the ontology that makes the Answer Engine work.
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Media
Marcel Barrera sits down with Adrian Swinscoe on the Punk CX Podcast!
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Articles
The Real Reason Customer Service Is Still Failing: It’s Not AI, It’s Your Data
Why AI Isn’t Reducing Contact Demand AI was supposed to reduce the number of customer inquiries, but demand has only increased.
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Articles
There is no LLM(ing) your way out of Service and Support ... not without MOB(s)
"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.
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Articles
Customer Support Doesn't Cause Demand ... They Solve It... Right?
The current solutions in the market are failing to address the core issues plaguing customer support.
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Media
serviceMob - Challenging the Service/Support Status Quo
serviceMob is revolutionizing the world of service/support - listen in to hear how we have created new Ai backed Smart KPIs!
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Case Study
Case Study: Leading Home Trades SaaS Unicorn
serviceMob used its service analytics platform to help a leading home trades SaaS unicorn
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Media
Marcel Barrera invited to talk on podcast episode with Brand F*UPS
Our CSO, Marcel Barrera, was invited to talk to Robyn Young, the podcast of Brand F*ups
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Articles
Data Entropy - The Mission Impossible of Service & Support
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.
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Articles
Answer Contacts, Solve Problems: Making life easier for Experience & Support Executives
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.
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Articles
Why Piles and Piles of Cases and Tickets - Suck the life out of 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.
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Articles
In a galaxy not to far away: serviceMob's Odyssey to Experiential Support
Despite the wealth of cases, tickets, and interaction insights, businesses face a fundamental challenge – the struggle to model data from the customer's perspective.
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Articles
The Hidden Dilemma in Customer Support: Quantifying Customer Experiences
The industry acknowledges the importance of improving customer experience, yet it largely lacks the conceptual data needed to understand customer behaviors and experiences
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Articles
The Tech-Mirage & Analytics Illusion of Service/Support
Data visualization tools struggle to explain the data of service in a manner that echoes the customer's voice.
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Articles
The Franken-Stack of Customer Service: A Monstrous Challenge for Executives
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.
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Articles
Unlocking the Data Dilemma: A Call to Redefine Service and Support
serviceMob is positioned as a solution for service leaders looking to address the challenges of managing customer service effectively, especially in the context of dark data.
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Articles
Transforming the Service Analytics Landscape: A Solution to Dark Data and Technical Debt
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?
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Articles
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.”
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Case Study
Case Study: Disruptive Healthcare Unicorn
serviceMob used its proprietary methodology and algorithms to help a healthcare unicorn forecast its contact demand better than the Erlang C model
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Articles
99 Problems with Customer Service and this is #1
Why customer service still sucks in the modern world, for you, me, and everyone in between, and why the first of its 99 problems is bad data.