How do you move from transactional interactions to trust-driven relationships — and use AI to actually know your customer, not just contact them?
Together, they explored how Jabra is transforming its customer experience through AI-powered data architecture, compliant automation, and a patient-first mindset that makes trust the core of every operational decision.
When Susan Thomas joined Jabra nearly three years ago, her team was swimming in data — but drowning in systems. Each customer interaction lived in a different tool. Agents toggled between telephony software, chat apps, email queues, and separate databases for audiology appointments and order fulfillment.
“We realized our teams were blind to context,” Thomas explained. “A customer would call, and we couldn’t easily see their past purchases, previous service cases, or even the notes from their last audiology visit.”
Jabra’s solution: bring everything under one roof with Salesforce as the single source of truth.
Today, every customer interaction — from online orders to in-app chats to voice calls — flows through Salesforce Service Cloud. Audiologists record patient notes and hearing goals inside Salesforce. Fulfillment runs directly from the same system. Even retail order data syncs into the same environment.
This end-to-end integration didn’t just improve operational visibility — it created an unprecedented dataset that now powers their AI strategy.
“Once we centralized everything,” Thomas said, “we realized just how much intelligence we were sitting on. We had the data. The question was: what could we do with it?”
Are you juggling disconnected and inefficient RevOps processes, tools, and teams? It’s time for a RevOps audit. Don’t worry, you can do it yourself. Check out RevOps Co-op Video Series: How to Perform a RevOps Audit.
Most RevOps teams can spin up new AI tools in a day. For healthcare and life sciences, it’s not that simple. Every data flow touches HIPAA compliance, PHI protection, encryption, and consent management.
That means you can’t “just try things.”
“Testing new software in a regulated environment is a different sport,” said Volm. “If I wanted to trial a call recording tool, I could spin it up today. But Jabra can’t. Every tool has to meet security, retention, and audit requirements before it touches production data.”
Instead of fighting that reality, Jabra leaned into it — designing an AI strategy that uses Salesforce-native tools (Einstein, Agentforce, Shield, and Data Cloud) within the guardrails of their existing infrastructure.
By working with Apparatus, they hosted internal AI Lunch & Learn sessions to demystify what Einstein and Agentforce could actually do.
“We didn’t know what we didn’t know,” Thomas admitted. “It wasn’t about building something immediately. It was about understanding the art of the possible.”
This mindset shift was key. By aligning AI exploration with compliance and education from the start, Jabra could innovate without ever risking patient privacy.
If you want to discover how AI can bridge the gap between data teams and GTM leaders in RevOps, along with strategies for better alignment and faster insights, then check out RevOpsAF Podcast Episode 40: Leveraging AI to Align Departments.
With thousands of customer calls and chats coming in every week, Jabra’s CX team faced a classic scaling problem: too much qualitative data, not enough time to analyze it.
Each week, the company hosted “Voice of the Customer” sessions, manually reviewing random call samples to spot recurring issues. It was valuable — but painfully inefficient.
“We were listening to calls one by one,” said Thomas. “It was like trying to understand a forest by looking at one tree at a time.”
So Jabra and Apparatus used AI to tag, categorize, and summarize interactions automatically. With Einstein and Agentforce, they began processing transcripts from Salesforce Voice, live chat, and email threads, then extracting key signals:
This automated enrichment replaced anecdotal feedback with structured insight — giving the team real visibility into patterns across 250,000+ interactions.
“When agents close a call, they can only pick one reason from a dropdown,” Thomas explained. “But customers don’t just call for one thing. AI gave us back the rest of that story.”
It also surfaced quick wins: one insight showed that customers were frequently asking for downloadable instructions for hearing aid accessories — something easily fixed by publishing PDFs on the website.
Small data improvements like that compound fast when multiplied across thousands of conversations.
Want to see how AI transforms CRM records, enhances data quality, and reshapes B2B sales? Then check out RevOps Co-op Video Series: AI Data Enrichment: The Future of 3rd Party Data in GTM.
One of the session’s most repeated refrains came from host Matthew Volm:
“Don’t start with AI. Start with the problem.”
It’s easy to get caught up in the hype cycle. But as Jabra’s team discovered, successful AI deployment in RevOps starts by identifying friction points — and solving those first.
In Jabra’s case, that meant focusing on visibility and insight rather than immediate automation. Instead of trying to replace agents with bots, they used AI to enhance their understanding of customers.
Fezza described this as building “augmented teammates,” not replacements. “You’re not creating magic from scratch,” he said. “You’re taking what you already do — workflows, processes, automation — and adding an intelligent layer on top.”
This principle guided their roadmap:
Each phase built confidence — not just in the technology, but in the people using it.
Looking to explore how AI shapes decision making in B2B marketing and revenue operations and uncover AI's role and constraints in driving an effective revenue engine? Then check out RevOpsAF Podcast Episode Episode 24: Why AI is the Last GTM Tool to Buy.
Introducing AI into customer workflows can trigger fear: “Will this replace my job?” or “Can we trust the results?”
Jabra tackled this head-on through a structured change management plan. Their agents still manually disposition every call. The AI runs in parallel — tagging, summarizing, and scoring sentiment — creating a living feedback loop between humans and machines.
This dual system provides a built-in validation layer. If the AI tags a call as “product malfunction” but the agent selects “shipping delay,” it triggers a quality check and prompt refinement.
“We’re running the AI alongside our team to learn where it adds value,” said Thomas. “It’s an iterative process, not a replacement process.”
Fezza reinforced that governance is an ongoing discipline, not a one-time setup. “AI needs more refinement than a typical tech rollout. You build, test, validate, refine — over and over. That’s how you get reliable output.”
This approach helped Jabra avoid the “AI whiplash” that often follows rushed deployments: data inconsistencies, low adoption, and internal skepticism.
If you’re interested in how fairness and transparency make or break territory planning and how RevOps can master equity and change management in territory design, then check out RevOps Co-op Blog: The Biggest Hurdles in Territory Design: Equity and Change Management.
Both speakers agreed: the key to AI success in RevOps isn’t accuracy on day one — it’s iteration.
Within months, Jabra had transformed its Voice of the Customer program. AI-tagged call data now feeds directly into weekly meetings, allowing CX and product teams to quickly spot trends.
Instead of debating anecdotes, they’re reviewing quantified sentiment scores, call themes, and follow-up actions — all generated automatically.
“We’re finding themes in hours, not weeks,” Thomas said. “That efficiency gives us more time to fix issues, not just talk about them.”
The next phase? Proactive case deflection and AI-guided self-service. Using Salesforce Data Cloud and Agentforce, Jabra is exploring how to automatically suggest help articles or escalate high-sentiment cases before they reach an agent.
By pairing human empathy with machine context, Jabra is shifting from reactive support to predictive care — a leap that’s redefining what “customer experience” means in healthcare.
For more on how operators can align the tactical with the strategic, check out RevOpsAF Podcast Episode 39: Aligning the Tactical with the Strategic.
“It’s okay to be learning,” said Thomas. “You don’t have to automate everything. Start by using AI to understand your customer more deeply — that’s where trust begins.”
AI isn’t about replacing human expertise — it’s about unlocking it. Jabra’s story shows that even in highly regulated industries, operators can use AI to bridge the gap between data and empathy, structure and trust.
By combining governance, education, and a RevOps-driven architecture, Jabra has proven that AI can do more than streamline workflows — it can help companies listen at scale.
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