Podcast
October 17, 2025
Episode 63: Set It and Refine It: Clean Data, Auto-magically
Learn how AI-powered passive logging automates CRM hygiene without burdening sellers - and what you shouldn't automate. Feat. Arjun Ganatra.
In this episode of the RevOpsAF Podcast, co-host Camela Thompson, Head of Marketing and RevOps SME at RevOps Co-op, sits down with Arjun Ganatra, Business Systems Lead at Veriff.
With more than a decade spent untangling Salesforce instances and rebuilding GTM tech stacks for global teams at Stack Overflow and Vera, Arjun brings a practitioner’s eye to one of RevOps’ most chronic headaches: data hygiene.
What starts as a well-intentioned campaign to “clean the CRM” often becomes a war of attrition between operations and sales. Arjun’s solution flips the script — automate the capture, structure, and enrichment of data without touching the rep’s keyboard. He calls it passive logging, and it’s quickly becoming a cornerstone of AI-native RevOps.
Early in his career, Arjun believed — like many operators — that manual data entry was simply part of a rep’s job.
“If you’re paid a base salary, updating Salesforce should be table stakes.” — Arjun Ganatra
But after years of living on both sides of the table — as a seller, buyer, and operator — he realized the math doesn’t hold up. Every minute spent logging notes or updating opportunity fields is a minute not spent advancing pipeline.
The shift came when he began buying software himself. As a technical buyer, he experienced the other side of a disconnected process: fragmented hand-offs, missing context between calls, and redundant qualification questions. It was clear — messy data wasn’t just a reporting problem; it was killing customer experience and wasting cycles.
The new mindset: sellers should generate data naturally through the tools they already use, while RevOps orchestrates how that data is captured, cleaned, and activated downstream.
Most CRMs are still designed for manual inputs — dropdowns, text boxes, and required fields that slow sellers down. Passive logging reverses this paradigm by collecting structured data automatically from conversations, emails, and calendars.
Using AI-driven tools like Momentum, Arjun’s team now extracts critical fields straight from meeting transcripts and Slack recaps.
Here’s how it works in practice:
The result? More complete datasets, faster reporting cycles, and less seller resentment.
“If RevOps can automate 80 percent of capture, we give sellers 80 percent of their time back." — Arjun Ganatra
RevOps Co-op has several partners building AI technology to help with things like this. You can see a full list of our partners here.
Automation has limits. Some fields encode human nuance that AI still can’t infer reliably. Arjun cautions against “automating the art.”
Pipeline Stages:
“A rep knows why an opportunity sits in validation for 23 days — maybe procurement stalled or the champion went dark. That context doesn’t live in a transcript.” — Arjun Ganatra
Exit Criteria: Keep automation supportive, not directive. Salesforce’s Lightning interface can surface required fields contextually — a design trick Arjun used at Vera to show stage-specific fields in one sidebar component. Reps always know what they need to fill out, but they still own when to move a deal.
Over-Engineering: Forcing 20 required fields or 1,000 automation rules can backfire fast. “When the CRM stops matching reality,” he says, “the sales team revolts — and suddenly you’re back to forecasting out of spreadsheets.”
Instead, simplify. Build structure where AI can thrive (drop-downs, lists, and defined pick-lists), and protect human discretion where nuance matters.
When it comes to the full funnel, there’s plenty you shouldn’t do around automation - check out our prior webinar on Funnel Fiascos to learn what not to do (but how to fix it if you do).
The biggest barrier to clean data isn’t technology — it’s trust.
Before introducing any automation, Arjun aligns with senior sales leadership to ensure buy-in. He launches small champion cohorts of tech-forward reps who pilot new workflows for at least a month.
This approach yields two benefits:
“Your top-performing reps become your loudest advocates — use that volume strategically.” — Camela Thompson
Check out this prior podcast episode to learn how an enablement leader partnered with RevOps to implement a new tool, drive adoption, and measure impact through effective change management.
At Vera, passive logging is no longer theory. The RevOps team has successfully automated several core workflows:
Each of these automations adheres to a simple principle: reduce seller friction without reducing seller control.
AI and automation are transforming everything, including sales territory planning. Check out this blog post to see how RevOps can move beyond spreadsheets to build scalable, transparent territories with AI and automation.
Even the best automation fails if RevOps operates in isolation. Arjun urges operators to spend time “on the floor” — shadowing calls, observing workflows, and mapping pain points.
“Your frontline reps are your best product managers. Sit beside them, watch how they sell, and you’ll find five automations you can build tomorrow.” — Arjun Ganatra
This empathy-driven approach uncovers “quick wins” — the kind that build long-term credibility and make broader transformation possible.
To discover the key to sustainable revenue growth by treating RevOps as a product, aligning with C-level priorities, and solving customer gaps, check out this event recording RevOps as a Product: Building the GTM Engine.
Bad data isn’t just an operational issue — it’s a revenue leak. Forecasting errors compound across finance, customer success, and marketing attribution. A recent RevOps Co-op analysis found that companies with mature data-hygiene programs close deals 23 percent faster and retain 14 percent higher NRR.
Passive logging transforms data cleanliness from a compliance initiative into a strategic growth lever. It shortens the feedback loop between customer interactions and GTM decisions — enabling proactive coaching, more accurate forecasting, and better customer experiences.
Without clean data, AI will deliver unhelpful insights and deal-stopping guidance. Check out this digital event recording to learn 10 tips for tackling AI data quality challenges.
Looking ahead, Arjun predicts the next major leap will be voice-native AI assistants that allow RevOps teams to speak directly to their systems.
“I don’t want to craft a perfect prompt. I want to tell my AI what I need, and have it do the work.” — Arjun Ganatra
He also envisions dynamic buyer workspaces that automatically spin up after a call — aggregating transcripts, next steps, trust docs, and meeting links into a shared digital room. Think of it as the natural evolution of digital sales rooms — but built in real time by AI.
For more examples on how RevOps leaders are using AI to solver real operational challenges, check out out this digital event recording on Taking the Sexy out of AI: AI for Ops.
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