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What’s up everyone, today we have the pleasure of sitting down with Aditi Uppal, Vice President, Corporate Marketing at Teradata.

Summary: Aditi shows how five honest conversations can reshape how you read data, because customer language carries context that numbers miss. She points to overlooked signals like product usage trails, community chatter, sales recordings, and event conversations, then explains how to turn them into action through a simple pipeline of capture, tag, route, track, and activate. Tools like BrightEdge and UserEvidence prove their worth by removing grunt work and delivering usable outputs. The system only works when culture supports it, with rapid response channels, proposals that start with customer problems, and councils that align leaders around real needs. Blend the speed of B2C listening with the discipline of B2B execution, and you build strategies grounded in reality.

In this Episode…

• How to Use Customer Conversations to Validate Marketing Data
• Balancing Quantitative Data with Customer Conversations
• Gathering Customer Insights From Underrated Feedback Channels
• Activating Voice of Customer with AI Agents
• How to Use Rapid Response Teams in Marketing Ops
• Building Customer Obsession Into Marketing Culture
• Why Voice of Customer Works Differently in B2B and B2C

About Aditi

Aditi Uppal is a data-driven growth leader with over a decade of experience driving digital transformation, product marketing, and go-to-market strategy across India, Canada, and the U.S. She currently serves as Vice President of Corporate Marketing at Teradata, where she leads global strategies that fuel pipeline growth and customer engagement. 

Throughout her career, Aditi has built scalable marketing systems, launched partner programs delivering double-digit revenue gains, and led multi-million-dollar campaign operations across more than 50 technologies. Recognized as a B2B Revenue Marketing Game Changer, she is known for blending strategy, operations, and technology to create high-performing teams and measurable business impact.

How to Use Customer Conversations to Validate Marketing Data

Dashboards create scale, but they do not always create confidence. Aditi explains that marketers often stop at what the model tells them, without checking whether real people would ever phrase things the same way. Early in her career she spent time talking directly to retailers, truck drivers, and mechanics. Those interactions were messy and slow, filled with handwritten notes, but they gave her words and patterns that no software could generate. That language still shapes how she thinks about campaigns today.

She argues that even a small number of conversations can sharpen a marketer’s decisions. Five well-chosen interviews can give more clarity than months of chasing analytics dashboards. Once you hear a customer describe a problem in their own terms, the charts you already have feel more trustworthy. As Aditi put it:

“If you get an insight that says this is their pain point, it helps so much to hear a customer saying it. The words they use resonate with them in ways marketers’ words often do not.”

She points out that B2C teams benefit from built-in feedback loops since their channels naturally keep them closer to customers. B2B teams, on the other hand, often hide behind personas and assumptions. Aditi suggests widening the pool by talking to students and early-career professionals who already use enterprise software. They may not be buyers today, but they become decision makers tomorrow. Those conversations cost almost nothing and create raw material more valuable than agency-produced content.

She frames the real task as choosing the right method for the right question. If you want to refine messaging, talk to your most active customers. If you want to understand adoption patterns, run reports. If you want to pressure test a product roadmap, combine both and compare the results. Decide upfront what you need and when you need it. Then continue adjusting, because customer understanding is not a one-time project, it is an ongoing discipline.

Key takeaway: Use customer conversations as a validation layer for your data. Pair five direct interviews with your dashboards, and you gain language, context, and trust that numbers alone cannot provide. Always define why you need an insight, then pick the method that gets you there fastest. That way you can build messaging, campaigns, and roadmaps grounded in reality rather than in assumptions.

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Balancing Quantitative Data with Customer Conversations

Marketers keep adding dashboards, yet confidence in the numbers rarely grows. Aditi argues that a few customer conversations often do more to build certainty than a warehouse of metrics. Early in her career she spent long days interviewing retailers, truck drivers, and mechanics. She filled notebooks with their words, then worked through the mess to find common threads. The process was slow, but it created clarity that still guides her perspective today.

“You do not need hundreds of those conversations. You just need five, and you will come out so much more confident in the data you are looking at.”

That perspective challenges a common assumption in B2B marketing. Models can predict buying intent, but they cannot capture the urgency or tone that customers bring to their own words. Dashboards may flag data scientists as target buyers, yet when you sit with an aspiring data scientist, you hear frustrations and motivations that algorithms miss. Real language often carries sharper meaning than the polished words marketers invent for campaigns.

Aditi warns that relying only on quantitative signals pushes teams into a self-referential loop. Marketers build strategies based on metrics, then describe those strategies in their own buzzwords. Direct conversations break that loop. Even five interviews can ground your messaging, highlight gaps in the data, and validate where models are directionally right. B2C teams often benefit from tighter feedback loops through customer-facing channels. B2B teams need to create their own versions of those loops by talking to users directly, including students and early-career practitioners who represent the next generation of decision makers.

Every stage of marketing benefits from this practice. Roadmaps become sharper, content becomes more resonant, and campaign ideas carry more weight when tested against real voices. Customer interviews cost little compared to polished content campaigns, yet they create a foundation of confidence that technology alone cannot replicate.

Key takeaway: Five direct customer conversations can build more confidence than a room full of dashboards. Capture the exact words your buyers use, compare them with your data models, and use both inputs together. That way you can validate your metrics, sharpen your messaging, and trust that your strategy connects with the people who matter most.

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Gathering Customer Insights From Underrated Feedback Channels

Marketers love surveys. They love sending out NPS links, post-purchase forms, and satisfaction checkboxes that make dashboards look busy. Aditi is blunt about the limits of this ritual. A buying committee has users, influencers, and decision makers. Each group has different needs, and you cannot lump them into a single “customer voice.” If you want useful signals, you have to decide who you are listening to and why.

Product usage data is the first place she looks. Watching how users move through a product says more than a checkbox ever could. Heat maps show hesitation. In-product surveys capture emotion in the moment. Even journey paths become a story of confusion, discovery, or frustration. These signals are raw, immediate, and harder to ignore. As Aditi puts it:

“Great avenues for us to get insights come while they are using the product.”

She also calls out community chatter. Marketers often dismiss Reddit or niche forums as noise, but those conversations are brutally honest. Users talk without scripts, and the commentary is rarely softened for company ears. If you are serious about understanding perception, you need to be there, reading what people actually say. That way you can see how your messaging lands outside your echo chamber.

Sales recordings bring another layer. SDR and MDR calls capture the first raw reactions from prospects. Aditi recalls one call where a prospect said, “I thought you guys were selling a point solution, but that’s not who you are.” That single misunderstanding forced her team to rethink positioning. You cannot get that kind of feedback from a survey. It only surfaces when you listen to actual conversations at the earliest touchpoints.

Events matter too, but not only for leads. Third-party conferences, sponsor booths, even hallway chats become high-volume feedback loops. Her team found so much market intelligence at events that they had to automate collection just to keep up. The secondary value often outweighed the direct ROI. Most companies measure events in closed deals, but they miss the chance to mine those conversations for real input about how the market thinks.

Key takeaway: Stop treating surveys and NPS scores as the default source of truth. Use product usage data to see what people do, monitor communities to hear what they say, analyze sales recordings to catch what they believe, and collect event conversations to understand what they want. Each channel adds a layer of perspective. If you build processes to capture and act on these signals, you can correct messaging errors early, align product priorities with user behavior, and avoid wasting budget chasing the wrong story.

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Activating Voice of Customer with AI Agents

Most companies collect customer feedback and then bury it in transcripts, survey exports, or CRM notes. Aditi argues that the only way to create value from voice of customer data is to treat it like a pipeline that runs end to end. Feedback needs to flow through structured steps instead of lingering as anecdotes in a slide deck.

She breaks the work into five clear functions:

1. Capture the raw input from calls, events, or surveys.
2. Tag the data with metadata such as topic, intent, and segment.
3. Route it to the right team or individual.
4. Track it through to resolution with clear ownership.
5. Activate it by feeding back into messaging, campaigns, or product updates.

“A Gong call reveals a trend, like multiple buyers in manufacturing asking how we compare to a competitor. An agent can pick that up, extract the tags, and push it into Slack. From there, product marketing gets the assignment to update messaging or create a one pager.”

Automation can handle most of this process today. AI agents can extract context, classify intent, and push signals into systems where work happens. Humans still add judgment, but the drudgery is already solvable. What matters is building the workflow so every piece of feedback has a clear destination and an outcome that gets logged. Aditi envisions dashboards where items move across columns labeled heard, routed, resolved, and measured, so teams can see progress rather than wonder if feedback disappeared into a void.

Voice of customer automation also demands cross-functional participation. Marketing hears one part of the story, but product, sales, operations, HR, and finance each hear their own version. Automating the flow builds a shared record of what customers are saying across silos. That way you can catch patterns early, prioritize fixes faster, and anchor decisions in customer reality instead of gut instinct.

Key takeaway: Treat voice of customer like a structured pipeline, not a loose collection of quotes. Break it into five stages (capture, tag, route, track, activate) and use AI agents to automate 70 to 80 percent of the work. Keep humans in the loop for judgment and prioritization. When every function contributes and the loop is closed, customer feedback stops being noise and starts becoming an operating system for better decisions.

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Voice of Customer Martech Examples

Automation only matters when it clears bottlenecks that marketers feel every day. Keyword research is a prime example. Teams slog through endless clusters of terms, second-guessing intent, and manually drafting briefs that rarely scale. Aditi put BrightEdge in place to kill that grind. Its automation pulls from real search data and site behavior, then produces content briefs that map directly to what audiences are looking for. Instead of starting from a blank page, her team starts from structured recommendations that actually reflect demand.

“We are using BrightEdge to automate content briefings, which was earlier a very manual process,” Aditi said.

BrightEdge briefs do not sit in a vacuum. They feed into QA workflows and connect with Microsoft Copilot to generate drafts that move into the CMS. That cycle matters. It creates a closed loop where data informs briefs, briefs drive content, and performance flows back to sharpen the next round. It is a rare example of automation that makes both the SEO team and the content team faster.

Another overlooked pain point is capturing and reusing customer proof. That is where UserEvidence comes in. They built a platform that pulls feedback from surveys, review sites like G2, and existing testimonials. Instead of dumping it into a spreadsheet that no one reads, the platform automatically surfaces the best quotes and transforms them into ready-to-use marketing assets. You can drop them on the website, push them into sales decks, or share them across social. It turns customer voice into a renewable asset instead of a buried dataset.

Aditi also pointed to predictive modeling with 6sense as a way to expand pipeline. Their model flagged ICP lookalikes already in-market that the sales team had missed. Those accounts went straight into Salesforce, nurtured in Eloqua, and activated in ad campaigns. The payoff was not more noise but more qualified accounts with real intent. When automation shows you where to focus, revenue follows.

Key takeaway: Tools like BrightEdge and UserEvidence win because they attack high-friction work. BrightEdge automates keyword research and content briefs so you can produce market-relevant content without the manual drag. UserEvidence converts customer feedback into polished assets that flow across your stack. Add predictive modeling into the mix, and you have a toolkit that saves time, surfaces opportunities, and fuels revenue. The throughline is simple: pick automations that collapse busywork and deliver outputs your team can actually use.

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How to Use Rapid Response Teams in Marketing Ops

Aditi describes a rapid response process that trims away the bureaucracy most ops teams get stuck in. Instead of routing tickets across systems and waiting for approvals, she sets up a single Teams channel where every relevant player sits together. Field marketers, digital specialists, inside sales reps, and MDRs all watch the same feed. Any inquiry—from a live webinar comment to a form fill on the website—drops in immediately. The group then asks one question: who owns this right now? That simple setup cuts resolution time from days to minutes.

One example stood out. During a LinkedIn Live session, a prospect messaged that they could not find product information. The request landed in the shared channel and within five minutes someone had responded with the exact resource. What would normally linger in a queue became a near real-time customer win. Those quick responses leave customers feeling acknowledged and employees feeling confident that their system actually works.

“It needs to start simple. Like for us, it’s literally one channel where everyone jumps in. And because it’s visible, people feel accountable to respond quickly.”

The effectiveness comes from visibility. Every request is public. Everyone in the channel knows who is accountable. That visibility creates a subtle form of social pressure, and no one wants to be the person leaving a request unanswered while their peers watch. Over time, this shared space builds new habits. Instead of asking, “Where should I send this?” people automatically know that the channel is the first stop. Common requests, like RFP templates or employer verifications, start to surface repeatedly, and that is when AI can step in to cluster them, summarize patterns, and feed intelligence back into the team.

Rapid response channels thrive when they combine three elements. Speed ensures the customer feels urgency from your side. Visibility ensures nothing slips into a black hole. Ownership ensures that someone always claims the task. When those three forces work together, the process feels human and responsive instead of corporate and slow.

Key takeaway: Build a rapid response system that creates speed, visibility, and ownership. Start with one shared channel where every request is public and accountability is visible. That way you can resolve issues in minutes, strengthen trust with customers, and build a culture where fast action becomes the default. Once that muscle is strong, bring in AI to spot patterns and share learnings across functions without losing the immediacy that makes it work.

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Building Customer Obsession Into Marketing Culture

Every marketing brief competes for resources, and the ones that actually get traction usually share a common trait. They begin with a sharp articulation of the customer problem. Aditi called this a culture change, a discipline she has been pushing across her teams. No proposal gets greenlit until it answers the question of why it matters to the customer and what need it addresses. That discipline changes the rhythm of a company, because it forces teams to resist the urge to chase shiny ideas and instead prove their relevance to the people they serve.

“Every meeting, every proposal has to start with a why. What is the customer insight that is driving this?”

To make this stick, Aditi put structural programs in place. The most impactful is the Digital Customer Experience Council, a monthly standup that brings together product, CX, marketing, and GTM leaders. The agenda focuses on customer themes, not vanity dashboards. When product teams discuss unification programs, marketing gets context to shape campaigns. When CX flags recurring pain points, GTM sees data that can inform competitive strategies. These conversations create natural cross-pollination, and they ensure that campaigns are built from customer reality rather than internal speculation.

Aditi also insisted on a symbolic but powerful change. Every deck, from strategy updates to CEO presentations, must open with a slide dedicated to customer insight. That slide can include research themes, customer quotes, or support patterns. The point is not to check a box, but to hardwire a behavior. When leaders consistently see customer context on the first page, it sets an expectation that the conversation will be grounded in real needs. Over time, repetition makes it part of the company’s operating rhythm.

Cultural rewiring takes patience, and Aditi admitted it is hard work. Yet the companies that pull it off create a different kind of discipline. They treat customer obsession as a muscle built through repeated practice. Each meeting, each brief, and each council session becomes a rep. Over time, the organization shifts from slogans about customer focus to living proof that customer problems define the agenda.

Key takeaway: Build a customer-first culture through practice, not promises. Start every proposal with a clear customer problem. Create cross-functional councils to share customer themes that different teams can act on. Require every deck to open with customer context so that leaders stay anchored to real needs. Culture changes through repetition, and customer insight must become the default entry point for every idea.

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Why Voice of Customer Works Differently in B2B and B2C

Voice of customer looks completely different when you compare consumer markets with enterprise sales. In B2C, feedback loops run fast. Teams rely on store visits, ride-alongs, social scraping, and unfiltered calls with buyers. The inputs are messy and anecdotal, but the immediacy makes the signals powerful. In B2B, feedback channels are structured. Advisory boards, win-loss reviews, and quarterly business reviews take center stage. The process moves slower, carries higher stakes, and tends to filter out raw emotion.

Consumer brands build credibility because they respond in public. Someone complains on social media, and strong B2C players post an update, fix the issue, and close the loop where everyone can see it. Enterprise companies rarely create this level of transparency. Unless the account is among the top tier, feedback often disappears into a ticket queue. Aditi believes B2B leaders need to lean into more visible “we heard you” moments to show that feedback has a direct connection to product or service changes.

“B2B should be adopting a lot of visible ‘we heard you’ moments across channels,” Aditi explained. “Show people that feedback from a ticket or a QBR actually drove action.”

Messaging highlights another divide. Aditi recalls working in automotive lubricants and realizing that if a mechanic at a garage could not repeat the product’s value back in plain words, the product would fail in the market. B2B teams often drown their value propositions in jargon and context, which creates confusion. Clarity drives adoption. A simple way to pressure test messaging is to ask customers to repeat it. If their version does not match yours, the message needs revision.

Each model carries lessons worth stealing. B2C thrives on proximity to real human reactions, while B2B has discipline in operationalizing customer feedback into roadmaps and strategy. Companies that combine both strengths move faster and scale with more confidence. Fast signals give teams urgency, and operationalized systems give those signals staying power.

Key takeaway: Treat voice of customer as a visible practice, not a buried report. Publicly close feedback loops so customers see their input reflected in change. Pressure test your messaging until customers can repeat it back in simple language. Combine the scrappy listening habits of B2C with the disciplined integration of B2B, and you create an engine that both earns trust in the short term and drives strategy over the long term.

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Why Life Integration Works Better Than Work Life Balance

Happiness in demanding roles often gets boiled down into productivity hacks or overused buzzwords. Aditi reduces it to one clear measure: the energy you feel when you wake up. If you start the day with excitement for what is ahead, your system is working. If you do not, then something in your setup needs rethinking.

Her framework is life integration. Work, family, community, and personal growth operate as a single unit. They overlap constantly, so she chooses to treat them as interconnected parts of one life. That choice gives her a better way to measure progress. She looks at whether she is adding value in different areas—at work, at home, in her community, and in her own growth—rather than chasing an abstract sense of balance.

“I don’t believe in work life happiness. I think there needs to be integration of the different aspects of your life, work, life, community, personal, family.”

This perspective forces a shift in how you check in with yourself. Instead of aiming for balance between separate worlds, you evaluate energy and value across all of them. The metric is whether you feel energized to handle both the global strategy meeting and the sprint after your toddler. That daily sense check is more reliable than waiting for some mythical balance that never arrives.

Her outlook also calls out an uncomfortable truth: life integration is messy, and that is the point. You cannot chase toddlers, lead teams, build community, and expect things to stay in neat compartments. The chaos itself can be energizing if you frame it as integration rather than interruption.

Key takeaway: Life integration works because it gives you one practical test for happiness: do you wake up energized to engage with all parts of your life? Use that check to measure whether your energy is flowing into the right places. When you feel drained, reconfigure the mix of work, family, and personal commitments until the answer tilts back to yes. This mindset provides a daily system you can trust without waiting for balance that never arrives.

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Episode Recap

Aditi built her career on something deceptively simple: listening to customers. Early on she spent hours with retailers and mechanics, filling notebooks with raw language that shaped her campaigns years later. She argues that even five thoughtful conversations can change how you read data, because the words people use sharpen context in ways numbers cannot.

She looks for signals in places marketers often overlook. Product usage trails expose hesitation points. Reddit and community chatter carry blunt honesty. Sales recordings catch the first misunderstandings that can derail positioning. Event conversations provide unfiltered market sentiment that rarely shows up in a report. Together these inputs form a fuller picture of what customers actually think and feel.

Feedback only creates impact if it moves. Aditi treats it like a pipeline: capture, tag, route, track, activate. AI can handle the grunt work, but humans still decide priorities. Tools like BrightEdge and UserEvidence show the payoff of this structure. BrightEdge automates content briefs based on real demand, while UserEvidence turns customer quotes into ready-to-use assets for sales and marketing. These automations collapse the drag work and give teams usable outputs.

Culture makes the system stick. Aditi set up rapid response channels where every request lands in front of the right people, cutting resolution time from days to minutes. She requires proposals to start with a clear customer problem and built councils where CX, product, and GTM leaders align on customer themes. Even decks open with a dedicated slide to insight. Repetition hardwires the behavior until customer focus becomes the operating rhythm.

B2C and B2B run at different speeds, but both carry lessons. Consumer markets thrive on immediacy, while enterprise teams excel at operationalizing feedback. Companies that blend those habits (fast signals with disciplined follow-through) earn trust and build strategies anchored in reality.

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Intro music by Wowa via Unminus
Cover art created with Midjourney (check out how)

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