Episodios

  • 200: Matthew Castino: How Canva measures marketing

    200: Matthew Castino: How Canva measures marketing
    Dec 16 2025
    What’s up everyone, today we have the pleasure of sitting down with Matthew Castino, Marketing Measurement Science Lead @ Canva.(00:00) - Intro (01:10) - In This Episode (03:50) - Canva’s Prioritization System for Marketing Experiments (11:26) - What Happened When Canva Turned Off Branded Search (18:48) - Structuring Global Measurement Teams for Local Decision Making (24:32) - How Canva Integrates Marketing Measurement Into Company Forecasting (31:58) - Using MMM Scenario Tools To Align Finance And Marketing (37:05) - Why Multi Touch Attribution Still Matters at Canva (42:42) - How Canva Builds Feedback Loops Between MMM and Experiments (46:44) - Canva’s AI Workflow Automation for Geo Experiments (51:31) - Why Strong Coworker Relationships Improve Career SatisfactionSummary: Canva operates at a scale where every marketing decision carries huge weight, and Matt leads the measurement function that keeps those decisions grounded in science. He leans on experiments to challenge assumptions that models inflate. As the company grew, he reshaped measurement so centralized models stayed steady while embedded data scientists guided decisions locally, and he built one forecasting engine that finance and marketing can trust together. He keeps multi touch attribution in play because user behavior exposes patterns MMM misses, and he treats disagreements between methods as signals worth examining. AI removes the bottlenecks around geo tests, data questions, and creative tagging, giving his team space to focus on evidence instead of logistics. About MatthewMatthew Castino blends psychology, statistics, and marketing intuition in a way that feels almost unfair. With a PhD in Psychology and a career spent building measurement systems that actually work, he’s now the Marketing Measurement Science Lead at Canva, where he turns sprawling datasets and ambitious growth questions into evidence that teams can trust.His path winds through academia, health research, and the high-tempo world of sports trading. At UNSW, Matt taught psychology and statistics while contributing to research at CHETRE. At Tabcorp, he moved through roles in customer profiling, risk systems, and US/domestic sports trading; spaces where every model, every assumption, and every decision meets real consequences fast. Those years sharpened his sense for what signal looks like in a messy environment.Matt lives in Australia and remains endlessly curious about how people think, how markets behave, and why measurement keeps getting harder, and more fun.Canva’s Prioritization System for Marketing ExperimentsCanva’s marketing experiments run in conditions that rarely resemble the clean, product controlled environment that most tech companies love to romanticize. Matthew works in markets filled with messy signals, country level quirks, channel specific behaviors, and creative that behaves differently depending on the audience. Canva built a world class experimentation platform for product, but none of that machinery helps when teams need to run geo tests or channel experiments across markets that function on completely different rhythms. Marketing had to build its own tooling, and Matthew treats that reality with a mix of respect and practicality.His team relies on a prioritization system grounded in two concrete variables.SpendUncertaintyLarge budgets demand measurement rigor because wasted dollars compound across millions of impressions. Matthew cares about placing the most reliable experiments behind the markets and channels with the biggest financial commitments. He pairs that with a very sober evaluation of uncertainty. His team pulls signals from MMM models, platform lift tests, creative engagement, and confidence intervals. They pay special attention to MMM intervals that expand beyond comfortable ranges, especially when historical spend has not varied enough for the model to learn. He reads weak creative engagement as a warning sign because poor engagement usually drags efficiency down even before the attribution questions show up.“We try to figure out where the most money is spent in the most uncertain way.”The next challenge sits in the structure of the team. Matthew ran experimentation globally from a centralized group for years, and that model made sense when the company footprint was narrower. Canva now operates in regions where creative norms differ sharply, and local teams want more authority to respond to market dynamics in real time. Matthew sees that centralization slows everything once the company reaches global scale. He pushes for embedded data scientists who sit inside each region, work directly with marketers, and build market specific experimentation roadmaps that reflect local context. That way experimentation becomes a partner to strategy instead of a bottleneck.Matthew avoids building a tower of approvals because heavy process often suffocates marketing momentum. He prefers a model where teams follow shared principles, ...
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    56 m
  • 199: Anna Aubuchon: Moving BI workloads into LLMs and using AI to build what you used to buy

    199: Anna Aubuchon: Moving BI workloads into LLMs and using AI to build what you used to buy
    Dec 9 2025
    What’s up everyone, today we have the pleasure of sitting down with Anna Aubuchon, VP of Operations at Civic Technologies.(00:00) - Intro (01:15) - In This Episode (04:15) - How AI Flipped the Build Versus Buy Decision (07:13) - Redrawing What “Complex” Means (12:20) - Why In House AI Provides Better Economics And Control (15:33) - How to Treat AI as an Insourcing Engine (21:02) - Moving BI Workloads Out of Dashboards and Into LLMs (31:37) - Guardrails That Keep AI Querying Accurate (38:18) - Using Role Based AI Guardrails Across MCP Servers (44:43) - Ops People are Creators of Systems Rather Than Maintainers of Them (48:12) - Why Natural Language AI Lowers the Barrier for First-Time Builders (52:31) - Technical Literacy Requirements for Next Generation Operators (56:46) - Why Creative Practice Strengthens Operational LeadershipSummary: AI has reshaped how operators work, and Anna lays out that shift with the clarity of someone who has rebuilt real systems under pressure. She breaks down how old build versus buy habits hold teams back, how yearly AI contracts quietly drain momentum, and how modern integrations let operators assemble powerful workflows without engineering bottlenecks. She contrasts scattered one-off AI tools with the speed that comes from shared patterns that spread across teams. Her biggest story lands hard. Civic replaced slow dashboards and long queues with orchestration that pulls every system into one conversational layer, letting people get answers in minutes instead of mornings. That speed created nerves around sensitive identity data, but tight guardrails kept the team safe without slowing anything down. Anna ends by pushing operators to think like system designers, not tool babysitters, and to build with the same clarity her daughter uses when she describes exactly what she wants and watches the system take shape.About AnnaAnna Aubuchon is an operations executive with 15+ years building and scaling teams across fintech, blockchain, and AI. As VP of Operations at Civic Technologies, she oversees support, sales, business operations, product operations, and analytics, anchoring the company’s growth and performance systems.She has led blockchain operations since 2014 and built cross-functional programs that moved companies from early-stage complexity into stable, scalable execution. Her earlier roles at Gyft and Thomson Reuters focused on commercial operations, enterprise migrations, and global team leadership, supporting revenue retention and major process modernization efforts.How AI Flipped the Build Versus Buy DecisionAI tooling has shifted so quickly that many teams are still making decisions with a playbook written for a different era. Anna explains that the build versus buy framework people lean on carries assumptions that no longer match the tool landscape. She sees operators buying AI products out of habit, even when internal builds have become faster, cheaper, and easier to maintain. She connects that hesitation to outdated mental models rather than actual technical blockers.AI platforms keep rolling out features that shrink the amount of engineering needed to assemble sophisticated workflows. Anna names the layers that changed this dynamic. System integrations through MCP act as glue for data movement. Tools like n8n and Lindy give ops teams workflow automation without needing to file tickets. Then ChatGPT Agents and Cloud Skills launched with prebuilt capabilities that behave like Lego pieces for internal systems. Direct LLM access removed the fear around infrastructure that used to intimidate nontechnical teams. She describes the overall effect as a compression of technical overhead that once justified buying expensive tools.She uses Civic’s analytics stack to illustrate how she thinks about the decision. Analytics drives the company’s ability to answer questions quickly, and modern integrations kept the build path light. Her team built the system because it reinforced a core competency. She compares that with an AI support bot that would need to handle very different audiences with changing expectations across multiple channels. She describes that work as high domain complexity that demands constant tuning, and the build cost would outweigh the value. Her team bought that piece. She grounds everything in two filters that guide her decisions: core competency and domain complexity.Anna also calls out a cultural pattern that slows AI adoption. Teams buy AI tools individually and create isolated pockets of automation. She wants teams to treat AI workflows as shared assets. She sees momentum building when one group experiments with a workflow and others borrow, extend, or remix it. She believes this turns AI adoption into a group habit rather than scattered personal experiments. She highlights the value of shared patterns because they create a repeatable way for teams to test ideas without rebuilding from scratch.She closes by urging operators to update their ...
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    1 h
  • 198: Pam Boiros: 10 Ways to support women and build more inclusive AI

    198: Pam Boiros: 10 Ways to support women and build more inclusive AI
    Dec 2 2025
    What’s up everyone, today we have the pleasure of sitting down with Pam Boiros, Fractional CMO and Marketing advisor, and Co-Founder Women Applying AI.(00:00) - Intro (01:13) - In This Episode (03:49) - How To Audit Data Fingerprints For AI Bias In Marketing (07:39) - Why Emotional Intelligence Improves AI Prompting Quality (10:14) - Why So Many Women Hesitate (15:40) - Why Collaborative AI Practice Builds Confidence In Marketing Ops Teams (18:31) - How to Go From AI Curious to AI Confident (24:32) - Joining The 'Women Applying AI' Community (27:18) - Other Ways to Support Women in AI (28:06) - Role Models and Visibility (32:55) - Leadership’s Role in Inclusion (35:57) - Mentorship for the AI Era (38:15) - Why Story Driven Communities Strengthen AI Adoption for Women (42:17) - AI’s Role in Women’s Worklife Harmony (45:22) - Why Personal History Strengthens Creative LeadershipSummary: Pam delivers a clear, grounded look at how women learn and lead with AI, moving from biased datasets to late-night practice sessions inside Women Applying AI. She brings sharp examples from real teams, highlights the quiet builders shaping change, and roots her perspective in the resilience she learned from the women in her own family. If you want a straightforward view of what practical, human-centered AI adoption actually looks like, this episode is worth your time.About PamPam Boiros is a consultant who helps marketing teams find direction and build plans that feel doable. She leads Marketing AI Jump Start and works as a fractional CMO for clients like Reclaim Health, giving teams practical ways to bring AI into their day-to-day work. She’s also a founding member of Women Applying AI, a new community that launched in Sep 2025 that creates a supportive space for women to learn AI together and grow their confidence in the field.Earlier in her career, Pam spent 12 years at a fast-growing startup that Skillsoft later acquired, then stepped into senior marketing and product leadership there for another three and a half years. That blend of startup pace and enterprise structure shapes how she guides her clients today.How To Audit Data Fingerprints For AI Bias In MarketingAI bias spreads quietly in marketing systems, and Pam treats it as a pattern problem rather than a mistake problem. She explains that models repeat whatever they have inherited from the data, and that repetition creates signals that look normal on the surface. Many teams read those signals as truth because the outputs feel familiar. Pam has watched marketing groups make confident decisions on top of datasets they never examined, and she believes this is how invisible bias gains momentum long before anyone sees the consequences.Pam describes every dataset as carrying a fingerprint. She studies that fingerprint by zooming into the structure, the gaps, and the repetition. She looks for missing groups, inflated representation, and subtle distortions baked into the source. She builds this into her workflow because she has seen how quickly a model amplifies the same dominant voices that shaped the data. She brings up real scenarios from her own career where women were labeled as edge cases in models even though they represented half the customer base. These patterns shape everything from product recommendations to retention scores, and she believes many teams never notice because the numbers look clean and objective."Every dataset has a fingerprint. You cannot see it at first glance, but it becomes obvious once you look for who is overrepresented, who is underrepresented, or who is misrepresented."Pam organizes her process into three cycles that marketers can use immediately.The habit works because it forces scrutiny at every stage, not just at kickoff.Before building, trace the data source, the people represented, and the people missing.While building, stress test the system across groups that usually sit at the margins.After launch, monitor outputs with the same rhythm you use for performance analysis.She treats these cycles as an operational discipline. She compares the scale of bias to a compounding effect, since one flawed assumption can multiply into hundreds of outputs within hours. She has seen pressure to ship faster push teams into trusting defaults, which creates the illusion of objectivity even when the system leans heavily toward one group’s behavior. She wants marketers to recognize that AI audits function like quality control, and she encourages them to build review rituals that continue as the model learns. She believes this daily maintenance protects teams from subtle drift where the model gradually leans toward the patterns it already prefers.Pam views long term monitoring as the part that matters most. She knows how fast AI systems evolve once real customers interact with them. Bias shifts as new data enters the mix. Entire segments disappear because the model interprets their silence as disengagement. Other segments dominate because ...
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    49 m
  • 197: Anna Leary: The Art of saying no and other mental health strategies in marketing ops

    197: Anna Leary: The Art of saying no and other mental health strategies in marketing ops
    Nov 25 2025
    What’s up everyone, today we have the pleasure of sitting down with Anna Leary, Director of Marketing Operations at Alma.(00:00) - Intro (01:15) - In This Episode (04:38) - How to Prevent Burnout (05:46) - What Companies Can Do Better (07:50) - Agility of Planning (08:53) - Why Saying No Strengthens Marketing Operations (13:48) - How to Decide When to Push Back (18:03) - Hill To Die On (20:03) - How to Handle Constant Pushback (29:55) - Wishlist (37:06) - How to Use Asynchronous Communication to Reduce Stress (44:24) - How To Evaluate Martech Tools Based On Real Business Impact (48:45) - Why Marketing Ops Needs Visible Work Systems (51:24) - Health Awareness (52:56) - How to Recognize and Prevent Burnout in Marketing OperationsSummary: Anna built systems to keep marketing running smoothly, but the real lesson came when those same systems failed to protect her. In this episode, she shares how saying no became her survival skill, why visibility is the antidote to burnout, and how calm structure (not constant hustle) keeps teams sharp and human. It’s a story about boundaries, balance, and learning to lead without losing yourself.About AlmaAnna Leary is the Director of Marketing Operations at Alma, where she builds scalable systems that help marketing teams work smarter. With a focus on lead flow, data architecture, and enablement, she’s known for creating centers of excellence that turn fragmented operations into cohesive, measurable programs. As a Marketo Certified Solutions Architect and Marketo Measure (Bizible) specialist, Anna brings a rare balance of technical depth and strategic clarity to every initiative she leads.Before joining Alma, Anna spent more than a decade shaping marketing operations strategies for brands like Uber, Teamwork, Sauce Labs, and Bitly. Whether optimizing attribution models or training teams to adopt new workflows, Anna’s work always centers on efficiency, empowerment, and driving impact across the full marketing ecosystem.Burnout and BalanceMarketing ops work demands constant precision. Teams juggle system integrations, data cleanups, and new tech rollouts, often all before lunch. The job requires mental endurance and a tolerance for chaos. Anna understands this well. “Everyone’s trying to be the person who knows the newest tech,” she said. “It’s hard to keep up, and that adds to the mental load.” The competition to stay relevant has turned into a quiet stress test that too many operators fail without noticing.The strange part is that ops teams often create systems designed to protect their organizations but rarely use those same systems to protect themselves. Anna explained how Service Level Agreements (SLAs) can lose their meaning when teams treat them as flexible. Urgent requests push through, exceptions pile up, and structure dissolves. Each “quick favor” chips away at the purpose of having defined processes. She put it plainly:“If we’re making an exception for everything, then we’re not respecting the process.”When teams stop respecting their own boundaries, burnout follows quickly. SLAs exist to create stability, and stability is what keeps people sane. Following process is not bureaucracy; it is protection. It gives operators time to think clearly, plan ahead, and make fewer reactive decisions. That way you can build predictability into your week instead of letting other people’s emergencies define it.Anna also shared how her team reworked its entire planning system to reduce stress. “We used to do quarterly capacity planning,” she said, “but half the projects fell apart by week four.” She scrapped the process and replaced it with smaller, rolling cycles that fit the unpredictable nature of marketing requests. For someone who identifies as Type A, letting go of that much structure felt risky, but the tradeoff was worth it. Her team now works with more energy, less anxiety, and a better sense of control.“Giving up some of that control is actually good in the end because it’s less stressful.”Her story shows how burnout prevention depends on structure that adapts. Ops professionals do their best work when their systems reflect real life, not an idealized version of it. Boundaries, planning, and discipline should support humans, not box them in.Key takeaway: Protect your team’s mental health by enforcing the systems you build. Treat SLAs as promises, not preferences. Review your planning cycles regularly and adjust them to match the actual pace of work. Stability in ops comes from building rules that people respect and structures that evolve as the business changes.The Power of NoSaying no is one of the hardest and most necessary skills in marketing operations. Every week brings a new request, a “quick fix,” or a last-minute idea that someone swears will only take five minutes. Anna treats these moments as boundary checks. They test whether her team can protect their focus without losing trust or influence across the ...
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    56 m
  • 196: Blair Bendel: The World of casino marketing and the tech that brings it to life

    196: Blair Bendel: The World of casino marketing and the tech that brings it to life
    Nov 18 2025
    What’s up everyone today we have the pleasure of chatting with Blair Bendel, Senior Vice President of Marketing at Foxwoods Resort Casino.(00:00) - Intro (00:49) - In This Episode (03:39) - Evolution of Casino Martech (06:11) - Customer Loyalty & Personalization (09:36) - Using the Right Marketing Channel for the Right Goal in Hospitality (12:38) - Foxwood’s Martech and Customer Data Migration to MoEngage (15:05) - Picking MoEngage (20:07) - Why Change Tools?? (22:46) - Implementing a New Platform (24:58) - Building Structure for 24/7/365 Casino Marketing (31:20) - Key Things to Track (33:15) - Fail Fast, Learn Faster (37:25) - Balancing Big Data with Privacy (40:23) - Why AI Will Not Fix Casino Marketing Overnight (43:23) - Exploring AI (46:59) - Human Experience Drives Long-Term Casino Revenue (49:05) - Human Side (52:12) - Why Face-to-Face Conversations Strengthen Marketing TeamsSummary: The casino floor never sleeps. Lights hum, cards shuffle, and people come not just to gamble but to feel alive. While other industries went digital overnight, casinos stayed grounded in human moments, and Blair’s mission has been to connect those experiences through smarter tech. At Foxwoods, he replaced a maze of disconnected martech with a single platform, giving his team one clear view of every guest. Push messages became quick nudges, emails carried depth, and silence built trust. In a business that runs 24/7/365, his team moves fast, learns constantly, and protects what matters most: guest privacy. About BlairBlair Bendel has spent nearly two decades shaping brands that make casinos feel alive. As SVP of Marketing at Foxwoods Resort Casino, one of the world’s largest gaming and entertainment destinations, he leads strategy across brand, digital, loyalty, and guest experience for a property owned by the Mashantucket Pequot Tribal Nation.Before Foxwoods, Blair drove marketing for Boyd Gaming and Pinnacle Entertainment, guiding multi-property teams through high-stakes launches and rebrands. Known for blending data and instinct, he’s built campaigns that turn foot traffic into fandom and moments into measurable growth.The Evolution of Casino MartechCasinos thrive on the energy of real people in real spaces. Blair has spent his career in that environment, where the hum of slot machines and the rhythm of foot traffic define success. He points out that while other industries rushed to digitize, gaming and hospitality focused on the on-property experience that drives most of their revenue. Technology in this world serves the guest standing in front of you, not a distant audience online.“There’s a lot of innovation, but it’s all centered around that customer and that on-property experience,” Blair said.Walk across a modern casino floor and you see how far that innovation has gone. Slot machines now reach twelve feet high, lit by curved screens that feel more like immersive art installations than games. Even bingo, once a paper-and-pen ritual, lives on tablets. These changes reflect more than aesthetic upgrades. They mark the blending of digital personalization with in-person entertainment. Each new machine and experience collects data, interprets patterns, and helps casinos understand what keeps players coming back.Blair sees the next phase of progress in the pairing of martech systems and artificial intelligence. Casinos have long collected data on player habits, but much of it stayed locked in isolated databases. AI now connects those dots, linking preferences, visit frequency, and loyalty activity into one living profile. That way you can predict what a guest wants before they ask for it. Personalized dining offers, targeted game promotions, or well-timed follow-up messages all become part of a continuous loop that strengthens engagement.Still, Blair focuses on the human side of this transformation. “People assume tech makes everything easier, and it doesn’t,” he said. Each new platform requires training, integration, and trust. Martech without people who know how to use it becomes clutter. Blair spends much of his time ensuring his team understands the technology deeply enough to keep the guest experience effortless. The strategy depends on teams who can think like data analysts and act like hosts.Key takeaway: Martech and AI can elevate on-property hospitality when used to deepen human connection instead of replacing it. Integrate systems that unify guest data, but prioritize training and comfort among your team. When your people trust the tools and your guests feel known, technology quietly fades into the background while loyalty takes center stage.Customer Loyalty and Personalization in Casino MarketingCasino marketing has operated on autopilot for too long. Guests still get dropped into massive segmentation buckets, treated as if their weekend habits, entertainment tastes, and spending patterns are interchangeable. Blair describes it bluntly: “We still send show offers to guests who’...
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    55 m
  • 195: Megan Kwon: How One of Canada’s largest retailers orchestrates messaging, and structures martech

    195: Megan Kwon: How One of Canada’s largest retailers orchestrates messaging, and structures martech
    Nov 11 2025
    What’s up folks, today we have the pleasure of sitting down with Megan Kwon, Director, Digital Customer Communications at Loblaw Digital.(00:00) - Intro (01:26) - In This Episode (04:11) - Building a Career Around Conversations That Scale (06:25) - Customer Journey Pods and Martech Team Structures (09:08) - Martech Team Structures (11:23) - Customer Journey Martech Pods (12:54) - How to Assign Martech Tool Ownership and Drive Real Adoption (14:54) - Martech Training and Onboarding (17:30) - How To Integrate New Martech Into Daily Habits (19:59) - Why Change Champions Work in Martech Transformation (24:11) - Change Champion Example (28:25) - How To Manage Transactional Messaging Across Multiple Brands (32:35) - Frequency and Recency Capping (35:59) - Why Shared Ownership Improves Transactional Messaging (41:50) - Why Human Governance Still Matters in AI Messaging (47:11) - Why Curiosity Matters in Adapting to AI (53:08) - Creating Sustainable Energy in Marketing LeadershipSummary: Megan leads digital customer communications at Loblaw Digital, turning enterprise-scale messaging into something that feels personal. She built her teams around the customer journey, giving each pod full creative and data ownership. The people driving results also own the tools, learning by building and celebrating small wins. Her “change champions” make new ideas stick, and her view on AI is grounded; use it to go faster, not think for you. Curiosity, she says, is what keeps marketing human.About MeganMegan Kwon runs digital customer communications at Loblaw Digital, the team behind how millions of Canadians hear from brands like Loblaws, Shoppers Drug Mart, and President’s Choice. She’s part strategist, part systems thinker, and fully obsessed with how data can make marketing feel more human, not less.Before returning to Loblaw, Megan helped reshape how people discover and trust local marketplaces at Kijiji, and before that, she built growth engines in the fintech world at NorthOne. Her career has been a study in scale; from scrappy e-commerce tests to national lifecycle programs that touch nearly every Canadian household. What sets her apart is the way she leads: with deep curiosity, radical ownership, and a bias for collaboration. She believes numbers tell stories, and that the best marketing teams build movements around insight, empathy, and accountability.Building a Career Around Conversations That ScaleRunning digital messaging at Loblaw means coordinating communication at a scale that few marketers ever experience. Megan oversees the systems that deliver millions of emails and texts across brands Canadians interact with daily, including Loblaws, Shoppers Drug Mart, and President’s Choice. Her team manages both marketing and transactional messages, making sure each one aligns with a specific stage in the customer journey. The workload is immense. Each division has its own priorities, and every campaign needs to fit within a shared infrastructure that still feels personal to the customer.“We work with a lot of different business divisions across the entire organization. Our job is to make sure their strategies and programs come to life through the customer lifecycle.”Megan’s team operates more like a connective tissue than a broadcast engine. They bridge the gaps between marketing, product, and data teams, translating disconnected strategies into a unified experience. That work involves building systems capable of:Managing multiple brand voices while keeping messaging consistentTriggering real-time communications that respond to customer behaviorIntegrating old and new technologies without breaking operational flowEvery campaign becomes part of a continuous conversation with the customer. Each message is one step in a long dialogue, not a one-off announcement.Megan’s perspective comes from experience earned in very different industries. She began her career at Loblaw during the early days of online grocery, a time when digital operations were experimental and resourceful. She later worked across fintech, marketplaces, and paid media before returning to Loblaw. That journey helped her understand every layer of the customer funnel, from acquisition through retention. It also taught her how to combine growth marketing tactics with enterprise-level communication systems, that way she can scale personalization without losing humanity.Most large organizations still treat messaging as a collection of isolated programs. Megan treats it as an ecosystem. Her work shows that when lifecycle and acquisition efforts operate within a shared framework, communication becomes more coherent and far more effective. Alignment between data, channels, and teams reduces noise and builds trust with customers who engage across multiple brands.Key takeaway: Building a unified messaging ecosystem starts with structure, not volume. Create systems that connect channels, data, and brand voices into one coordinated experience. Treat...
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    55 m
  • 194: Jane Menyo: How Gong democratized customer proof with AI research and standardized prompts

    194: Jane Menyo: How Gong democratized customer proof with AI research and standardized prompts
    Nov 4 2025
    What’s up everyone today we have the pleasure of sitting down with Jane Menyo, Sr. Director, Solutions & Customer Marketing @ Gong.(00:00) - Jane-audio (01:01) - In This Episode (04:43) - How Solutions Marketing Turns Customer Insights Into Strategy (09:22) - Using AI to Mine Real Customer Intelligence from Conversations (13:18) - Why Stitching Research Sequences Works in Customer Marketing (17:09) - Using AI Trackers to Uncover Buyer Behavior in Sales Conversations (23:21) - How Standardized Prompts Improve Sales Enablement Systems (29:43) - Building Messaging Systems That Scale Across Industries (34:15) - How Gong’s Research Assistant Slack Bot Delivers Instant Customer Proof (38:26) - Avoiding Mediocre AI Marketing Research (43:42) - Why Customer Proof Outperforms AI-Generated Marketing (45:41) - Why Rest Strengthens Creative Output in MarketingSummary: Jane built her marketing practice around listening. At Gong, she turned raw customer conversations into a live feedback system that connects sales calls, product strategy, and messaging in real time. Her team uses AI to surface patterns from the field and feed them back into content that actually reflects how people buy. She runs on curiosity and recovery, finding her best ideas mid-run. In a world obsessed with producing more, Jane’s work reminds marketers to listen better. The smartest strategies start in the quiet moments when someone finally hears what the customer’s been saying all along.About JaneJane Menyo leads Solutions and Customer Marketing at Gong, where she’s known for fusing strategy with storytelling to turn customers into true advocates. She built Gong’s customer marketing engine from the ground up, scaling programs that drive adoption, retention, and community impact across the company’s revenue intelligence ecosystem.Before Gong, Jane led customer and solutions marketing at ON24, where she developed go-to-market playbooks and launched large-scale advocacy initiatives that connected customer voice to product innovation. Earlier in her career, she helped shape demand generation and brand strategy at Comprehend Systems (a Y Combinator and Sequoia-backed life sciences startup) laying the operational groundwork that fueled growth.A former NCAA All-American and U.S. Olympic Trials contender, Jane brings a rare blend of discipline, creativity, and competitive energy to her leadership. Her approach to marketing is grounded in empathy and powered by data; a balance that turns customer stories into growth engines.How Solutions Marketing Turns Customer Insights Into StrategyJane’s role at Gong evolved from building customer advocacy programs to leading both customer and solutions marketing. What began as storytelling and adoption work expanded into shaping how Gong positions its products for different personas and industries. The shift moved her from celebrating customer wins to architecting how those wins inform the company’s broader go-to-market strategy.Persona marketing only works when it goes beyond demographics and titles. Jane treats it as an operational system that connects customer understanding with product truth. Her team studies how real people use Gong, where they get stuck, what outcomes they care about, and how their teams actually make buying decisions. Those details guide every message Gong sends into the market. It is a constant feedback loop that keeps the company close to how customers think and work.Her solutions marketing team functions like a mirror to product marketing. Product marketers focus on what the product can do, while Jane’s team translates that into why it matters to specific audiences. They do not write from feature lists. They write from the field. When a sales manager spends half her day in Gong but still struggles to coach reps efficiently, Jane’s team crafts stories and materials that speak directly to that pain. The goal is to make every communication feel like it was written from inside the customer’s daily workflow.“Our work is about meeting customers where they are and helping them get to outcomes faster,” Jane said.That perspective only works when every team in the company has equal access to the customer’s voice. Gong’s own technology makes that possible. Conversations, feedback, and usage patterns are captured and shared automatically, so customer knowledge is no longer limited to those on the front lines. Jane’s group uses that visibility to deepen persona profiles, test new positioning, and identify emerging trends before they reach scale. It makes the company more responsive and keeps messaging grounded in real behavior instead of assumption.For anyone building customer marketing systems, the lesson is practical. Treat persona development as a live system, not a static report. Use customer data to update your understanding regularly. Create tools that let everyone in your company hear what customers say in their own words. That way you can write content, sales ...
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    53 m
  • 193: David Joosten: The Politics and architecture of martech transformation

    193: David Joosten: The Politics and architecture of martech transformation
    Oct 28 2025
    What’s up everyone, today we have the pleasure of sitting down with David Joosten, Co-Founder and President at GrowthLoop and the co-author of ‘First-Party Data Activation’.(00:00) - Intro (01:02) - In This Episode (03:47) - Earning The Right To Transform Martech (08:17) - Why Internal Roadshows Make Martech Wins Stick (10:52) - Architecture Shapes How Teams Move and What They Believe (16:25) - Bring Order to Customer Data With the Medallion Framework (21:33) - The Real Enemy of Martech is Fragmented Data (28:39) - Stop Calling Your CRM the Source of Truth (34:47) - Building the Tech Stack People Rally Behind (38:18) - Why Most CDP Failures Start With Organizational Misalignment (44:18) - Why Tough Conversations Strengthen Lifecycle Marketing (55:15) - Why Experimentation Culture Strengthens Martech Leadership (01:00:00) - How to Use a North Star to Stay Focused in LeadershipSummary: David learned that martech transformation begins with proof people can feel. Early in his career, he built immaculate systems that looked impressive but delivered nothing real. Everything changed when a VP asked him to show progress instead of idealistic roadmaps. From that moment, David focused on momentum and quick wins. Those early victories turned into stories that spread across the company and built trust naturally. Architecture became his silent advantage, shaping how teams worked together and how confidently they moved. About DavidDavid is the co-founder of GrowthLoop, a composable customer data platform that helps marketers connect insights to action across every channel. He previously worked at Google, where he led global marketing programs and helped launch the Nexus 5 smartphone. Over the years, he has guided teams at Indeed, Priceline, and Google in building first-party data strategies that drive clarity, collaboration, and measurable growth.He is the co-author of First-Party Data Activation: Modernize Your Marketing Data Platform, a practical guide for marketers who want to understand their customers through direct, consent-based interactions. David helps teams move faster by removing data friction and building marketing systems that adapt through experimentation. His work brings energy and empathy to the challenge of modernizing data-driven marketing.Earning The Right To Transform MartechEvery marketing data project starts with ambition. Teams dream of unified dashboards, connected pipelines, and a flawless single source of truth. Then the build begins, and progress slows to a crawl. David remembers one project vividly. His team at GrowthLoop had connected more than 200 data fields for a global tech company, yet every new campaign still needed more. The setup looked impressive, but nothing meaningful was shipping.“We spent quarters building the perfect setup,” David said. “Then the VP of marketing called me and said, ‘Where are my quick wins?’”That question changed his thinking. The VP wasn’t asking for reports or architecture diagrams. He wanted visible proof that the investment was worth it. He needed early wins he could show to leadership to keep momentum alive. David realized that transformation happens through demonstration, not design. Theoretical perfection means little when no one in marketing can point to progress.From then on, he started aiming for traction over theory. That meant focusing on use cases that delivered impact quickly. He looked for under-supported teams that were hungry to try new tools, small markets that moved fast, and forgotten product lines desperate for attention. Those early adopters created visible success stories. Their enthusiasm turned into social proof that carried the project forward.Momentum built through results is what earns the right to transform. When others in the organization see evidence of progress, they stop questioning the system and start asking how to join it.Key takeaway: Martech transformations thrive on proof, not perfection. Target high-energy teams where quick wins are possible, deliver tangible outcomes fast, and use that momentum to secure organizational buy-in. Transformation is granted to those who prove it works, one visible success at a time.Why Internal Roadshows Make Martech Wins StickAn early martech win can disappear as quickly as it arrives. A shiny dashboard, a clean sync, or a new workflow can fade into noise unless you turn it into something bigger. David explains that the real work begins when you move beyond Slack celebrations and start building visibility across the company. The most effective teams bring their success to where influence actually happens. They show up in weekly leadership meetings for sales, data, and marketing, and they connect their progress to the company’s larger mission. That connection transforms an isolated result into shared purpose.“If you can get invited to those regular meetings and actually tie the win back to the larger vision, you’ll bring people along in a much bigger way,” ...
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