Humans of Martech

Summary: Tobi challenged marketing’s fixation on prediction. He has built highly accurate LTV models, but accuracy alone does not move revenue. Marketing is intervention. Correlation shows patterns; causality tells you what happens when you pull a lever. That shift reshapes experimentation, explains why dynamic allocation can outperform static A B tests, and highlights how self learning systems can backfire or get stuck in local maxima. It also fuels his skepticism of unleashing agentic AI on historical data without a causal layer. If you want to change outcomes instead of forecast them, your systems need to understand levers and log decisions you can actually audit.(00:00) - Intro (01:22) - In This Episode (04:07) - Why Predictive Models Fail Without Causal Inference (09:49) - How to Validate Causal Impact on Customer Lifetime Value (13:04) - Reducing Uncertainty Around Causal Effects by Optimizing Levers, Not Labels (17:01) - Why Dynamic Allocation Works Better Than Fixed Horizon A B Testing (31:54) - The Boomerang Effect and Why Uninformed AI Sabotages Early Results (40:15) - Escaping Local Maxima and The Failure of Randomly Initialized Decisioning (44:04) - Why Agentic AI Trained on Data Warehouse Correlations Reinforces Bias (49:00) - The Power of Composable Decisioning (53:06) - How Machine Decisioning Transcends Marketing (01:01:41) - Why Clear Priority Hierarchies Improve Executive Decision Making About TobiasTobias Konitzer, PhD is VP of AI at GrowthLoop, where he’s chasing closed-loop marketing powered by reinforcement learning, causality, and agentic systems. He’s spent the past decade focused on one core problem: moving beyond prediction to actually influencing outcomes.Previously, Tobi was Chief Innovation Officer at Fenix Commerce, helping major eCommerce brands modernize checkout and delivery with machine learning. He also founded Ocurate, a venture-backed startup that predicted customer lifetime value to optimize ad bidding in real time, raising $5.5M and scaling to $500K+ ARR before its acquisition. Earlier, he co-founded PredictWise, building psychographic and behavioral targeting models that drove over $2M in revenue.Tobi earned his PhD in Computational Social Science from Stanford and worked at Facebook Research on large-scale ML and bias correction. Originally from Germany and based in the Bay Area since 2013, he writes frequently about causal thinking, machine decisioning, and the future of marketing.Why Predictive Models Fail Without Causal InferencePrediction dominates most marketing roadmaps. Teams invest months refining churn models, tightening confidence intervals, and debating which threshold deserves a campaign. Tobi built an entire company on that logic. His team produced highly accurate lifetime value predictions using deep learning and granular event data. The forecasts were sharp. The lift curves were clean. Buyers were impressed.Then lifecycle marketers asked a more uncomfortable question: what action should follow the score?A predictive model encodes the current trajectory of a customer under existing policies. It describes what will likely happen if nothing changes. Marketing changes things constantly. The moment you intervene, you alter the system that generated the prediction. The forecast reflects yesterday’s conditions, not tomorrow’s strategy.> “Prediction tells you the future if you do nothing. Causation tells you how to change it.”Consider the Prediction Trap.On the left, the status quo labels a person as high churn risk. The function is observation. The outcome is a description of what happens if you leave the system untouched. On the right, a lever gets pulled. The function is intervention. The outcome is directional change.That shift in function changes how you work.Prediction thinking centers on segmentation:Who is likely to churn?Who is likely to buy?Who looks like high LTV?Causal thinking centers on levers:Which incentive reduces churn?Which sequence increases repeat purchase?Which offer raises lifetime value incrementally?Tobi often uses an LTV example to expose the trap. Suppose high LTV customers frequently viewed a specific product early in their journey. A team might redesign the onboarding flow to feature that product more aggressively. The correlation looks persuasive. The causal effect remains unknown.Several alternative explanations could drive the pattern:The product may correlate with a specific acquisition channel.The product may have been highlighted during a limited campaign.The product view may signal prior brand familiarity.Only an intervention test can estimate incremental impact. Correlation can guide hypothesis generation, but it cannot validate the lever itself.Tobi also highlights a deeper issue. Acting on predictions introduces compounding uncertainty across multiple layers:The predictive model carries statistical variance.The translation from model features to campaign strategy introduces interpretation bias.The experiment introduces sampling error.Execution introduces operational noise.Each layer adds variability. When teams treat prediction accuracy as the goal, they lose visibility into where uncertainty enters the system. When teams focus on intervention impact, they concentrate measurement on the lever that drives revenue.Boardrooms already operate in causal language. Incremental ROI is causal. Budget allocation is causal. Executives care about what caused growth, not which segment looked promising in a dashboard. Prediction can inform prioritization. Causal inference determines what to scale.If you want to move in that direction, adjust your operating model:Start every initiative with a controllable lever.Define the action before defining the segment.Design experiments that isolate the incremental effect of that lever.Randomized or adaptive allocation both estimate causal lift.Report impact in revenue, retention, or contribution margin.Tie every experiment to a business outcome.Document assumptions and uncertainty.Build institutional memory around what caused change.Prediction remains useful. Intervention drives growth. Teams that understand that distinction build systems that learn through action instead of watching the future unfold from the sidelines.Key takeaway: Anchor your marketing engine in causal experiments. For every predictive score, define the specific action it informs, test that action against a control, and quantify incremental lift tied directly to revenue or retention. Replace segment rankings with lever performance dashboards that show effect size, confidence, and business impact. When every campaign answers the question “What did this intervention cause?” your team shifts from observing trajectories to shaping them.How to Validate Causal Impact on Customer Lifetime ValueMost teams treat high LTV segments as proof of where to spend. The model ranks customers. The top decile looks profitable. Budget flows upward. Tobi described asking the head of CRM at a billion dollar outdoor brand what he does when a model predicts someone will be high LTV. The answer came instantly: Spend more on them, no?That instinct feels responsible. It also confuses observation with intervention. Introducing the high LTV Fallacy:On the right side of the chart, you see a dense cluster labeled high LTV customers. Revenue increases with marketing spend. The correlation line slopes upward. It looks clean and convincing. They were going to buy anyway. That cluster may represent customers with higher income, stronger brand affinit...

Jenna Kellner, VP of Marketing at Workleap and revenue-focused leader known for scaling teams and tackling tech debt. She discusses messy “Frankenstein” stacks and why leaders must reinvest in core systems. She covers decision-making with imperfect data, building AI confidence via small experiments, and why first principles and close execution drive better business judgment.

Ronald Gaines, a marketing ops and digital transformation leader who builds scalable revenue engines, shares six practical lessons for emerging ops leaders. He discusses leading without formal authority, defining your role proactively, treating ops like product work, enforcing data discipline, and using intake systems to protect team capacity.

Maria Solodilova, Head of Business Development at Yango Ads and adtech leader in mobile mediation and programmatic monetization. She maps adtech as a live marketplace, explains how SDKs, auctions, and supply dynamics turn app attention into revenue. She also covers AI’s practical roles, programmatic inventory behavior, and why transparency and timing shape publisher earnings.

Anthony Rotio, Chief Data Strategy Officer at GrowthLoop and former AB InBev marketing leader with a computer science background. He walks through moving from robotics to marketing systems and why broken feedback loops stall learning. He outlines agent context graphs for causal simulation and drift detection. The conversation also covers retail media networks, governed first-party data, and agent-to-agent commerce shaping automated marketing.

"Hey – So what do you do?” Why is it that we always default to work when we get this question. its like many of us have let our jobs become the center of how we see ourselves. This slowly happens to many of us, as work occupies more mental and emotional space.I asked 50 people in martech and operations how they stay happy under sustained pressure. This 3 part series – titled “50 Operators share the systems that keep them happy” explores each of these layers through the lived experience of operators who feel the same pressure you probably feel right now.Today we close out the series with part 3: meaning. We’ll hear from 19 people and we’ll cover:(00:00) - Teaser (01:08) - Intro / In This Episode (04:27) - Rich Waldron: Auditing Whether Work Is Actually Moving (06:49) - Samia Syed: Tracking Personal Growth (08:33) - Jonathan Kazarian: Tracking Growth Across Life Health and Work (10:11) - Kim Hacker: Choosing Roles With Daily Visible Impact (12:21) - Mac Reddin: Checking Work Against 3 Personal Conditions (14:11) - Chris Golec: Choosing Early Stage Building Work (15:19) - Hope Barrett: Feeding curiosity across multiple domains (17:45) - Simon Lejeune: Treating work like a game (19:52) - Ana Mourão: A mental buffer between noticing and doing (21:46) - Tiankai Feng: Anticipation planning (25:30) - István Mészáros: Choosing Who You Are When Work Ends (29:52) - Danielle Balestra: Feeding Interests Unrelated to Work (31:42) - Jeff Lee: Continuing to Build Personal Projects After the Workday Ends (33:23) - John Saunders: Keeping a builder practice outside of work (34:41) - Ashley Faus: Group Creative Rituals Outside of work (37:40) - Anna Aubucho: Maintaining a second self through solo creative practice (39:56) - Ruari Baker: Preserving Identity Through Regular Travel (42:15) - Guta Tolmasquim: Building a personal product roadmap (45:37) - Pam Boiros: Feeding identities that have nothing to do with work (47:52) - Outro All that and a bunch more stuff after a quick word from 2 of our awesome partners.A lot of the operators I chatted with don’t talk about happiness like it suddenly arrives. They describe it as something you feel when things actually start to move. Our first guest gets there right away by tying happiness directly to progress, the kind that tells you you’re not stuck.Rich Waldron: Auditing Whether Work Is Actually MovingFirst up is Rich Waldron, Co-founder and CEO at Tray.ai. He’s also a dad, and a mediocre golfer.Progress sits at the center of Rich’s definition of career happiness. He treats it as a felt sense rather than a dashboard metric. When work advances in a direction that makes sense to him, his energy steadies. When that movement slows or stalls, frustration surfaces quickly and spreads into everything else. That feeling becomes a cue to examine direction rather than effort.“Happiness is mostly driven by progress.”That framing resonates because it names something many operators struggle to articulate. Long hours can feel sustainable when the work moves forward. Light workloads can feel draining when days repeat without traction. Progress gives work narrative weight. It answers a quiet internal question about whether today connects to something that matters tomorrow.Rich also points to patterns that erode meaning over time.Roles with little challenge dull attention, even when the pay is generous.Constant activity without visible change breeds irritation that lingers after work ends.Both conditions interrupt momentum. The mind keeps searching for movement that never arrives. Rest stops working because unresolved motion occupies every quiet moment.Progress also shapes identity beyond work. When things move in the right direction, attention releases its grip on unfinished problems. Rich links that release to showing up better at home. He describes being more present as a parent because mental energy is no longer trapped in work that feels stuck. Forward motion restores proportion. Work keeps its place as one part of a full life rather than the dominant one.Balance emerges as a byproduct of this orientation. You choose problems that move. You notice when progress fades. You adjust before frustration hardens into burnout. That rhythm preserves meaning over long career arcs and keeps work aligned with the person you want to remain.Key takeaway: Track progress as a signal of meaning. When your work moves in a direction you respect, it stays contained, your identity stays intact, and the rest of your life receives the attention it deserves.Samia Syed: Tracking Personal GrowthThat’s Samia Syed, Director of Growth Marketing at Dropbox.  She’s also a mother, outdoor fanatic, and an avid hiker.Progress became the scorecard Samia relies on to keep her career from consuming her sense of self. Early professional years trained her to chase perfection, because perfection looked measurable, respectable, and safe. That mindset quietly tightened the frame around what counted as a good day. Effort increased, expectations rose with it, and satisfaction stayed elusive because the standard never settled.Progress creates a different rhythm. It shows up in motion you can recognize without squinting. Samia pays attention to signals that accumulate instead of reset:Teams moving forward together rather than cycling through urgency.People developing judgment and confidence over time.Personal growth that feels lived-in rather than optimized.A child learning, changing, and surprising you in ways no metric could predict.That framing matters because it ties work back to a broader life rather than isolating it. Progress carries meaning when it connects professional effort to personal identity. Samia talks about watching her daughter grow with the same care she gives to her team’s evolution. Growth becomes something you witness and participate in, rather than something you chase or defend. That mindset keeps work from becoming the only place where worth gets measured.“Anchoring on perfection as your metric for happiness sets you up for unhappiness. Progress is where I find it now.”Many careers quietly reward polish over development and composure over learning. Progress resists that pressure by valuing direction and continuity. It leaves room for ambition while protecting a sense of self that exists beyond job titles. You still push forward, but you also recognize that your life holds meaning across roles, seasons, and relationships that no performance system can fully capture.Key takeaway: Track progress instead of perfection. Pay attention to growth across work and life, because meaning comes from seeing yourself develop over time, not from chasing a standard that keeps moving.Jonathan Kazarian: Tracking Growth Across Life Health and WorkThat’s Jonathan Kazarian, Founder & CEO of Accelevents. He’s also father and a frequent sailor.Jonathan keeps work from consuming his identity by actively measuring progress in more than one place at the same time. He pays attention to movement in business, health, and personal life, and he revisits those signals regularly. That habit creates distance between who he is and what he works on. Work becomes one lane of progress instead of the entire road.Growth carries real weight in his thinking because it shows up as momentum you can feel. He talks about forward movement as something tangible, the sense that effort today pushes life somewhere better tomorrow. Setbacks still happen, but they do not erase t...

People describe the routines and boundaries that protect family time and emotional energy. They share small daily rituals, in-person conversations, and regular check-ins that recharge relationships. Several stories focus on designing work to enable travel, protect creativity, and keep priorities aligned with what matters most.

Careers place a ton of demand on energy and attention way before results start to stabilize. Many operators discover that health and routine determine how long they can operate at a high level.I spoke with 50 people working in martech and operations about how they stay happy under pressure. This 3 part series – titled “50 Operators share the systems that keep them happy” explores each of these layers through the lived experience of operators who feel the same pressure you probably feel right now.Today we start with part 1: stability through routines, boundaries, and systems that protect the body and mind. We’ll hear from 15 people:(00:00) - Teaser (01:05) - Intro (01:30) - In This Episode (04:09) - Austin Hay: Building Non Negotiables (08:06) - Sundar Swaminathan: Systems That Prevent Stress (12:33) - Elena Hassan: Normalizing Stress (14:32) - Sandy Mangat: Managing Energy (16:31) - Constantine Yurevich: Designing Work That Matches Personal Energy (19:05) - Keith Jones: Intentional Work Rhythms (23:58) - Olga Andrienko: Daily Health Routines (26:06) - Sarah Krasnik Bedell: Outdoor Routines (27:21) - Zach Roberts: Physical Reset Rituals Outside Work (28:57) - Jane Menyo: Recovery Cycles (31:56) - Angela Vega: Chosen Challenges and Recovery Cycles (36:09) - Megan Kwon: Presence Built Into the Day (37:50) - Nadia Davis: Calendar Discipline (39:36) - Henk-jan ter Brugge: Planning the Week as a Constraint System (43:15) - Ankur Kothari: Personal Metrics (44:07) - Outro Austin Hay: Building Non NegotiablesOur first guest is Austin Hay, he’s a co-founder, a teacher, a martech advisor, but he’s also a husband, a dog dad, a student, water skiing fanatic, avid runner, a certified financial planner, and a bunch more stuff... Daily infrastructure shows up through repetition, discipline, and choices that protect energy before anything else competes for it. Austin grounds happiness in curiosity, but that curiosity only thrives when supported by sleep, movement, and time that belongs to no employer. Learning stays fun because it is not treated as another performance metric. It remains part of who he is rather than something squeezed into the margins of an already crowded day.Mental and physical health shape his schedule in visible ways. Austin treats them as operating requirements rather than aspirations. His days include a short list of behaviors that carry disproportionate impact:Regular sleep with a consistent bedtime.Exercise that creates physical fatigue and mental quiet.Relationships that exist entirely outside work.Hobbies and games that feel restorative rather than productive.These habits rarely earn praise, which explains why they erode first under pressure. In his twenties, Austin chased work, clients, and money with intensity. He told himself the rest would come later. That promise held eventually, but the gap years carried a cost. He remembers moments of looking in the mirror and feeling uneasy about the life he was assembling, despite checking every external box.Trade-offs now anchor his thinking. Austin frames decisions as equations involving time, energy, and outcomes. Goals demand inputs, and inputs consume limited resources. Avoiding that math leads to exhaustion and resentment. Facing it creates clarity. Many people resist this step because it forces hard choices into daylight. The industry rewards the appearance of doing everything, even when the math never works.“I view a lot of decisions and outcomes in life as trade-offs. At the end of the day, that’s what most things boil down to.”Sleep makes the equation tangible. Austin aims for bed around 9 or 9:30 each night because his mornings require focus, training, and sustained energy. He needs seven and a half hours of sleep to function well. That requirement dictates the rest of the day. Social plans adjust. Work compresses. Goals remain achievable because the system supports them.He defines what he wants to pursue.He calculates the energy required.He locks in non negotiables that keep the math honest.That structure removes constant negotiation with himself. The system holds even when motivation dips or distractions multiply.Key takeaway: Daily infrastructure depends on non negotiables that protect sleep, health, and energy. Clear priorities, visible trade-offs, and repeatable routines create careers that stay durable under pressure.Sundar Swaminathan: Systems That Prevent StressNext up is Sundar Swaminathan, Former Head of Marketing Science at Uber, Author & Host of the experiMENTAL Newsletter & Podcast. He’s also a husband, a father and a well traveled home chef, amateur chess master.Stress prevention sits at the center of Sundar’s daily system for staying happy and effective at work. A concentrated period of personal loss collapsed any illusion that stress deserved patience or tolerance. Three deaths in three weeks compressed time, sharpened perspective, and forced a reassessment of what stress actually costs. Stress drains energy first, then attention, then presence. A career cannot outrun that erosion for long.Control defines the structure of his days. Sundar organizes work and life decisions around what he can actively influence and treats everything else with intentional distance. That discipline reduces noise and preserves energy. The system stays practical because complexity invites self-deception.Work within control receives effort, follow-through, and care.Work outside control receives acknowledgment and release.Outcomes matter, but the quality of effort matters more.Emotional reactions get examined instead of amplified.That repetition builds resilience as a habit rather than a personality trait. Over time, the body learns that urgency does not improve outcomes, while steadiness often does.Long-term thinking provides ballast when short-term chaos shows up. Sundar frames happiness the way experienced investors frame capital. Daily decisions compound quietly. Some weeks produce visible setbacks. The trend still moves when investments stay consistent. He invests daily in relationships, energy, and directionally sound choices. Moving his family to Amsterdam followed that logic. The decision carried friction and uncertainty, yet it expanded daily happiness in ways that cautious planning rarely delivers.“If you keep investing in yourself and the relationships that matter every day, the long-term trend moves up.”Priorities reinforce the system. Sundar grew up with career dominance baked into identity. Family now anchors that identity with clarity. That hierarchy shapes calendars, boundaries, and energy allocation. Work performance benefits from this structure because focus sharpens when limits exist. Activities that drain energy lose priority quickly. Unhappiness spreads fast and contaminates every adjacent part of life.Environment completes the infrastructure. Daily systems matter as much as mindset. Living in a place where flexibility exists without negotiation removes friction before it forms. Parenting logistics do not create anxiety. Time away from work does not require justification. Many expat families notice similar relief because daily life carries less ambient pressure. When systems support people, stress loses room to grow.Key takeaway: Sustainable careers rely on daily infrastructure that prevents stress before it accumulates. Clear control boundaries, long-term thinking, and supportive environments create stability that protects energy and compounds over time.Elena Hassan: Normalizing Str...

Phyllis Fang, Head of Marketing at Transcend focused on data privacy and trust infrastructure, and former Uber safety marketer. She talks about permissioned data systems and how consent powers personalization. She explains auditing data touchpoints, building a marketing trust stack, and why consent can become a revenue lever. She also discusses designing teams for curiosity and skills that matter in the AI era.

In this discussion, Jordan Resnick, Senior Director of Marketing Operations at CHEQ, breaks down the complexities of identifying real versus fake traffic. He highlights the surge of AI-driven bots and explains how they mimic genuine user behavior. Jordan reveals strategies for detecting bot activity through behavioral patterns and offers practical solutions for go-to-market teams to mitigate lead pollution. He also discusses the importance of transparency in reporting and adapting marketing systems for the evolving landscape of machine customers.