István built a warehouse-native analytics layer that lets teams define metrics once, query them directly, and skip the messy syncs across five tools trying to guess what “active user” means. Instead of fighting over numbers, teams walk through SQL together, clean up logic, and move faster.More
Yearly Archives: 2025
179: Tiankai Feng: The comeback of data quality and how NLP is changing the data analyst role
Data governance feels like the Jedi Council, steady with its rules, while marketing ops moves like the Rebel Alliance, quick to adapt when perfect data never arrives. Tiankai believes progress comes from blending discipline with curiosity, bringing data in early as a partner, not a critic.More
178: Guta Tolmasquim: Connecting brand to revenue with attribution algorithms that reflect brand complexity
Brand measurement often feels like a polite performance nobody fully believes, and Guta learned this firsthand moving from performance marketing spreadsheets to startup rebrands that showed clear sales bumps everyone could feel. When she built Purple Metrics, she refused to pretend algorithms could explain everything, designing tools that encourage gradual shifts over sudden upheaval.More
177: Chris O’Neill: GrowthLoop CEO on how AI agent swarms and reinforcement learning boost velocity
Chris explains how leading marketing teams are deploying swarms of AI agents to automate campaign workflows with speed and precision. By assigning agents to tasks like segmentation, testing, and feedback collection, marketers build fast-moving loops that adapt in real time. More
176: Rajeev Nair: Causal AI and a unified measurement framework
Rajeev believes measurement only works when it’s unified or multi-modal, a stack that blends multi-touch attribution, incrementality, media mix modeling and causal AI, each used for the decision it fits. At Lifesight, that means using causal machine learning to surface hidden experiments in messy historical data and designing geo tests that reveal what actually drives lift. Attribution alone can’t tell you what changed outcomes.More
175: Hope Barrett: SoundCloud’s Martech Leader reflects on their huge messaging platform migration and structuring martech like a product
In twelve weeks, Hope led a full messaging stack rebuild with just three people. They cut 200 legacy campaigns down to what mattered, partnered with MoEngage for execution, and shifted messaging into the product org. Now, SoundCloud ships notifications like features that are part of a core product. Governance is clean, data runs through BigQuery, and audiences sync everywhere. The migration was wild and fast, but incredibly meticulous and the ultimate gain was making the whole system make sense again.More
174: Joshua Kanter: A 4-time CMO on the case against data democratization
Joshua spent the earliest parts of his career buried in SQL, only to watch companies hand out dashboards and call it strategy. Teams skim charts to confirm hunches while ignoring what the data actually says. He believes access means nothing without translation. You need people who can turn vague business prompts into clear, interpretable answers.More
173: Samia Syed: Dropbox’s Director of Growth Marketing on rethinking martech like HR efforts
Samia Syed treats martech like hiring. If it costs more than a headcount, it needs to prove it belongs. She scopes the problem first, tests tools on real data, and talks to people who’ve lived with them not just vendor reps.More
172: Ankur Kothari: A practical guide on implementing AI to improve retention and activation through personalization
Ankur explains how most AI personalization flops cause teams ignore the basics. He helped a brand recover millions just by making the customer journey actually make sense, not by faking it with names in emails. It’s all about fixing broken flows first, using real behavior, and keeping things human even when it’s automated.More
171: Kim Hacker: Reframing tool FOMO, making AI face real work and catching up on AI skills
Tool audits miss the mess. If you’re trying to consolidate without talking to your team, you’re probably breaking workflows that were barely holding together. The best ops folks already know this: they’re in the room early, protecting momentum, not patching broken rollouts. Real adoption spreads through peer trust, not playbooks.More