Data-Rich, Decision- Poor - Why I’m Writing Here
Less channel and tool worship. More decisions that move the number on a trusted customer data foundation. Audience-first, not AI-first.
You probably have more customer and marketing data than ever and a pile of Gen-AI tools promising salvation. Instead, they’ve added more cycles of work.
Decisions still drag. In many teams, AI made it worse: weeks of analysis for choices that should take hours. Data chaos. Dashboards everywhere, clarity nowhere. Meanwhile, “AI gurus” sell prompt packs and playbooks that deliver… more confusion.
I’m Abhi Yadav. I’ve spent my career at the intersection of consumer identity, decision science, and knowledge graphs and I pride myself on being a result oriented operator who ships data-driven growth engines while being less gregarious and more nerdy. Although I’ve been lucky to learn alongside some of the world’s best marketing, GTM and CX teams at Google, Palo Alto Networks, American Express, Target, Nike, Akamai and 100s of data driven GTM operators who came from CMO or CIO or CDO orgs yet outcome focussed then IT projects focussed. I helped pioneer Customer Data Platforms (CDPs). Now I’m focused on what comes after the data platform: activating decisions and building high-performance GTM ops that cut through tool-first and channel-first noise.
I don’t have all the answers. I’m still learning given the speed of evolution. This publication shares what’s worked (and what hasn’t) to decide faster with the composable stack you already have.
What you’ll get perhaps 2-3 times a month
From the trenches: What actually works when teams are moving fast.
Enterprise-ready, practical: Futuristic ideas you can deploy at scale.
Ops → outcomes: How Marketing/RevOps quietly create real lift.
Vendor-neutral stories: Real implementations, no hype, no pay-to-play.
Innovation notes: Reflections and experiments worth stealing.
Who this is for
You own a growth number (revenue, pipeline, CAC).
You're tired of pretty charts that don't change what you do next.
You want real help using AI, not another tool or demo or academic theory.
Marketing/RevOps or Data Ops team who wants to elevate their story which execs/board can understand & appreciate.
Your data is still in a mess, forget about decision activation
Modern CMOs, CXOs, Marketing/RevOps, Founder/CEOs folks who are struggling to activate decisions in a data rich, decision poor operations.
What you won't get
Tool reviews, vendor horse races, or academic frameworks that never touch reality.
No "future stack" drawings divorced from the mess we all operate in. No more AI hype disguised as strategy.
What I've seen so far
2015–2019: Collect & buy all the data, use scrappy tools & integrate everything
2020–2023: Millions spent but no ROI, so many tools & integrations, even slower decisions
2024–now: Agents everywhere promising faster decisions but often breaking, delivering more work for humans to check. Useful when it shortens signal → decision → action, counterproductive when it just gives you smarter ways to overthink.
My bias: quiet, clear first principle thinking beats loud stacks & vibe marketing.
Start here
"OODA Loop Marketing" - Learn what we are building and learn always on marketing
"Retail's AI Reckoning" - common traps and fixes for retail teams
"The Application Layer Is Melting" - why data first approach is future proof then tool first
My promise
3-4 post a month. One faster decision a week, plus a simple habit to make that speed stick. Short posts (5–7 minutes), checklists you can use tomorrow, and real examples no fluff, no pitches.
If that sounds useful, subscribe. Or just hit reply with the slowest decision on your plate. I'll share a way to speed it up.
Thanks for reading.
P.S. The decision loop I reference comes from the OODA model (observe → orient → decide → act). Old idea, still useful when you actually run it. More at abhiyadav.substack.com
Citation: Boyd, J. R. (1987). A discourse on winning and losing. Maxwell Air Force Base, AL: Air University Library Document No. M-U 43947.