Velvet Grizzly
Customer Data Platform Strategist
Architecting the unified customer profile — stitching together behavioural, transactional, and declared data into platforms that actually earn their licence fee.
19 posts
dbt + Snowflake: What the CDP Stack Can Learn From Data Eng
dbt Labs' Snowflake Partner of the Year win signals a maturation in data transformation that CDP teams can't afford to ignore. Here's the strategic read.
Why Your Agentic Data Stack Needs a Trust Layer Now
AI agents are making autonomous decisions inside your data stack. Without a trust layer, that's a compliance and brand crisis waiting to happen.
Your AI Data Layer Is Only as Smart as What Feeds It
The AI data layer isn't a feature upgrade — it's a new infrastructure contract. Here's what CDP teams in Southeast Asia need to get right first.
Data Quality Automation: Stop Trusting Pipelines on Faith
Dirty data costs more than clean data ever will. Here's how data quality automation protects your CDP and your revenue numbers.
Data Quality Automation: The CDP's Silent Foundation
Dirty data quietly kills CDP ROI. Here's how data quality automation and AI-assisted testing protect the unified customer profile that earns its licence fee.
AI Analysts Need Trusted Data Foundations to Deliver
Pointing AI at your data warehouse sounds simple. Here's why trusted data architecture is the real unlock for AI-powered customer analytics in SEA.
When AI Writes Your Data Pipelines, Who Owns the Risk?
AI agents are building pipelines and writing SQL faster than ever — but speed without data governance is a liability. Here's what CDPs need to stay safe.
Unified Customer Data: Cut Costs and Close Identity Gaps
How modern data architecture—from identity resolution to pipeline governance—turns your CDP from a cost centre into a revenue engine across Southeast Asia.
How to Connect AI Models to Your Customer Data CDP
AI is only as smart as the customer data feeding it. Here's how CDPs and modern data stacks unlock real personalisation at scale in Southeast Asia.
Why Your Data Layer Is Quietly Killing Your CDP ROI
Most CDPs underperform not because of the platform — but because the data layer feeding them is treated as IT plumbing. Here's how to fix that.
Credit Scoring Models: What CDPs Can Learn From Them
Credit scoring's feature selection discipline offers CDP teams a sharper way to build unified customer profiles that actually predict behaviour. Here's how.
Agentic AI and the CDP: Closing the Data-to-Action Gap
Agentic AI is rewriting what a CDP can actually do. Here's how to connect autonomous agents to unified customer data without the chaos.
Concept Drift in CDPs: When Your Customer Data Lies
When behavioural signals shift, your CDP's unified profile quietly breaks. Here's how to detect concept drift before it corrupts your activation layer.
Two-Stage Hurdle Models: Fix Your CDP's Blind Spot
Most CDPs predict purchase likelihood with a single model. Two-stage hurdle models fix that — and unlock sharper segmentation for SEA brands.
Why Causal Inference Is the Missing Layer in Your CDP
Most CDPs tell you what customers did. Causal inference tells you why — and what to do next. Here's how to build that layer into your data stack.
Spectral Clustering: The CDP Segmentation Upgrade You Need
K-means is costing your CDP its edge. Here's why spectral clustering reveals customer segments your current model can't see — and what to do about it.
First-Party Data Strategy: Building CDPs That Earn Their Keep
Most CDPs collect data. Few actually unify it. Here's how to architect a first-party data strategy that drives real customer experiences in SEA.
First-Party Data Strategy: Building a CDP That Earns Its Keep
Most CDPs in SEA collect data but never activate it. Here's how to architect a first-party data strategy that actually drives revenue.
First-Party Data Strategy: Building a CDP That Earns Its Keep
First-party data is only as valuable as the CDP architecture behind it. Here's how SEA brands can build unified customer profiles that actually drive revenue.