Customer data architecture that delivers certainty.
Fractional CDA, Independent Advisor, Architecture Lead.
Working with marketing and data leaders who need a senior data architecture brain, not another platform vendor.
The problem followed you from the last platform.
It will likely follow you to the next one.
Here's how it typically plays out.
Your CDP isn't delivering unified profiles
Not because the platform is wrong, but because the data it can see is incomplete. Identity resolution inside a CDP only works on the sources the CDP is connected to. The sources it can't reach don't exist in your unified profile.
Your segments don't feel right.
Not because your marketing team is building them incorrectly. Because the intelligence layer producing them is working from partial data. Segmentation logic built on digital behaviour alone misses everything that happens offline, in store, in the contact centre, and in the transaction history.
You switched platforms and the same problems followed
Because the platform wasn't the problem. The architecture underneath it was. A new CDP or MAP inherits the same incomplete data, the same unresolved identity, the same ungoverned sources. The problems are not platform-specific. They are architectural.
The platform is not broken. The data architecture underneath it is. That is what we fix.
The Solution.
Full-Spectrum Customer Data Architecture
Same decision. Completely different foundation.
Independent Customer Data Architecture Leadership for Marketing and Data Leaders.
Customer Data Architecture Audit
Diagnose what is broken and why. Fixed scope. Fixed price.
Customer Data Architecture Blueprint
Design the target state. The blueprint your engineers and implementation partners build from.
Fractional Chief Data Architect
Ongoing architecture consultancy. One to two days per week. Monthly retainer.
Independence without ecosystem depth is just opinion. The architecture recommendations are grounded in hands-on delivery experience across the platforms and ecosystems that modern customer data architecture runs on.
Data Infrastructure
Snowflake · Databricks · AWS · Salesforce Data Cloud (Data 360)
Cloud-first architecture, medallion architecture design, data pipeline design, reverse ETL patterns, lakehouse architecture, ID resolution strategies.
MarTech Ecosystem
Marketing automation platforms · Customer data platforms · CRM architecture · Integration and middleware · Consent management · Analytics and attribution
Over two decades of delivery across the full MarTech stack — from ESP data models through to enterprise MAP architecture and composable CDP design.
Insurance
Retail & D2C
B2B SaaS
Auto
Public Sector
Outside these sectors the practice takes on selective engagements where the customer data architecture problem is acute and the fit is clear. The discovery call is the right place to find out.
Is this the right fit?
- Your board has asked for an AI strategy and you know the data foundations are not ready to support one
- You are preparing a significant platform investment and want an independent assessment before you commit
- You have switched platforms before and the same problems followed — and you now understand why
- You are under Consumer Duty or GDPR scrutiny and your consent and data governance architecture cannot currently withstand examination
- You have recently taken on a new role, inherited a complex data environment and need an honest picture of what you are working with
- You need someone to implement a platform — that is a different engagement and I will point you toward the right people
- You have already decided what to do and need someone to validate it — the assessment follows the evidence, not the brief
- You are looking for a vendor recommendation — there are no platform relationships here and no commission on what you buy
- You need a large team with multiple workstreams running in parallel — this is a senior independent practice, not a consultancy with fifty analysts
Start with a conversation.
Fixed scope. No retainer required.
Starting from $5,000.
Thirty minutes. No pitch. An honest conversation about what you are seeing, whether this is the right fit and what the next step should be.
Fresh Perspectives.
Practical thinking on Customer Data, MarTech, AI, and making better technology decisions.
