
A Data and MarTech Audit gives you an obligation-free assessment of your marketing and customer data setup, including how data is captured, stored, integrated, and governed.
In as little as 3–6 weeks you get a clear view of what is missing, what needs fixing first, and what your current setup can support, plus a fix list with estimated effort and expected impact.
What the audit covers
The audit is designed to assess readiness for advanced marketing analytics and identify the changes that matter most, so you can prioritise fixes before committing to more complex work.

We map MarTech setup & data capture across CRM systems, web analytics, media platforms (paid & unpaid), customer databases, promotional calendars, etc.
The aim is to see what you have, how it’s structured, and whether it aligns across time, granularity, and definitions.

Next we review the data itself, focusing on:
- Quality - accuracy, completeness, reliability
- Availability - 2+ years of daily/weekly data for key KPIs, media, promos, major events
- Accessibility - storage and ease of access
- Governance - ownership, definitions, update process

We review how your tools and systems connect, looking for breaks in the data flow, data in silos, and manual steps that create risk.
We then assess whether the data can be centralised and normalised for analysis at the required frequency and granularity, and flag what is needed if it cannot.

Finally, we turn the findings into a practical roadmap, including short-term fixes (e.g. tracking, taxonomy), medium-term improvements (e.g. aligning owned & paid data streams), or more strategic changes like warehouse consolidation or platforms integration.
Where needed, I phase the work so you can move forward without overloading internal teams.
How I work
Discovery Sessions
- Collaborative conversations to map current systems, priorities and known pain points
Assessment Analysis
Evaluate how data is collected, stored, updated & connected
Typically covering marketing platforms, CRM systems, web analytics tools and data warehousing
Audit Report
- Plain English report, outlining what is ready to use, what is missing or unreliable and what needs work
Implementation
Coordinate with internal analysts and/or external agencies to validate findings
Support execution where needed