Data Readiness: The Foundation for AI Automation & Effective Customer Engagement

The full recording and slide deck from our live session, everything you need to take action on your data strategy today.

Untitled design (1)-1

£900bn

annual cost of dirty data to UK businesses

12%

of revenue lost to inaccurate data on average

22%

of customer records in UK databases are inaccurate

WATCH THE RECORDING

The full session, on demand

what we covered

Session Agenda

01
Why automation investments underdeliver
The tools are ready. The ambition is there. The gap is almost always the same thing with Marie Roberts
02
A live diagnostic: how data-ready are you?
Five questions. Answer honestly. Understand where your organisation actually sits with Dan O'Reilly
03
What data readiness actually means
Clean, structured, accessible, usable, defined and why each layer matters with Marie Roberts
04
The Automation Maturity Model
Four stages, where most organisations sit, and how to progress through them with Marie Roberts
05
A practical framework: Audit · Centralise · Enrich · Govern
Four actions you can start today. The sequence matters with Dan O'Reilly
06
HubSpot in action
How HubSpot enables data readiness end-to-end, with live examples with Jeremy Williamson
Guest spotlight: Compare the MarketDMA Gold 2025: "Making AutoSergei Real with Meer-tech." What it actually took behind the scenes with Ji Hye Chang and a live Q&A with all speakers.
SLIDE DECK

Download the presentation

DOWNLOAD SLIDE DECK

The full slide deck from the session, including the Automation Maturity Model, the Audit · Centralise · Enrich · Govern framework, case studies, and all key stats.

Screenshot 2026-03-19 at 22.39.47
KEY TAKEAWAYS

Three Things to Act On

1

The data problem is solvable
It is not glamorous, but it determines whether every other investment you have made actually delivers. The good news: you can start with a single contacts report this week.

2

Most organisations are closer to the start than they think
Run the five diagnostic questions honestly. The gap between perceived maturity and real maturity is usually significant and knowing where you are is the first step.

3

The sequence matters, you cannot skip steps
Clean data → connected systems → reliable automation → AI as the natural next chapter. In that order. AI does not fix a data problem. It amplifies one.