Only Two Per Cent of Enterprise Marketing Leaders Rate the Data in their Martech Stack as Strong

Nov. 10, 2025

Only one out of every 50 CMOs (2%) believe that their marketing data is strong and flows well through their martech stack, according to research released today.

As a result, the vast majority have experienced negative business impacts stemming from data inefficiencies:

• 48% say they waste time manually pulling reports
• 44% cite slow learning cycles and repeated mistakes
• 42% report losing budget due to underused or misused technology
• 40% experience ineffective media targeting or wasted spend.

The survey was carried out by marketing optimisation and transformation specialists Intermedia Global (IMG). It canvassed 250 UK C-Suite professionals with responsibility for marketing technology in mid-sized enterprises with annual revenues between £100m and £500m.

Emily Crisp, data planning lead at IMG, commented:

“The first step to making marketing technology perform better is to improve the data flow. It’s key to making the most of the tools you already have, which for most marketing departments is far more important than adding new ones to the martech stack. Shiny new AI platforms are all very well, but recent figures from MIT suggest that 95% of businesses are yet to see a return on their generative AI pilots and we can expect this translates to underperforming AI tools more broadly. This isn’t because the technology is bad, but those new tools will usually live or die by the data underpinning them.”

 

However, the current situation cannot be explained by a lack of understanding, as IMG’s research also underlines that most CMOs fully recognise the importance of good data: 91% believe that the quality of their data positively influences the success of their marketing campaigns.

Emily Crisp concluded:

“In our experience, the lack of good data is often the primary cause of friction and inefficiency in the marketing process. Any CMO looking to genuinely improve the Marketing Experience (MX) for their teams has to resist all the hype around AI silver bullets and focus on getting their data house in order. Anything else will simply create more work.”