Martech data blind spots threaten AI payback

Martech data blind spots threaten AI payback

Only two per cent of CMOs say their marketing data is strong. Most are investing in AI without fixing weak data foundations, leaving advanced tools underperforming and marketing budgets misfiring, according to new findings from Intermedia Global.


The vast majority of marketing leaders admit their data infrastructure is failing, and with it so too does the performance of the artificial intelligence tools they are investing in heavily.

A new study from marketing transformation consultancy Intermedia Global (IMG) has found that just two per cent of enterprise CMOs believe their data is robust and well integrated across their martech stack. The remaining 98 per cent report weak data flows and inefficient systems that undermine both operational efficiency and strategic decision-making.

Those shortcomings have tangible costs. Almost half (48 per cent) of respondents said their teams lose time manually pulling reports; 44 per cent experience repeated mistakes due to slow learning cycles; and 42 per cent see budget drain away through underused or misused technology. A further 40 per cent pointed to wasted media spend from poor targeting.

IMG’s findings, based on a survey of 250 UK executives responsible for marketing technology across mid-sized enterprises, paint a picture of sophisticated martech stacks built on fragile foundations. While AI tools are now common, few companies appear to have the underlying data quality to make them deliver.

Emily Crisp, data planning lead at IMG, said the issue is structural rather than strategic. “The first step to making marketing technology perform better is to improve the data flow,” she said. “Shiny new AI platforms are all very well, but those tools will live or die by the data underpinning them.”

That warning aligns with wider research from MIT, which recently found that 95 per cent of businesses have yet to see a financial return on their generative AI pilots. Many are realising that automation and intelligence layers cannot compensate for inconsistent or incomplete datasets.

Despite this, the problem is not one of ignorance. According to IMG’s study, 91 per cent of CMOs acknowledge that data quality directly influences campaign success — yet few have managed to turn that awareness into structural reform.

Crisp added: “Any CMO looking to genuinely improve the Marketing Experience 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.”

For now, it seems most marketing departments are still feeding cutting-edge AI systems with second-rate data and expecting first-rate results.



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