Four reliable indicators that the marketing analytics program will fail

Marketing Analytics, Martech, ROI, Gartner, CMO, Machine Learning, Advertising, Predictive Analytics, AI, Artificial Intelligence

Marketing analytics has made strong inroads into agencies’ toolkits for the last three years. Machine learning-powered sentiment analysis, programmatic advertising, predictive analytics, and a cohort of other AI use cases are a frequent concern for the CMOs.

As per Gartner’s CMO Spend Survey, budget allocation for martech has fallen by 26% this year. Considering that investment rates peaked in 2017-2018, it can be extrapolated that most businesses are deep into exploring what they have purchased new technology and how it can be used to optimize in-house marketing processes.

According to Gartner, marketers have leveraged only 61% of the functions available in their martech portfolio. Most organizations lack people, skills, and a proper vision for their marketing analytics program.

Ascend2 research further mirrors that sentiment indicating that 61% of companies invested initially in martech solutions to improve marketing ROI and marketing efficiency. Yet, post-adoption, 47% of respondents still struggle to capture that elusive ROI figure, and 40% is far from being as productive as they’d like to be.

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