Only 32% of marketing professionals from around the world claim to be highly effective at engaging with individual customers, while even smaller percentages feel confident in their ability to identify and capture new markets (25%) or uncover new insights to generate additional business value (23%). These findings are from a new IBM study [pdf] that suggests that many marketers are limited in their analytical sophistication, basing their decisions more on past experience than prescriptive analytics that can improve their outcomes.
Close behind, 37% of respondents are termed “constrained analysts,” who are either “struggling to move into more prescriptive analytics and modeling,” or whose scope hasn’t moved outside of marketing and sales.
Just 23% can be dubbed “marketing scientists,” who are both advanced in their analytical capabilities and possessing a broader scope, thus allowing them to effect greater changes in their organizations.
Not surprisingly, traditional marketers lag marketing scientists across several data-driven areas. For example, they are less likely to use a broad variety of sources (25% vs. 48%), to use a scientific approach to research (16% vs. 45%), and to emphasize data-based decision making (18% vs. 49%). Constrained analysts tend to sit nearer to traditional marketers than marketing scientists across those points: just 27% emphasize data-based decision making.
Combining the proportion from each group that emphasize data-based decision making with the proportion of the survey sample that each group accounts for yields the following result: 28.5% of marketers surveyed emphasize data-based decision making. Or, to flip the result, roughly 3 in 4 rely more on “hunches and experience” than data to make decisions.
About the Data: IBM surveyed 358 marketing professionals in Australia, Canada, India, the United Kingdom and the United States to find out how they use data to make business decisions. Respondents come from a wide range of organizations covering 17 industries: 50% work for small companies (100-999 employees); 25% work for mid-sized companies (1,000- 4,999 employees); and 25% work for large companies (5,000 or more employees).