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A key marketing challenge is demonstrating value and relevance. Marketers generally agree that marketing analytics can help marketers measure their contribution to the organizations they serve.
In April 2013, Demand Metric conducted a benchmarking study, with 622 respondents, to examine how marketing analytics is being adopted, adding value, and becoming integrated into overall marketing strategy.
A survey was used to collect data, and its analysis provides these key findings:
World leaders: North American organizations lead the world in meaningful marketing analytics initiatives
Size matters: large organizations are having more marketing analytics success than SMBs.
Money talks: those who are allocating greater portions of marketing budgets are getting more from their analytics initiatives.
Keeping it in the family: analytics data is largely staying inside the marketing department.
Perception isn’t reality: CEOs, presidents, SVPs and business owners have a significantly higher opinion of the credibility of marketing analytics data than do members of the marketing organization.
Table of Contents
State of Marketing Analytics
Attitude Toward Marketing Analytics
Use of Marketing Analytics Data
Impact of Marketing Analytics
Influence on Decision Making
Credibility of Data & Insights
Chief Analyst Bottom Line
About Demand Metric Benchmarking
The Demand Metric 2013 Marketing Analytics Survey was administered online over a period of April 17th through May 3rd, 2013. During that time, over 700 responses were collected, 622 of which were complete.
All members of the Demand Metric community received email invitations to participate in the survey, and participation was encouraged through a random draw incentive for an iPad Mini.
While respondent email addresses were collected in order to facilitate the prize drawing, no identifying information was retained or considered in the analysis of the survey data.
Following collection of the survey data, Demand Metric used IBM SPSS statistics software to analyze the results and draw statistically significant conclusions.