Study Reveals How Marketers Should View Access To Data

Data-Shutterstock-ASome 46% of marketers participating in the 2013 MarketingSherpa Marketing Analytics Benchmark Report occasionally gain insight from analytics data their company collects. And while another 37% routinely gain insight, 6% rarely gain insight, 9% lack the tools, and 2% don’t have access to the data.

MarketingSherpa's first extensive study of marketing analytics research aims to help marketers do their job better by benchmarking data use in social media, search engine optimization, paid search and display advertising, as well as email, video and content marketing.

The report -- insight from 1,131 marketers who participated in our research -- reveals that 53% plan to increase budgets for analytics platforms and use, 43% plan to keep investments the same, and 4% plan to decrease investments.

When asked to name the greatest challenge to effective analytics use, 21% of marketers said lack of resources to execute strategy; 20%, time required; 17%, lack of understanding on how to proceed; 15%, budget constraints; 13%, lack of system integration; 10%, lack of systems; and 3%, other.

Many marketers don't understand that the data doesn't sit on the surface, but rather exists deep within each siloed media segment. What will marketers strive for in 2013? Only 27% said integrating silos of data, something marketers should become more concerned with accomplishing -- especially because attribution will drive better return on investment. Campaigns will never reach their full potential without integrating silos of data from mobile, desktop, video, Web-based television and other media.

The surface data will not provide the same insight as digging deep into data from each media and matching it to the others. The next challenge will become integrating data from intent signals from around the globe rather than device, no matter the device.

What did marketers say they want to improve on? Some 66% said they would work toward acting on data to improve marketing performance, followed by 39% who said they would combine data from multiple sources to draw conclusions and make predictions, 28% who said they would measure attribution and interaction across channels, and 27% who said they would improve data quality.

"Data photo from Shutterstock"

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