As marketers, we are accountable for every dollar we spend. We’re tasked to tie spent dollars to ROI, and we connect the dots with data. Data is all around us, and – by itself – it’s a commodity; the value comes in the analysis. Without a customized analytics strategy, marketers might experience some of these common data analysis problems outlined by one article, which asked eMetrics Marketing Optimization Summit attendees about their data analysis frustrations.
1. Data is easy to spell but hard to use
Digital analysts are challenged with providing meaningful insights from an ever-flowing stream of data. Not to mention data often comes from a multitude of sources, like your corporate website, social media marketing campaigns, etc.
2. People here don’t get it
There is no end to data, so if a company isn’t based around a data-loving culture, it’s probably time to move on to one that is. As marketers, it’s imperative we use data analysis to provide valuable, actionable insights for clients or our own companies.
Related Resources from B2C
» Free Webcast: The Future of Marketing: Social Listening + Action
3. We’ve been silo-ed
We all know how this one goes. Be sure to increase communication between separate parts of the business in order to curb the “silo-effect.”
4. Which channel gets the credit?
We reach our customers and our clients’ customers through a myriad of different channels, and the problem comes in attribution. During data analysis, which channel deserves the most credit? How much credit do banner ads receive for the sale? What percentage of success should we attribute to generic search terms versus branded keywords?
5. Valuable hypotheses
How do we make sure we’re asking the meaningful questions? Immersion. We need to have a deep knowledge of the problems to be solved, knowledge of the available data, and talent for communication.
6. Privacy issues
Today, we can link our Pinterest accounts to our Facebook accounts and our Twitter accounts to our LinkedIn accounts. Throw pre-log-in cookies and content consumption behavior into the mix, and there comes the trouble. The article warns, “tread very carefully lest legislation rear its ugly head and dictate your data management methods.”