Data Analysis Can Be Tough. These Tips Can Make It Easier.

You’ve created the marketing plan. You’ve set up a system for measuring metrics and have been tracking KPI’s religiously. You’ve encouraged your team to follow leads, create content, and make connections. Now it’s time to gather up all those charts and numbers and see what it all means. Data analysis is arguably one of the most important steps in any digital marketing strategy. It’s also arguably one of the most difficult.

Analyzing your data is about taking the raw numbers you've gathered for the past day, week, month, and year and giving them a voice. The data will tell you a story. This “data story” will make or break your marketing initiatives. If you don’t take the time to analyze your findings, you just have a bunch of numbers sitting in a spreadsheet. And that would be a pretty boring story. 

  • To correctly analyze your data you need to know a) what you’re looking for, and b) how to assemble the data that you’ve acquired and make it meaningful. There are a few pieces of advice to make sure you do this in the most productive way possible.

 

1 // Decide what you want to show

Decide on what you’re looking for before you dive into the data. Which is also pretty good advice for diving into pretty much anything. Most marketing teams will be focusing on analyzing leads, sales, conversions, ROI, and anything else that gives insight on how to optimize your marketing efforts. Let your data work for you! 

 

2 // Go back to your KPI’s

Remember those KPI’s you spent hours researching last quarter? You bet you do. Pull the data you’ve been tracking and put it into an easy to read presentation to share and analyze with your team. Together, look at the data and search out any patterns that you can derive meaning from. If your retention fluctuated, talk about what was happening at your company during the two weeks it went up. Did you hire a great customer service rep? Did you start a new blog series? Make lists of all of the factors that affect the KPI’s you're analyzing to figure out what caused increases and decreases. Collaborating with your team will be invaluable for this process. The goal is to have a comprehensive view of everything that was going on at the company to make sure you are linking cause (new email campaign) and effect (rise in click rate).

 

3 // Separate qualitative data from quantitative data

Both are important, but you need to know which is which. It’s like how stalactites are different than stalagmites. (We forget which is which, but you get the idea.) If you have been tracking your retention rate for the past three months, that is number specific, quantitative data. If you put out an awesome survey where you got meaningful customer feedback, that is qualitative. Keep them separate so that you can let the numbers speak for themselves, and then later contextualize and confirm your findings with the qualitative data.

 

4 // Separate internal data from external data

Start with the internal data you’ve gathered from your campaigns (your KPI’s are internal data) and organize it. Once it’s sorted out, look to external data you’ve gathered (survey of the industry, interviews with customers, outside research on community management strategies) in order to strengthen the internal data with outside sources, fact checks, and testimonials.

 

5 // Prioritize your data and put it together

Data analysis is going to be a part of your daily task as a marketer. But if you’re looking to prepare an end of quarter report for upper management, skip the detailed daily updates and paint a comprehensive picture of the last few months’ findings in a seamless, easy to understand way. Since you’ve now organized and analyzed your data with your team, go through and select data you think shows relevant, interesting patterns that you’ve determined hold significant meaning. Contextualize your findings with quotes from customers and other helpful qualitative data, detailing how relationships between different marketing efforts intertwine to create a complete story. 

 

Let’s finish this.

Data analysis is all about turning numbers into a story. Use the knowledge and experience of your entire team to dig deep and discover what your numbers are trying to tell you. Once you have a clear picture of what went on in your campaign, you can sit down and evaluate what you need to change the next time around. 

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