Working with Analytics: How to Organize Actionable Data

Author: Bradley G., Public Relations Intern

The big word of the 21st century is “Data.” Data is the tool by which we use science, log things on the world wide web, and, most importantly, it’s how we measure the successes or failures of our business. Consider the terms you’ve heard before discussed when marketing comes into the picture:

  • Target Demographics
  • Market Research
  • Brand Awareness
All of these share a kind of intellectual gravity, they bear a necessity for study and analysis. In short, they mean you’re going to have to do a lot of light science and math to find answers for what people are interested in buying and the appeal of your product. You likely know that to find these answers, you’re going to need to conduct studies, track what marketing techniques work and which ones don’t, and routinely probe public consciousness to see what’s trending so as to take advantage of it.

How do you collect and manage all of this data? The answer is in the craft of Analytics, which will be the focus of this article. We’re going to explain what analytics are, look into what “actionable marketing data” means, and explore what tools you can use to gather analytics.

Article Contents
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What Are Analytics?

How can one best define Analytics? Business Dictionary does a fine job in summarizing as follows:

    “The field of data analysis. Analytics often involves studying past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario. The goal of analytics is to improve the business by gaining knowledge which can be used to make improvements or changes.” [1]
What this means is that if you’re going to be collecting and tracking any kind of data for how your products are selling or how they could sell better, then you’re going to need to be working with analytics for them. Spreadsheets, graphs, charts, and routine calculation are all cornerstones of this field. It requires lots of number crunching, technical skill, and the ability to look with a discerning eye at what data matters. This last point is possibly the most crucial for a marketer to know, as you’re likely to be barraged with a huge amount of data about what’s going on with your current sales, where the market is, what’s popular, how much expendable income people have, and so forth.

Consider the example of a company that specializes in making cheap ramen, which for simplicity we will call “EZRamen.” EZRamen needs to track a large amount of numbers to be effective in business:

  • How much are customers willing to pay for ramen and how much are competitors selling it for?
  • What is the target demographic and what are they interested in buying?
  • How popular is ramen at this point in time in the market? Is there an upswing or a downswing and what is the cause?
  • What marketing campaigns tended to be more successful for EZRamen, and is there a marketing trend that’s either generally popular or popular for food sales that they could exploit?
The marketing team at EZRamen would have to look at all this data to accurately measure what actions they should take in the future. That being said, they’re likely to get a lot of data that they don’t need or can’t use: they need to be able to sort out the useful data from the rest. What is this useful data referred to as?

What is “Actionable Marketing Data”?

Ashish Gambhir, the co-founder of NewBrand Analytics, defined Actionable Data as follows:

    “Actionable data enables you to do something with the feedback. It answers not just "what" but "where, when, and why.”” [2]
Actionable Marketing Data is, in other words, the data you can work off of for marketing purposes. This is the data you can use to make decisions for who to direct your marketing campaign towards, when you should air advertisements on television, where online you should be posting ads to best reach your target demographic, and several other important decisions marketers need to be educated about before implementation.

Let’s return to EZRamen for a moment. EZRamen conducted some studies, and found a few pieces of data:

  1. College students (mostly freshmen and sophomores) make up the bulk of EZRamen sales.
  2. Maruchan and Top Ramen, the primary competitors for EZRamen, they charge about $0.99 for a pack of ramen standard.
  3. Ramen is listed as a high priority snackfood among college students, though they get lower and lower as the college students get older, with many citing that they’ve become “sick of the stuff.”
  4. Ramen sales start mounting up in August in January, the two times that students are returning back to school after breaks. The rest of the year are a slow decline before hitting peak numbers again during these months.
  5. EZRamen ads tend to do better when they feature some degree of “meme” humor popular with millennials and college students, though the ads themselves tend to bomb if the jokes are perceived as being too forced.
  6. Consumers tend to prefer the taste of Maruchan ramen to EZRamen.
This data is largely actionable, but let’s go part by part to consider what pieces of data are actionable and which are not to illustrate the point.

The first piece of data informs us that the demographic EZRamen needs to be targeting is freshman and sophomore college students. The second piece of data gives a price range that EZRamen should be charging around, as they don’t want to be considered too expensive or too cheap in comparison to the competitors. The third piece of data is largely useless, as there’s little to be done to combat diminishing interest in the product’s taste from a marketing perspective. The fourth piece of data gives important dates to focus advertising around in order to get consumers to remember EZRamen. The fifth piece of data indicates what kind of ads EZRamen should be running while also hiring coordinators for these ads that understand meme culture. The final piece of data is not actionable from a marketing perspective because it’s not marketing job to quality-test the taste of the product.

It’s likely you were able to reason most of that out yourself, which is a good sign: figuring out what data is actionable is and which is not is fairly common sense when you write it out this way, but the amount of numbers and spreadsheets you would get in marketing can be overwhelming. Thus, we implore you to remember that this doesn’t need to be that hard once you think of it this way. There are even tools out there to help you work with analytics and make them easier!

How Does One Gather and Organize Actionable Data?

As we wrote before in our article on demographics research, finding data for marketing purposes can be as simple as a Google search or an e-mail survey. More in-depth information specific to your product or service may come from user reviews (either from e-mail surveys or online review sites like Yelp) or from conducted surveys with a representative portion of your intended demographic pool or proven customers. Conducting these surveys and polls is the subject for another article, but there’s a multiplicity of guides online for how to do so if you want to inquire further right now.

As for organizing your data, the obvious answer is through either Microsoft Excel or Google Sheets, both of which give you spreadsheets to organize and crunch all the numbers. These numbers can then be summarized in a report for your business. How, though, do you get metrics for your online endeavors for advertising or social media? How can you track how certain ads are benefiting you, and how can you tell how successful specific posts are without spending inordinate amounts of time on it? Thankfully, there are multiple programs (many of them open-source) which can help you with this. [3]

  • Google Analytics - Google Analytics are the go-to tool for multiple businesses due to its plethora of features and open-source nature. All you need to do is add the Google Analytics code into your website’s HTML and then it will track how many people are visiting the website, where people click, how long they stay, and various other statistics.
  • Bitly - Bitly is known for shortening links to post on social media, but they also offer a free service to track the performance of those links, measuring clicks and the location of their origins.
  • Piwik - Piwik functions similarly to Google Analytics, but it’s much more complicated and requires that you download it onto your server. With this action, however, you can run more in depth measurements of your website’s performance than Google Analytics allows. It’s worth a warning that the interface is much more complicated than Google’s, so Piwik is really for the experienced or the patient.
  • Hootsuite - Hootsuite is the standard for social media management, with access to multiple platforms of social media at once, with the program online allowing you to track the performance of posts across multiple channels. The catch here, however, is that Hootsuite is a paid for service, and we’ve had some trouble running it at our company. Thus, we turned to...
  • Sendible - Sendible contains the same functions as Hootsuite but with a more user-friendly interface, as well as a fine amount of metrics functions for you to view charts and print out reports.
Utilizing one or more of these tools will keep you on top of your data, making your analytics run as smoothly as any multinational corporation.


Analytics isn’t something that you buy; analytics is something you have to do. It’s the work of looking through marketing data to find out what you can improve on in order to increase sales and maximize profit for your company. There are several tools that you can use to help you in your endeavors to do so, and all you need to do is take the first step in looking at what your company needs to know.

There’s an old adage about knowledge that says there are known knowns, known unknowns, and unknown unknowns. Most future problems for the market are unknown unknowns, but you have to know what blindspots your company has for consumer focusing and engagement. Seek them out, gather your data, and crunch the numbers to see what works and what doesn’t. Take some time to experiment with the tools available to you and find out which ones work for you.

With a little time and a little math, you may find yourself becoming an analytics expert. That’s a great benefit for a resume AND a company.


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