How To Succeed In Marketing Without Understanding Data And Analytics
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Understanding data and analytics seems to be a requirement to create content nowadays. There is a heavy push towards using analytics to not only manage your site and traffic, but to actually create that content.
Using data in your content is powerful, because data and numbers are convincing. Numbers give you proof that what you are doing does or does not work. But what if you’re not great with numbers? What if complicated data and analytics don’t really inspire you? Can you still write worthwhile and valuable blog posts?
Why It’s OK If You Don’t Understand Data And Analytics
There are two ways you can use data and analytics: to manage your site to understand what’s happening, or to create content based on it. There are also two kinds of data: your own site analytics, and outside research that includes reports, abstracts, charts, etc.
We’re going to talk about data and analytics in terms of you actually writing content based on them.
If you’re like me, I sometimes feel both impressed and embarrassed when I read a post with lots of charts, graphs, and interpreted data. It’s useful content, and clearly the writer knew both how to research and find data as well as what to do with it once they had it. But much of the time I devolve into thinking “that’s a pretty chart, I wish I understood it” and taking little from the massive amounts of data presented.
We’re not all data junkies.
A couple of reasons not to fret if you’re not a data junkie:
- Not everyone cares about data and analytics. You clearly know you aren’t interested in data. That means there are other people like you.
- Your audience probably doesn’t, either. If you don’t write posts heavy with data, you won’t attract the attention of the big data-loving blogs. But that is OK–they and their readers probably aren’t your audience.
- Data and analytics are imperfect. Don’t assume that data-heavy content is the only viable content, or that it is superior. The thing about data is that it’s not a sure thing.
Let’s explore that last point, that data and analytics are imperfect.
People interpret what data and analytics mean according to their own prejudices and assumptions, even if they aren’t aware of it. So if you suck at data and analytics and don’t use it in your writing, at least you’ll know that you won’t be guilty of having the following characteristics of someone mishandling data for their content.
1. Creating a hypothesis and hunting for data to fit it.
I’m guilty here; I get a great blog post idea, with great keywords, and then start doing searches on Google to find data…that fits the idea.
It isn’t intentional, but it happens because there are deadlines, I’m enthralled and familiar with my blog post idea, and I don’t always stop to ask the right questions that would help me do research that might turn up something that doesn’t fit. Plus, we’re so focused on answering the questions around our idea that we don’t always remember to ask the questions that contradict our idea.
2. Unable to see that data doesn’t tell the whole truth.
As much data and analytics as you are referencing, you are inevitably missing out on something. You might have mountains of data and analytics, but knowing which of those insights matter is the real skill.
Numbers don’t lie, you’ve heard, and that’s true. But what it took to get those numbers might not be the full truth.
Take focus groups, for example, a common source of data. I’ve been in focus groups before–it was Vegas, and I wanted a free lunch. They asked all kinds of pertinent and probing questions, and to be honest, some of them I couldn’t really answer. I didn’t know why I didn’t like the TV show. I couldn’t really say why I would buy that particular brand. But I wanted the free lunch so I came up with some answers and filled out my questionnaire.
As Tim Kastelle said in explaining his revelation about why he realized he drank Coca-Cola: people don’t really know what they want. And so, when we collect data off of sources that rely on imperfect measurements, anything we interpret from that data is just another level that is skewed.
When data is based on asking people directly, you must remember that people lie (sometimes without really being aware of it) and that any data built on their responses will not be accurate. Numbers don’t lie, but data can.
“It’s a basic truth of the human condition that everybody lies. The only variable is about what. – Dr. Gregory House”
3. Implying that data is one-size-fits-all.
As we pointed out in our post about A/B testing our email subject lines, our data is just that: ours. It isn’t yours.
There’s a danger in suggesting that the data and interpretation we come up with is what you should do specifically. A great post is one that reveals internal data and findings merely publishes it as something interesting to share, and not inflexible must-follow rules.
Often, if you read a data-heavy blog post, you’ll see comments by readers who want to know what the takeaway is. In this way, data is dangerous. Readers often use it to build a list of rules and that’s a bad idea.
Research can be wrong. You need to do your own research. Don’t trust the data others share, because it isn’t your data.
4. Misunderstanding the audience.
Data and analytics can tell us things like audience demographics, who clicked more, who liked what, what posts get shared the most–but those numbers aren’t even close to the whole picture. Yet it’s easy to get lulled into a number-based understanding of who is reading what we’re writing.
Additionally, unless you are a blog that purely provides research and data, there is more that your audience wants from you. They want your experience, your opinion, your stories–they don’t want numbers and charts only.
How To Write Posts If Data Isn’t Your Thing
In a world of data-filled and scientifically tested posts, it seems like there is no place for someone who has neither the interest or skills to write such content.
Or, perhaps seeing the comments on blogs and social media where posts full of data and analytics get called to the carpet by numerically gifted readers makes you avoid such content at all costs. It’s bad enough that you don’t feel comfortable writing such content, but to have to explain and defend it under pressure is terrifying.
Does this describe you?
It describes me. And yet, I’ve dipped my toe in creating content that has data and science as its foundation. Here’s how you do it.
1. Know what kind of data and analytics would be interesting to your audience.
This seems like a cruel Catch-22: how do you know what kind of data your audience is interested in unless you can read data to find out? Fair enough. But let’s look at data from the proper perspective.
The CoSchedule blog is a metablog. We blog about blogging.
It makes sense that we share our Google Analytics and other data to help you reconsider your own content marketing approach. Analytics and data that are wrapped in tips to help you grow your traffic are probably interesting to you because you want your own blog to succeed.
But that focus on that type of analytics and data aren’t necessary for your content (unless you are also a metablog). Your food blog readers don’t care about your Google Analytics.
When it comes to creating content, you don’t have to be able to write about analytics and data in the same way. So if you stare at your Google Analytics with glazed eyes and don’t know how to interpret it into meaningful content for your book review blog…you don’t have to. Your readers care about books, not your traffic analysis.
2. You don’t have to be a scientist, but research can still be fun.
Referencing or using scientific research is popular in blog posts now, but not everyone is interested in reading about that.
Brain scans, for example. Posts that tell us “How Your Brain Responds To X While Doing X”. Urk.
When I see a post with images of brain scans on metablogs, I look around a bit to see if anyone is observing my abject shame at having no idea how to even process that information, and quickly scroll on by. If you ever see an image of a brain scan in a blog post I’ve written, rest assured I’m full of BS. I don’t know how to interpret that kind of data.
If brain scans and scatter plots of brain waves make your head spin, don’t use them. That is not the only kind of data out there. There are other routes to go, other more approachable data available.
A. Find Interpreters
Research doesn’t have to lead to numbers and medical data. It can be more conversational, perhaps another blog post or an infographic someone has compiled.
Whenever I find a blogger who has the ability to take a data and science-heavy concept and repackage it so it is more understandable or applicable to everyday life, I add them to my RSS feed. (e.g. Gregory Ciotti) Such blogs are valuable in that they help you understand data you’d otherwise ignore, and they also help you learn to understand it yourself.
B. Start With Questions
Find the data that makes sense to you by asking yourself a question, or look to your reader’s comments for a question they’ve asked. (We do that often.) Hit the search engines. Head over to Google Scholar. Then, answer questions with questions. Remember to ask questions that contradict your idea. You’ll find yourself asking the same questions your readers might as you’re doing research and those questions will lead you to find more answers.
Let’s say you’ve shared a recipe of a gourmet tater tot hotdish on your mommy blog, and a reader commented that her kids won’t touch tater tot hotdish because of a food poisoning incident one Christmas (a true story in my family). The reader then asks what can she do to get them to eat tater tot hotdish, because she’d sure like to try this recipe.
You decide you want to harness the convincing power of data in your response, and so you do some research on the psychology of why we associate a bad incident with food and never eat that food again. You look for those numbers and percentages and summarizing statements, extrapolating and interpreting based on your own stories to support your conclusions. You offer up the suggestion on how to change their memory of the last tater tot hotdish experience so that they associate it with positive memories.
(Note: I hope I never see a blog post which encourages psychological memory alteration to get a child to eat food. That would be terrible.)
Curiosity spurs research, especially when your questions are specifc. Consider these examples of questions you could ask and the fascinating data you could find for a post:
- Book Blog: How far do most people read in a Kindle ebook? What kind of books don’t get read very far?
- Tech Blog: Where do most Android phone users live? Is there a regional or economic connection to Android use?
- Writing Blog: How many self-published ebook authors have cracked the top 100 list on Amazon? Have the most successful gone on to use traditional publishers?
I’ve never been a research person, preferring instead to write off the cuff and use my current knowledge base and gut. But after delving into even a surface level of research online to satisfy my own curiosity, I’ve found it a fun. You don’t have to be able to comprehend brain scans to give data a try. Just start by answering your own questions doing basic searches.
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3. Be willing to gather data within your content niche.
You have the ability to create your own data, if you aren’t finding or understanding the research available.
I can guarantee you that if you start discovering and publishing your own data, you are going to attract others in your niche who are looking for data to reference. It’s a great way to get links, traffic, and attention.
Testing is a great way to create content that gives your readers comparisons and helps them come to conclusions on their own. Every niche blog can do this. Let’s set up an example, using a fictional food blog. What kind of data would your food-loving audience ever be interested in?
- I Baked 10 Different Chocolate Chip Cookie Recipes. Here’s What I Learned.
- Should You Choose Room Temperature Butter Or Not?
- Glass vs. Metal: Choosing The Best Pan, Backed By Research
I was a pastry chef once. Believe me, these are topics that will be of interest to serious bakers. And they are all topics you can test in your own kitchen, document, and write about easily because food is what you write best about. Testing and coming up with data is completely within your grasp!
Ask your readers questions and create surveys. Learn from your own readers the basics of general trends and preferences of that kind of audience.
While it’s true that readers don’t always tell the truth (remember Vegas and that free lunch…), it is an attempt to gather some data. Present it as the results of your survey, and not the end-all results of all time. Your survey shouldn’t be about how to make your site better (that’s of interest to you), but on the topics in your niche blog’s content core. Let’s say you write a blog about healthy living. You might create reader surveys on:
- The diets they adhere to, and why.
- How they track their diet and exercise, and which methods work for them.
- Exercise habits.
- Sleep habits, and how the compare to other sleep data.
We are all curious about what others like us are thinking. Surveys provide that answer, and also let readers have a part in building your content.
In an interview, Tim Ferris revealed a technique he used in creating a cookbook. He started by asking his readers to list two of their favorite cookbooks. From there, he went on Amazon and pared down that list based on cookbooks that had an average of 4.5 stars or higher. Here’s where it gets interesting:
” […] I looked at the 3-star most helpful reviews, or most critical/most helpful, and looked for the things that they identified as missing in those best books. Then I made a running list of all the things that were missing from even the best books. Like in barbecue, they neglect brisket a lot. I was like, “Okay, great. We’re going to do short ribs, brisket. It’s going to be my book.” I made like a hit list, because I knew the market was there.”
Data is everywhere. It’s just waiting for someone to come along and gather it together. Amazon.com is a great place to both find data and repackage data. Study complaints against your competitors’ books or products, or the complaints against products that are relevant to readers in your niche. Read the poor reviews, and see what people are saying is lacking or is a problem.
In Amazon (and similiar) reviews, people are telling you what they want by telling you what was missing from a product. That’s useful data that you can use to create content in general, and that you can document for others in your niche to use.
You might also use this information to help you craft reader surveys to see if what these reviewers are saying holds true for your readership. That comparison (your readers’ tastes vs. the reviewers’ tastes) would be an interesting blog post in and of itself.
4. Track results and create content from that.
What you discover from research, testing, surveys, and reviews must be turned into consumable content for your readers.
You can track your results on Google Spreadsheets, and use those results to generate a chart. As a bit of a joke, I wrote a post about the psychology of the sayings on the wrappers of Dove chocolates. No one in the world needed that data, but it was a fun challenge. I carefully tracked my testing results on a Google Spreadsheet, and then generated charts.
Immediately something as ridiculous as chocolate wrappers became…data. It became available for someone else to reference should they ever talk about chocolate and psychology.
And after eating all of the chocolate required to compile this data, I will never eat Dove chocolates again.
5. Skip data and research-based content altogether.
I meant what I said: there is room in content marketing for writers who aren’t into reading scholarly studies or eating two bags of Dove chocolates in the name of research.
There are so many other content types you can use on your blog, whether you wish to share your expertise, tell stories, inspire your readers, create how-tos, or review products.
You don’t have to be a data and numbers fanatic to be a part of content marketing, unless you are writing to an audience that demands it (a metablog or other industry blog that uses data to prove ROI and value of their product).
Luckily, the CoSchedule blog has a variety of writers with different approaches to content. This is one of the big strengths of a team blog, the ability to have that data junkie, and that story teller, as part of the team. When you are a solo blogger, it’s a little more challenging. You have to stretch your writing styles a bit further.
But remember: there is room for content marketers who aren’t data junkies!
For all of you non-data junkies out there, what do you do when you are faced with the need to deal with data and analytics? Do you have a team member to help you out?
August 28, 2014