I started using Tableau with Version 3.6 way back in February, 2008. Since that time, I have continued to use Tableau about every day, with several thousand data files investigated over this time from a wide range of businesses. I have used files ranging in length from hundreds of lines to billions of lines and I have gotten to know Tableau software pretty well. This work experience has allowed me to explore Tableau in many different ways and that history has given me the opportunity to write this blog starting in May, 2013. This blog post series describes what I have learned as a Tableau blogger over the past 15 months.
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How the Blogging Journey Began
Initially, I had no outline of what I was going to write about as shown in Figure 1, in which I state: “I have a lot to say, so I’ll get started with a little #Tableau training”. As you can see, the first topic I wrote about is based in statistical process control theory and the technique I demonstrate is how to make x-bar and R charts in Tableau.
This isn’t exactly the most compelling topic for your average Tableau user. I followed this up with classics such as “annual sales comp calculations” and “correlations and scatter plots”. Although these business techniques might appeal to a few readers, they are not exactly going to launch a new blog high into the blog-o-sphere. So I kept plugging away and quickly decided to do a little experimentation. I decided to write about a variety of topics to see which aspects of Tableau software would be of most interest to the expanding audience of Tableau users.
Over the past 15 months, I have written over 80 blog posts of which 60 of them are Tableau-focused. The topics covered ranged from mathematical modeling, to ETL (extract, transform and load) methods, to mapping approaches, to specific techniques I developed, as well as other things shown in Figure 2. I have now decided to analyze the results of my experiment to see if I can learn a few lessons about Tableau blogging.
Although I am tempted to be a total data geek in Part 1 of this blog post series, I will not bog this post down with an onslaught of Tableau-generated graphics (as tempting as this may be). I will maintain control in Part 1 of this series and I just summarize ten of my findings. In part 2 of this post, however, I use a bit of mathematical modeling and statistical analysis to support additional findings and conclusions, as well as showing some Tableau graphics. For Part 1, however, I will follow the advice of Detective Joe Friday from the Dragnet series when he used to say: “Just the facts, Ma’am, only the facts”.
To start, I must state the obvious. Tableau is a wildly engaging product(s) and is a phenomenal quantitative tool. As strange as it may sound, I think have an addiction to using Tableau! However, even with its incredible allure and scintillating growth, it is still just a software package. People experience this product while working on a computer. Nobody watches a weekly TV show called “The Tableau Files” (at least not yet!).
Therefore, for people to connect to your blog, you have to write about things that they want to learn. You have to produce posts that help people overcome problems that they are experiencing in real-time. So if you want people to read your blog, figure out where the difficulties are in using Tableau, find ways of overcoming these difficulties, and then clearly write about them by taking your time to explain your findings. With that as a general overview, here are the first ten lessons I have discovered along this journey.
- The vast majority of traffic to my blog arrives because of general search engine matches. Since Google has now hidden the search terms used, I cannot tell you specifically what people search on but you will get an idea of what those topics in part 2 of this post.Therefore, a key finding is that your blog post titles must be informative and contain key words that people will be searching for.
- Do not expect a large readership just after you publish a post. When a post is published, a few people may read it the first day but generally readership occurs steadily over time.There are exceptions to this, but because you are writing about specific topics in Tableau, there are only so many people that are interested in reading about that topic. Readership takes time because people are at different stages of learning Tableau and they will arrive at your post when the time is right for them. Also, your more advanced topics will likely have lower total readership than more general topics.
- Do not expect a lot of feedback /comments from your readership just because you write a blog. Write the blog for yourself, to share your knowledge, and to help others in the Tableau community. Don’t expect people to become your buddies by reading your blog like they might do with the CNN website or their local newspaper. Enjoy the process and know that somewhere in the world, when you least expect it, you just helped someone get over a hurdle they were having while learning or writing about Tableau.
- There are risks and rewards for how you approach your blogging mission. One approach is to avoid going too deep on any topic because Tableau is a very fluid software company. Tableau listens to their user base better than the vast majority of software companies do. Therefore, Tableau makes changes relatively rapidly to their products to improve the user experience and the software capabilities. In other words, you should understand that your blog masterpieces can quickly become functionally obsolete due to Tableau software updates. Tableau is still early in its product lifecycle so remember that when you are tempted to go really deep into a topic and become the master of that domain. Good examples of this are the upcoming improvements in the visual approach to understanding how advanced table calculations work, auto un-pivoting of data during the data load process, and auto parsing of delimited fields that have more than one variable included in the field. The counterpoint to the conservative approach is to go all-in in your mission. Strive to become the master of a technique of particular aspect of the software. There are plenty of examples of people that have done that and have been rewarded by Tableau for their expertise. If you want to become a Tableau Zen Master, for example, this might be a good approach to use. There are plenty of open topics for you to master including things like using Tableau with Alteryx or R, or even writing custom codes using the Advanced Programming Interfaces (API’s) that are now available. You can become a master of using the different types of available database connections or using different computer platforms such as Amazon Redshift or hadoop systems. There are plenty of open pathways for the upcoming blogger to make their mark.
- When beginning your blog, consider the following. Good blog posts can easily be overlooked early in your blog history because people do not know about your blog. Consider holding some of your better ideas for a while until you establish a bit of a readership. Although you might really want to post your best stuff first, understand that it really isn’t that important to post those things today. Nobody who visits a post really cares when it was written! Also, posts may have a tendency to get lost over time due to the nature of how blogs are structured and published, with the newest material on top and the oldest on the bottom. People generally do not go searching through your archives for things you wrote in the past. Understand that your older posts will most likely be found through general internet searches so be sure to follow #1 above.
- People don’t really care to read about personal-use cases of Tableau. Even if you write very interesting personal cases such as I did when I wrote about using Tableau to help the Doctor save my wife and baby during a high-risk pregnancy, most people will not read those types of posts. I also tested this concept with other personal examples that didn’t use Tableau and these posts were also largely ignored, although I think they are very interesting stories ( The Phone Call of a Lifetime or The Pinnacle of Pain). My advice is to avoid these types of posts in a technical blog and start another blog for topics like these.
- Sometimes things you write about do not get the readership you expect. Other times you might write something that you feel is obscure and you question why you even wrote it. My best example is: “I Wish #Tableau Had These Two Capabilities“. When I wrote that piece, I was positive that no one would ever read it. Now with nearly 2,400 views in under a year, I am continually astounded that people have found that post and continue to read it. The lesson is to not be afraid to write about things that don’t exist or are outside the realm of normalcy. These posts are creative and might trigger a response from your audience. Also, I suspect the word “wish” might be key in driving traffic to that post, although I have not tested that theory.
- If you quit blogging for a few months in a row, expect your readership to rapidly diminish. You need to stay relevant by publishing something every month at least, to keep yourself on the Tableau blog radar. I had a three-month hiatus due to an extreme work overload in late 2013 that taught me that lesson.
- Strive for true transparency in what you write about. Much of my best work is unpublished because of business confidentiality agreements. However, if it is possible for you to demonstrate techniques you created without sacrificing confidentiality, try to do so using hypothetical data or some other way of expressing your method. These posts will take longer to create because of the extra work needed but they will help you gain readership and will demonstrate your skills.
- Take the time to carefully consider your posts before publishing. Make sure that you clearly state the objective of the post, explain your findings, document the details, and provide links when possible to your materials so that others can use what you created. Jonathon Drummey is masterful in following this approach.
Upcoming in Part 2 of this Post
I promise to get quantitative in Part 2 of this post, particularly after unleashing this unsubstantiated and qualitative list of suggestions upon you. After all, aren’t we all interested in analytics? Although the work is mostly done, the complete story has not been discovered. Will it ever be written? We will see. Why would that be the case? Well, this blog post series is violating many of the suggestions listed above. First, I don’t think anyone will read this post(s). Why? Well, there are only a few dozen Tableau bloggers in existence. Therefore, my target audience is initially very small. Secondly, most of the existing Tableau bloggers already know what they are doing and are busy with their own blogging work, so why would they want to take the time to read about what I think? In fact, many of the existing Tableau bloggers will never see this post! Therefore, my initially small population is automatically much smaller than when I started writing this series. Lastly, this post doesn’t teach anything about using Tableau. In fact, the only reason I wrote Part 1 of this post is for #3 above.
Chances are good that I will write part 2 of this series, however, because I am the type of person that returns the shopping cart to the spot it belongs, even when it is across the parking lot and there is a driving rain storm and no one is watching what I do. It is called perserverence or stubborness (depending upon your point of view) and it is an innate characteristic that some people have. I like to finish the job because my Mom taught me how to do this by the way she lived her life. So for the three of you that have read this post in its entirety, thank you very much for reading!
Update on Part 2
Part 2 is now published, so click here if you want to continue…