Using #Tableau and Predictive Analytics on My Blog

Introduction

About three months ago, I used Tableau to build a predictive model for my blog readership. Today I checked the accuracy of that predictive model. This short article shows the results of this fairly simplistic work.


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The Prediction

In the two-part series I wrote about Lessons Learned as a Tableau Blogger (click for Part 1 or Part 2), I showed the growth of my blog over time in terms of the number of article views. The graphic I produced in September 2014 is shown in Figure 1, which also includes the coefficients of the second-order polynomial model.

Figure 1 -

Figure 1 – Growth curve for 3danim8’s blog.

 

In the text of Part 2, I said that this polynomial model could be used to estimate when this blog will have been read 50,000 (50K) times. By looking at the chart and the error bounds shown, it was clear that the 50K number would be achieved in December 2014, assuming the blog conditions remained the same over the time period (continue to publish new topics, etc).

Today, I used a previous helper guide I wrote for Tableau Models to estimate the date when the 50Kth read of the blog would happen. I programmed the polynomial equation in Excel to make the future readership predictions as shown in Figure 2.

Figure 2 - Using Tableau's polynomial model to predict the 50,000th read of the blog.

Figure 2 – Using Tableau’s polynomial model to predict the 50Kth read of the blog (on or about 12/7/14).

 The Results

The initial polynomial model has proven to be fairly accurate. The predicted date for the 50K view was about 12/7/14 as shown in Figure 2. The actual date of the 50K read was today, 12/8/14, as shown in Figure 3. The model was accurate to 1 day in over 3 months. This prediction is not too bad considering all of the variation and noise that goes into building a technical blog.

Figure 3 - The actual 50,000th read occurred on 12/8/14.

Figure 3 – The actual 50Kth read occurred on 12/8/14.

 

Future Prediction

The challenge for me will be to continue to produce enough interesting blog content to build additional readership. A lot of additional content will be necessary to continue this polynomial-type growth. I think that it is going to be really hard to maintain a second-order polynomial growth rate for this blog because I only publish original content and do not depend upon the work of others to build readership. So for the record, Figure 4 shows the prediction for blog growth over the next 12 months. That trend is going to take a lot of work to achieve!

 Figure 5 - The projected blog readership growth over the next 12 months.


Figure 4 – The projected blog readership growth over the next 12 months.

2 thoughts on “Using #Tableau and Predictive Analytics on My Blog

  1. Pingback: Andy Kriebel is a True #Tableau Zen Master | 3danim8's Blog

  2. Pingback: One Year Later – New Predictive Analytics for My #Tableau and #Alteryx Blog | 3danim8's Blog

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