WordPress is likely one of the hottest open-source web site making instruments which is vastly utilized by many bloggers together with myself. WordPress builders present tons of customized plugins to fulfil totally different wants. However not the entire plugins are effectively designed and secured.  One of the attention-grabbing items of data anybody who owns an internet site/weblog wants is their web site statistics. On this put up, I clarify learn how to analyse your WordPress web site stats in Energy BI. Earlier than I begin, I need to level out that there’s a WordPress stat already out there in WordPress Admin Dashboard which supplies very informative details about your weblog like Complete Views, At this time Views, Greatest Ever Views and so forth. You can even set up the WordPress app in your cellular machine to simply entry your web site stats. However, the stats WordPress offers me in not sufficient. I would like extra. I want a extra detailed evaluation on

  • Present Month vs. Final Month
  • Present 12 months Vs. Final 12 months
  • Most Common Day of Week
  • Most Common Month of 12 months
  • High 10 Posts

and so forth.

As non of the above evaluation can be found within the regular stats , I made a decision to construct my very own model of “WordPress Web site Stats Evaluation in Energy BI”. This provides me the pliability of making as a lot evaluation as I want , and… it’s so a lot enjoyable.

In the event you personal a WordPress weblog or every other kind of web sites or should you’re simply curious to discover ways to use an internet site API in Energy BI, then this put up is for you.

I managed to create a Energy BI Desktop template which you can obtain and use it without spending a dime. You’re welcome to switch it primarily based in your wants. You will discover the obtain hyperlink on the button of the web page.

To have the ability to analyse your WordPress stats in Energy BI it is advisable personal a WordPress weblog or web site. Then a WordPress API key’s assigned to your account. The important thing was included in your WordPress Welcome Electronic mail. You should use that API key in Energy BI Desktop to create your customised reviews and analyse your weblog/web site stats then you’ll be able to publish the mannequin into Energy BI Service that’s accessible anytime anyplace. You can even create your individual dashboard in Energy BI Service.  Furthermore, you’ll be able to setup Schedule Refresh for the dataset to refresh your dashboards and reviews robotically.

You’ll must

  • personal a WordPress weblog/web site and have the API assigned to your account

  • set up the Jetpack plugin in your weblog/web site as WordPress stats is not maintained and you shouldn’t use it. As a substitute, you’ll be able to set up the Jetpack plugin

As I discussed earlier the API key’s included within the Welcome e-mail you acquired if you registered your weblog/web site with WordPress. Nonetheless, you may not have that e-mail anymore. You will get it from Akismet web site.

The opposite manner prime discover it’s out of your account if you login utilizing your admin account, then click on “Akismet” from “Jetpack” menu from left pane and also you’ll discover the API key below “Settings” part.

You will get WordPress stats API from right here: http://stats.wordpress.com/csv.php

If you click on the above URL you see an inventory of “GET” parameters out there which you’ll generate totally different queries to get totally different datasets. To construct your question use the next generic URL development:


So, to get knowledge about put up views for 30 days the above URL will appear to be this:


  • If you wish to get all knowledge about put up views ever then use desk=postviews&days=-1
  • To get all knowledge of your referrers then desk=referrers&days=-1
  • To get search phrases knowledge then desk=searchterms&days=-1

In the event you copy/paste the URLs above in your browser you need to get the info you’re searching for.

Learn extra at “phoxis.org“.

Constructing a Energy BI mannequin is pretty straightforward. We simply must load knowledge utilizing the URLs above and a Date desk for certain. To take action:

  • Open Energy BI Desktop
  • Click on “Get Knowledge”
  • Discover and click on “Net” then “Join”
  • Paste the URL to get put up views knowledge then click on OK
  • Click on “Edit” within the subsequent web page. This navigates you to the Question Editor
  • As you see Energy Question already promoted the primary row as column names
  • Rename the question to “Views” then click on “Apply”

You might repeat the above course of to get “Referrers” and “Search Phrases” knowledge as effectively. For the sake of this put up I preserve it so simple as potential and keep it up with solely “Views” desk.

Subsequently it’s possible you’ll click on “Shut & Apply”.

The subsequent step, as talked about earlier, is to create a “Date” desk.

  • Shut the “Question Editor” and return to Energy BI Desktop
  • Click on “Modeling” tab then click on “New Desk”
  • Sort within the following DAX code then press Enter
Date = var dateTable = CALENDAR(DATE(YEAR(MIN(Views[Date])),1,1), DATE(YEAR(TODAY()), 12,31))
SELECTCOLUMNS(dateTable, "Date", [Date]
, "12 months", YEAR([Date])
, "Month", FORMAT([Date], "MMMM")
, "MonthOrder", MONTH([Date])
, "12 months - Month", FORMAT([Date], "YYYY-MMMM")
, "YearMonthOrder", VALUE(FORMAT([Date], "YYYYMM"))
, "Week", CONCATENATE("Wk-", FORMAT(WEEKNUM([Date], 2), "00"))
, "12 months - Week", YEAR([Date]) & " Wk-" & FORMAT(WEEKNUM([Date]), "00")
, "Week Day", FORMAT([Date], "DDDD")
, "WeekDayOrder", WEEKDAY([Date], 2)
  • The code above creates a easy Date dimension ranging from 1st Jan of the beginning yr as much as thirty first Dec of the present yr. The rationale for that’s that now we have to cowl the entire date vary to make certain Time Intelligence features work exactly.
  • Click on “Mark as Date Desk” from “Modeling” tab
  • Choose “Date” column from the drop-down listing and ensure the date desk is validated efficiently, then click on OK
  • Conceal “MonthOrder” and “YearMonthOrder” columns from “Date” desk as we created these columns to kind “Month” and “12 months – Month” columns
  • Click on “Month” column then click on “Kind by Column” from “Modeling” tab and tick “MonthOrder”. This ensures that Months names are all the time proven in the proper order.
  • You might do the identical for “12 months – Month” column and kind it by “YearMonthOrder”
  • Create a relationship between “Views” and “Date” tables on ‘Views'[date] and ‘Date'[Date] columns by clicking “Handle Relationships” button from “Modeling” tab
  • Click on “New”
  • Choose “Date” from the primary drop-down listing
  • Choose “Views” from the second drop-down
  • Choose “Date” column from “Date” desk and “date” column from “Views”
  • Make certain “Cross filter course” is ready to “Single” then click on OK
  • Shut the “Handle relationships” window
  • Broaden “Views” tables and conceal “post_id” column as we don’t want it now

To this point we created our mannequin. Now it’s time to create some helpful measures to analyse our WordPress web site stats.

Now you can create some measures to get extra insights about your web site stats.

Beneath is an inventory of attention-grabbing measures it’s possible you’ll create or maybe you want much more that aren’t included within the listing:

  • General Views: Reveals whole variety of web site views from the start
  • Complete Views: Reveals variety of web site views
  • Most Common Month: Reveals Hottest month together with variety of views on that individual month
  • Hottest Week: Identical calculation, however, for week numbers
  • Most Common Day: Identical as “Most Common Month”, however, at day stage
  • Most Common Submit: Reveals the preferred put up together with variety of views
  • Views MTD: MTD stands for “Month to Date” which reveals cumulative variety of views from the start of month until present date. The quantity resets firstly of every month.
  • Views YTD: YTD stands for “12 months to Date” which reveals cumulative variety of views from the start of yr until present date, The quantity resets at first day of every yr
  • Views LMTD: LMTD stands for “Final Month to Date” which reveals cumulative variety of views from the start of earlier month until similar date as present date within the earlier month. The quantity resets firstly of every month.
  • Views LYTD: LYTD stands for “Final 12 months to Date” which reveals cumulative variety of views from the start of earlier yr until similar date as present date within the earlier yr. The quantity resets firstly of every yr.
  • Views LY MTD: LY MTD stands for “Final 12 months Month to Date” which reveals cumulative variety of views from the start of similar month as present month in earlier yr until similar date as present date. The quantity resets firstly of every month.

With the above measures you’ll be able to simply construct very informative reviews in Energy BI to see how your WordPress web site performs.

For example you’ll be able to examine “Views MTD” and “Views LY MTD” to see how your web site is doing in present month in examine with the identical interval final yr.

I Constructed the Energy BI report and made the Energy BI Template out there for obtain.

Obtain “WordPress Stats Analyser” right here.

Simply open the PBIT file then copy paste the API URL of your web site which is defined earlier on this put up.

Trying on the above report you’ll be able to rapidly see how your web site improved over time, what’s the hottest month, the preferred week and the preferred date. You can also see the evaluation of your web site recognition over months. Within the pattern above you see that the preferred month is March with about 11% of whole views of the web site, whereas July is the least fashionable month with about 7% of whole views.

In the event you hover over the three center visuals you’ll see extra insights constructed utilizing Web page Tooltips.

I hope you get pleasure from this Energy BI Template. I’m actually curious to see the way you enhance the report, so please let me know within the feedback part under the way you made it a greater report.


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