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--- admin:site_analytics [2020/07/10 02:58]
mchung [Things to know beforehand]
+++ admin:site_analytics [2020/07/10 08:15] (current)
mchung [Users and sessions - How many users, how long they're staying, and how much of the site they're using]
@@ Line 25: / Line 25: @@
   * Are you trying to understand CKAN or WP usage?
   * How many users and where do they come from?
-  * What do they do when they arrive on the site?
   * Do they specifically come to the site or are we showing up as a search result from their research online? What are the terms they are searching for?
+  * What do they do when they arrive on the site?
   * How long do they stay?
   * Which areas of the platform are they most interested in?
@@ Line 80: / Line 80: @@
   * Admin of the site as well as those working on donor reporting should already have access permission to Google Analytics. To request access, contact an ODI administrator.
+  * For donor reporting, it can be useful to break down the data by quarter. If you want to do this, it is best to download data on each quarter separately. This is because each data point which is downloaded for a specific temporal range is dated with the same range, thus if you set the temporal range for October 1, 2016 to September 30, 2017, it cannot be separated into week, month, or quarter.
 ==== Glossary of terms ====
-  * **Users**: Google Analytics calculates the number of users based on a cookie that is set by the user’s browser. That means if a user accesses the website from a different browser or device, he/she might be counted as multiple users. Google Analytics used to offer “Users” as the unique number of visitors who visit a site. The number used to represent exactly how many individual people were on the site. This is no longer the case. If you're interested, see more here:[[https://support.google.com/analytics/answer/2992042?hl=en&authuser=2]].
+  * **Users**: Counter to expectations, this is not a count of unique users on the platform. Google Analytics calculates the number of users based on a cookie that is set by the user’s browser. That means if a user accesses the website from a different browser or device, he/she might be counted as multiple users. Google Analytics used to offer “Users” as the unique number of visitors who visit a site. The number used to represent exactly how many individual people were on the site. This is no longer the case. If you're interested, see more here:[[https://support.google.com/analytics/answer/2992042?hl=en&authuser=2]].
   * **Sessions**: A session is a group of interactions by one user with the site that take place within a given time frame. One unique visitor may initiate multiple sessions in a day.  Sessions are typically refreshed after 30 minutes of inactivity. If you're interested, see more here:[[https://support.google.com/analytics/answer/2731565?authuser=2]]
@@ Line 97: / Line 98: @@
   * **Source**: The origin of traffic to the site, such as a search engine or a domain.
-  * **Medium**: General category of the source, such as organic, referral, email, or none.
+  * **Medium**: General category of the source, including organic, referral, email, or none.
   * **Referral traffic**: This is traffic that arrives on the site through another source, such as a link on another domain. Analytics automatically recognizes where traffic was immediately before arriving on the OD platform site, and displays the domain names of these sites as sources.
@@ Line 106: / Line 107: @@
   * Select your country instance under **Analytics Account** > OD instance > OD instance > **Master**
-**Note**: **Unfiltered** data contains spam data. Always choose **Master**.
+Note: **Unfiltered** contains spam data. Always choose **Master**.
 {{:admin:screen_shot_ga_access.png?400|}}
-===== Google Analytics for CKAN statistics =====
-  * Go to: https://analytics.google.com and sign-in
+==== User acquisitions - Where do users of the OD platform come from? ====
-  * Select your country instance under **Analytics Account** > OD instance > OD instance WordpressGA > OD instance Wordpress views
-{{:admin:screen_shot_ckan_ga_access.png?400|}}
+User acquisition data tells the source of traffic and the medium through which users came to the OD platform for the reporting period. A source can be either a search engine (Google) or a domain (www.mekongeye.com). Mediums include:
-===== CKAN for CKAN statistics =====
+  * Direct (a user typed the OD platform URL into the web browser)
+  * Organic search (A user clicked on the OD platform link from a search engine source such as Google)
+  * Cost-per-click search (A user clicked on a paid link from a search engine source such as Google)
+  * Email (A user clicked on a custom medium link made by OD)
+  * Referral (A user clicked a link published on an external website, inclusive of social media platforms, link contained in a non-OD e-mail newsletter)
+Since the OD platform hosts six interlinked websites, we can demonstrate how much traffic one OD site  directs to another OD site (eg. ODL to ODM). This **traffic** is measured by **number of sessions**.
+**Referral** data is also useful to understand how much traffic to the site has been directed from a partner organization's site (eg. Global Forest Watch to ODC).
-<WRAP center round info 90%>
+=== Accessing user acquisition data ===
-ODM data from October 1, 2016 to September 30, 2017 will be used for the following step-by-step demonstration.
-</WRAP>
-==== User acquisitions ====
-User acquisition data tells the source of traffic and the medium through which users came to the OD platform for the reporting period.
-There are three types of source:
-  * Direct (through entering the OD platform URL into the web browser)
-  * Organic (through search engine such as Google, Bing, Yahoo ... etc., which are called medium)
-  * Referral (through a link published on an external website, inclusive of social media platforms, link contained in an e-mail or newsletter)
-Since the OD platform hosts six websites and each is making linkages to another, we want to demonstrate how much traffic to one of the OD site is directed from other OD sites. For example, how much traffic to ODM is directed from OD country instances. This **traffic** is measured by **number of sessions**.
-Referral data is also useful if we want to measure how much traffic to the site has been directed from a partner organization's site. For example, how many sessions to ODC has been directed from the Global Forest Watch or a Cambodian government websites.
-=== Basic user acquisition data ===
-Basic referral data is readily available on Google Analytics. It is accessible through this path: Acquisition > Overview (you should see this page: https://analytics.google.com/analytics/web/#report/trafficsources-overview/)
+User acquisition data is readily available on Google Analytics. It is accessible through this path: Acquisition > Overview
-{{ :partners:traffic.png?nolink&700 |}}
+{{ :admin:screen_shot_acquisition_overview_ga.png?600 |}}
 From this **acquisition overview** page, you can find macro data on traffic source and number of sessions associated with each source. If this level of data is all you need, download the data by clicking on Export. You may save the file as CSV, Excel, Google Sheet, or PDF.
-{{ :partners:download_ga.png?nolink&700 |}}
+{{ :admin:screen_shot_export_options_ga.png?600 |}}
 Assuming you save the file as CSV, Excel, or Google Sheet, you will see:
-{{ :partners:traffic_data.png?nolink&700 |}}
+{{ :admin:screen_shot_xlsx.png?600 |}}
-The same process can be done to access broad data on traffic to OD platform from social media and social network sites.
+You can also access broad data on traffic to OD from social media and social networking sites. Follow this path: Acquisition > Social.
-{{ :partners:traffic_social.png?nolink&700 |}}
+{{ :admin:screen_shot_social_overview.png?600 |}}
 === User acquisition data disaggregated by source and medium ===
-Disaggregated data helps us answer the following questions:
+Disaggregated data helps us to answer the following questions:
   - What are some of the most popular search engines our users used?
   - How much **traffic** to OD platform is directed from other OD sites?
   - How much **traffic** to OD platform is directed from data partner websites?
-  - How much **traffic** to OD platform is directed from government / media / academic website?
+  - How much **traffic** to OD platform is directed from government / media / academic websites?
-Below is a step-by-step guide on how to download and analyze traffic data to show direct traffic, organic search, and traffic via referrals from OD platform and social media. Using the method below, you may also analyze how much traffic to OD platform comes from government, media, academic, NGOs, etc.
+Below is a step-by-step guide on how to download and analyze traffic data to show direct traffic, organic search, and traffic via referrals from the OD platform and social media. Using the method below, you can also analyze how much traffic to OD platform comes from government, media, academic, NGOs, etc.
 **Step 1: Download raw data**
   * Go to **Acquisition** > **All traffic** > **Source/Medium**.
-{{ :partners:raw_aquisition_ga_1.png?nolink&800 |}}
+{{ :admin:screen_shot_sourcemedium_all_traffic.png?600 |}}
   * Do not click export yet. Scroll all the way down to the data table.
-{{ :partners:aquisition_raw_one_page.png?nolink&800 |}}
+{{ :admin:screen_shot_souremedium_data_table.png?600 |}}
 <WRAP center round info 60%>
 Only the visible data is downloaded. In this case, only 10 rows of data would be downloaded if you clicked Export.
-Change the number of visible row to a number that is more than the total number of rows. In this example, choose 250 (there are 246 rows in total).
+Change the number of visible row to a number that is more than the total number of rows. In this example, choose 50 (there are 41 rows in total) {{ :admin:screen_shot_choose_50.png?200 |}}.
 </WRAP>
-{{ :partners:aguisition_data_raw_all.png?nolink&800 |}}
   * Scroll back up and click **Export** and save as Excel or Google Sheet.
-{{ :partners:aquisition_data_raw_excel.png?nolink&800 |}}
+{{ :admin:screen_shot_all_traffic_sourcemedium_googlesheets.png?600 |}}
 **Step 2: Working with raw data**
-  * Copy the data to a Google Sheet. See [[https://docs.google.com/spreadsheets/d/1I_Hsqmq_lLzrqOp2qfpxPnEO6h1CMKOPptCq2uazUTw/edit#gid=0|this sheet on Google Drive]].
+  * Copy the data to a new tab in Google Sheet, or if you downloaded an .xlsx file you can copy the data to a new Google Sheet. See [[https://docs.google.com/spreadsheets/d/1ef1E_o0LFmtqB0ibbrB8Fy_8-LNtfiyzCghSp1eDKkI/edit?usp=sharing|this sheet on Google Drive]].
-  * Take note of the **totals** for data verification later. Note that the total number of sessions from all traffic is 35045.
+  * Take note of the **totals** for data verification later. Note that the total number of sessions from all traffic is 2792.
-  * Delete the total and unrelated data. In this example the rows and columns which have been highlighted.
+  * Delete the total and unrelated data. See below image; here it would be the rows and columns that have been highlighted, as well as the metadata that would show up above the header row.
-{{ :partners:acquisition_data_gsheet.png?nolink&800 |}}
+{{ :admin:screen_shot_delete_unecessary_data.png?600 |}}
   * Add two new columns to the right of **Source / Medium** (column A). You should have column B and C blank.
   * Copy **Source / Medium** column and paste it into column B.
-Select column B > go to Data > Split text to columns > Split by "/" sign.
+  * Select column B > then go to Data > Split text to columns > custom > enter "/" sign. You should now have the following:
-You should have the following:
-{{ :partners:aquisition_split_text_to_data.png?nolink&800 |}}
+{{ :admin:screen_shot_split_by_slash.png?600 |}}
-This is data from ODM site. Thus the medium for "direct" is opendevelopmentmekong.net
+Since this is data from ODM, the medium for "direct" is opendevelopmentmekong.net
 **Step 3: Determine data you want to identify**
@@ Line 216: / Line 202: @@
   * Use the filter function to view data by **Medium**.
-  * Assign appropriate categories.
+  * Assign appropriate categories (e.g. government, media, NGOs, etc.).
 <WRAP center round tip 90%>
-If you want to analyze how much traffic to OD platform comes from government, media, academic, NGOs, etc., you will need to transform data in the **Source** column by associating .edu with Academia, .gov with Government, .org = NGOs and so on. For media organization, you will need to perform a text search to find match with news website URL. This manual data transformation might produce some inconsistency. Make sure you double-check the work and get a colleague to help reproduce the data using your method."
+If you want to analyze how much traffic to OD platform comes from government, media, academic, NGOs, etc., you will need to transform data in the **Source** column by associating .edu with Academia, .gov with Government, .org = NGOs and so on. For media organizations, you will need to perform a text search to find matches with news website URLs. Because this is a manual data transformation, there is an increased chance of inconsistency. Best practice would be to double-check the work and get a colleague to help reproduce the analysis using your method.
 </WRAP>
+{{ :admin:screen_shot_filtered_by_referral_source_analyzed.png?600 |}}
-{{ :partners:source_analyze_organic.png?nolink&800 |}}
 <WRAP center round important 80%>
-ODC and ODMm uses opendev[country].net as well as the default URL country.opendevelopmentmekong.net. Make sure to count traffic from both as traffic directed from the OD platform. There are traffic directed from PP site and ODM Wiki to PROD. For reporting purposes, this traffic doesn't need to be identified.
+The various OD sites use either opendevelopment[country].net or the default URL country.opendevelopmentmekong.net. Both count as traffic from the OD platform. There may also be traffic directed from PP site and ODM Wiki to PROD. For reporting purposes, this traffic should not be identified.
 </WRAP>
-{{ :partners:aquisition_data_od.png?nolink&800 |}}
+  * Now that the categorization is complete, use Pivot table function to count number of sessions for each medium. Make sure the grand total is the same as the number provided in the raw data (in this example 2792).
-  * Now that the categorization is complete. Use Pivot table function to count number of sessions for each medium. Make sure the grand total is the same as the number provided in the raw data (in this example 35045).
+{{ :admin:screen_shot_pivot_table_sum_sessions_source.png?600 |}}
-{{ :partners:aquisition_pivot.png?nolink&800 |}}
 **Step 5: Analyze / visualize data**
-Below is an example of how this data can be presented.
+Now you're ready to analyze and visualize the data.
-{{ :partners:user_aquisition_report.png?nolink&400 |}}
 <WRAP center round tip 90%>
@@ Line 245: / Line 226: @@
 </WRAP>
-==== Users and sessions ====
+==== Users and sessions - How many users, how long they're staying, and how much of the site they're using ====
-=== Things to know beforehand ===
+=== Basic user and session data ===
-**Temporal range**: For donor reporting, it's useful to breakdown the data by quarter. In the example below, we will gather data from October 1, 2016 to September 30, 2017, which are four quarters:
+Please see the [[admin:site_analytics#glossary_of_terms|Glossary of terms]], above, for basic definitions of these indicators.
-  * Quarter 4, 2016: October 1 to December 31, 2016
-  * Quarter 1, 2017: January 1 to March 31, 2017
-  * Quarter 2, 2017: April 1 to June 30, 2017
-  * Quarter 3, 2017: July 1 to September 30, 2017
-<WRAP center round tip 90%>
+**Users**: This data can be desegregated by **returning** and **new** to identify how many user cookies have been set over the reporting period.
-Each data point which is downloaded for a specific temporal range is dated with the same range, thus if you set the temporal range for October 1, 2016 to September 30, 2017, it cannot be separated into week, month, or quarter. It's a good practice to define the specific temporal range segments and download the data for each segment.
-</WRAP>
-=== Basic user and session data ===
+**Sessions**: Session data can be broken down by the following:
+  * **Average session duration** data shows Average time returning and new users spent on the Platform, calculated by the date range specified divided by total number of sessions
-**Users**: Gather data to show how many users, desegregated by **returning** and **new** users, have visited the OD platform over the reporting period.
+  * **Page / Session** data shows the average number of pages on the Platform viewed per session
+  * **Bounce rate** shows the percentage of users who viewed only one page compared to the total number of users.
-**Sessions**: A session is a group of interactions by one user with the site that take place within a given time frame. One unique visitor may initiate multiple sessions in a day.  Sessions are typically refreshed after 30 minutes of inactivity.
+You can read further [[https://support.google.com/analytics/answer/1033861?hl=en&authuser=2|here]].
-  * **Average session duration** data shows Average time returning and new users spent on the Platform
-  * **Page / Session** data shows Average number of pages on the Platform viewed per session by returning and new users
-  * **Bounce rate** shows how likely returning and new users on average to exit the Platform after viewing only one page.
 <WRAP center round info 90%>
@@ Line 272: / Line 245: @@
 </WRAP>
+{{ :admin:screen_shot_audience_overview.png?600 |}}
-{{ :partners:users_sessions_lumsum.png?nolink&700 |}}
@@ Line 606: / Line 578: @@
+===== Google Analytics for CKAN statistics =====
+  * Go to: https://analytics.google.com and sign-in
+  * Select your country instance under **Analytics Account** > OD instance > OD instance WordpressGA > OD instance Wordpress views
+{{:admin:screen_shot_ckan_ga_access.png?400|}}
 ===== CKAN for CKAN statistics =====

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