Frequently Asked Questions

The Editorial Insights Tool is a plug-and-play solution that gives publishers insights into content performance within key audience segments.

The dashboard uses the following metrics to assess content performance:

  • Completion Rate: % of pageviews where the entire article was read
  • Recirculation Rate: % of article pageviews that lead to another pageview
  • Segment Pageviews: % of article pageviews that came from priority segments: Fans and Engaged Users

By evaluating content performance based on these metrics and the article's overall Engagement Score, the EIT Dashboard aims to help publishers engage and grow their reader base.

Articles are typically ranked based on the metric of pageviews alone. EIT recognises that there are a number of ways an article can be successful in garnering engagement. If an article has low pageviews but a high completion rate, this article is engaging and should be amplified by the publisher. Pageviews, completion rate and recirculation rate should be considered equally important and not assessed in isolation.

To take all three metrics into account, EIT ranks articles by a new metric: Engagement Score.

Each article is given a score from 1-10 against each of the three metrics, based on how it performed compared to all other articles in the set.

The set of articles is split into 10 quantiles, with 1 being the lowest value in the set and 10 being the highest value in the set. So, the article with the lowest pageviews would be given a score of 1 and the article with the highest pageviews would be given a 10.

This same scoring system is applied for recirculation rate and completion rate, resulting in three scores for each article.

These three scores are then averaged to give the Engagement Score on a scale of 1-10.

Within the dashboard, articles are ranked based on Engagement Score. Top Articles have the highest Engagement Scores and Bottom Articles have the lowest Engagement Scores.

In the Take Action page, the engagement metrics are presented within the RORA framework. This helps publishers action the insights provided by the dashboard.

The RORA framework is comprised of the following tables:

  • Replicate: stories that have ↑ high pageviews and ↑ above average completion rates.
  • Optimize: stories that have ↑ high pageviews but ↓ lower than average completion rates or ↓ lower than average recirculation rates.
  • Reconsider: stories that have ↓ low pageviews and ↓ lower than average completion rates.
  • Amplify: stories that have ↓ low pageviews and ↑ above average completion rates or recirculation rates.
  1. Check that you have the required GCP permissions on the Google account you are using to set up the dashboard.
  2. Check that the BigQuery Transfer Service API is enabled on the relevant GCP project. See steps on how to enable the API here.
  3. Try running the Setup Wizard with your browser in Incognito or Private Browsing mode. This will usually overcome any conflicting authorization settings stored in your cookies.
  4. If you are still unable to find a solution, reach out to the EIT team using the help widget at the bottom left of the screen.
  1. If you have just finished setting up the dashboard, the data will not appear approximately for 1-2 hours. This is because the scheduled query that analyses your GA360 BigQuery dataset takes some time to complete on the first run.
  2. Check that your Publication Date custom dimension is in one of the recommended formats:

    • YYYY-mm-dd
    • YYYY/mm/dd
    • dd-mm-YYYY
    • dd/mm/YYYY
    • dd-mm-yy
    • dd/mm/yy
    • YYYYmmdd
    • ddmmYYYY

  3. In your BigQuery Project, go to Scheduled queries > editorial_insights_vn.n.n > RUN HISTORY and look for any query errors. There may have been an issue with parsing another one of your custom dimensions.
  4. If you are still unable to find a solution, reach out to the EIT team using the help widget at the bottom left of the screen.

  • Where is my data stored?

    Data is stored within the publisher’s own BigQuery project, as a separate dataset. As all EIT data is stored in a new dataset, your existing data will not be overwritten.

  • Who can access my data?

    Only those with access to your BigQuery Project can access the data. No access permissions need to be granted to EIT for the dashboard to be created. EIT cannot access your other BigQuery datasets.

  • How are you processing Data?

    The query is run within your own BigQuery Project. Self-containment of query processing ensures the security of your data. However, it does mean that there are BigQuery costs associated with dashboard use.

To set up the dashboard you will need the following IAM permissions in Google Cloud Platform (GCP):

  • bigquery.datasets.create
  • bigquery.datasets.get
  • bigquery.datasets.update
  • bigquery.jobs.create
  • bigquery.tables.create
  • bigquery.tables.get
  • bigquery.tables.getData
  • bigquery.tables.list
  • bigquery.transfers.get
  • bigquery.transfers.update
  • resourcemanager.projects.get
  • resourcemanager.projects.getIamPolicy
  • servicemanagement.services.bind
  • serviceusage.services.enable
  • serviceusage.services.get
  • serviceusage.services.list

In GCP you can create a custom role (e.g. EIT Admin) with these specific permissions.

Or, you can grant the following roles that include these permissions:

  • BigQuery Admin
  • Project IAM Admin
  • Service Management Administrator
  • Service Usage Admin

The following IAM permissions in Google Cloud Platform (GCP) are required for a user to access and view the dashboard:

  • bigquery.jobs.create
  • bigquery.tables.getData
  • bigquery.tables.get

The easiest way to grant these permissions to a user is the give them the Basic Viewer role.

However, we recommend creating a Custom Role called "EIT User" with these three permissions. This role can then be granted to anyone in your team who needs to use the dashboard.

In order to grant a user permissions in Google Cloud Platform, that user's email address must be a Google Account.

Create a Google Account with an existing email

  1. Go to Create Your Google Account.
  2. Under "Username", select "Use my current email address instead".
  3. Enter your email address.
  4. Set a password and verify as instructed.

Why do I receive an error message that my email is "already in use"?

If you receive this error message, your email address may be listed as an alternate email address to another Google Account.

This can sometimes happen if you have a personal Google Account as well as a corporate email account.

To set up your email address as its own Google Account:

  1. Go to Alternate Emails in your Google Account.
  2. In the list of alternate emails, remove the alternate email address (the email address that you would like to use as a separate Google Account).
  3. Wait 5-10 minutes, then follow the steps above to Create a Google Account with your preferred email address.

Follow these steps to enable the BigQuery Data Transfer Service API.

  1. Open the BigQuery Data Transfer Service API page in the cloud console.
  2. From the dropdown menu at the top of your screen, select the project that will be connected to the dashboard. This is the project where the GA360 data set is exported.
  3. Select ENABLE to enable the API.

The dashboard stores data in BigQuery and runs queries against that data.

The costs associated with running the dashboard will be incurred through the storage and usage costs of BigQuery.

The costs will appear in the billing account linked to your BigQuery project.

Storage Costs

$0.02 USD per GB per month ($20USD per 1TB).
For data which was not queried in a particular month, storage is discounted by 50%.

Scenario 1: someone loaded 1TB of data on 15th of April. Estimated cost for April = $20 USD.
Scenario 2: no one queried data from Scenario 1 in May. Estimated cost for May = $10 USD.
Scenario 3: 1st June someone added to the same table another 1TB of data, but no queries were run on old data. Estimated cost for June= $30 USD ($20 USD for new 1TB, $10 USD for old data).

Usage Costs

Querying 1TB of data costs $5 USD. (100GB $0.5, 10GB $0.05 )
There is cache - if you execute same query twice, there is no charge the second time.
There is no charge for queries which were not executed (due to errors).

Scenario 1: someone executed 3 different queries and each query consumed 10GB. Estimated cost = $0.15 USD.
Scenario 2: someone executed the same query 5 times and the initial query consumed 10GB. Estimated cost = $0.05 USD.

The Your Editorial Insights pages give you an overview of engagement with your site, segmented by Recency, Frequency and Visits. These pages should be used to analyse differences in traffic and content performance between segments.

Yesterday Page: Use this page to easily check in on yesterday’s content performance and identify what worked and what could be improved. Remember that these pages can be filtered by Category or Author, so you can review them in your daily content planning meetings within your team.

Last 7 Days: Use this page to easily check in on the last week’s content performance and identify what worked and what could be improved. Remember that these pages can be filtered by Category or Author, so you can review them in your weekly content planning meetings within your team.

Last 30 Days: Use this page to easily check in on the last 30 days’ content performance and identify what worked and what could be improved. Remember that these pages can be filtered by Category or Author, so you can review them in your monthly content planning meetings within your team.

Fans Segment

Fans are your most loyal and consistent readers.

Users in this segment match the following conditions over the last 30 days:

  • >=30 sessions
  • >=60 pageviews
  • <=3 days since last session

Use Case: Use this segment to identify the kind of content that your loyal readers love. Replicate these types of articles to keep your Fans engaged and active on your site.

Engaged Segment

Engaged readers are frequent visitors to your site that consume a high number of articles.

Users in this segment match the following conditions over the last 30 days:

  • >=15 and <30 sessions
  • >=20 and <60 pageviews
  • <=15 days since last session

Use Case: These readers consume a lot of content, so they have the potential to become Fans. Use this segment to replicate content that Engaged readers enjoy to move them up the engagement curve.

Semi Engaged Segment

Semi Engaged readers visit your site now and again and consume some articles.

Users in this segment match the following conditions over the last 30 days:

  • >=5 and <15 sessions
  • >=5 and <20 pageviews
  • <=20 days since last session

Use Case: These readers have the potential to become more engaged with your site. Use this segment to identify and replicate content that is working well to attract interest from new readers.

Fly Bys Segment

Fly Bys are once-off visitors to your site.

Users in this segment match the following conditions over the last 30 days:

  • 1 session
  • <=2 pageviews
  • <=30 days since last session

Use Case: These readers only read a couple of articles on your site and never returned. Use this segment to identify the content that generates new traffic to your site and to improve your content offering to keep these readers coming back.

Users: the number of unique visitors that had a session on your site in the time period.

Pages per User: the average number of pages viewed by individual users throughout the time period.

Recirculation Rate: the percentage of readers that came from another article. This metric is calculated as (1-%Exits).

Completion Rate: the percentage of pageviews where the entire article was read. This metric is calculated as (Total Article Completions / Total Pageviews). In the Setup Wizard, you can configure the dashboard to measure "completions" based on your own tracking configuration. A completion could be a 100% scroll event, a 90% scroll event or an event that fires on complete scrolls only. Whatever is used in your newsroom can be used to measure completion rate in EIT.

Engagement Score: a score out of 10 given to each article, based on performance against the three engagement metrics (pageviews, recirculation rate and completion rate). Each article is given a ranking against the other articles on your site for each of the three metrics, with 10 being the highest score and 0 being the lowest score. These three scores are then averaged to provide the Engagement Score for the article.

The number of daily users throughout the selected time period within each segment.

Use Case: this chart can be used to observe trends within each segment. For example, which social push may have caused a spike in Fly Bys on a particular day?

The number of daily pageviews throughout the selected time period within each segment.

Use Case: this chart can be used to observe trends within each segment. For example, which article on the homepage may have caused a spike in Fans pageviews on a particular day?

Common FAQ: why are Fly Bys pageviews lower than Semi Engaged pageviews if I have more Fly Bys? While there will often be more Fly Bys than Semi Engaged users, Fly Bys pageviews can be less than Semi Engaged pageviews. This is because Fly Bys as less engaged, so they have less pages per session than Semi Engaged readers. As such, the total pageviews for Fly Bys can be less than those for Semi Engaged readers.

These are your most engaging articles. Rather than ranking articles by pageviews alone, EIT ranks articles based on Engagement Scores.

The Engagement Score is a score out of 10 given to each article, based on performance against the three engagement metrics (pageviews, recirculation rate and completion rate). Each article is given a ranking against the other articles on your site for each of the three metrics, with 10 being the highest score and 0 being the lowest score. These three scores are then averaged to provide the Engagement Score for the article.

Use Case: this chart provides an overview of article performance across segments. What did well with Fans, but not as well with Fly Bys? How might this impact your strategy within channels designed to attract new readers (for example, social channels)?

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

Common FAQ: why are Fly Bys Pageviews lower than Fans Pageviews, if I have more Fly Bys? An article may attract a lot of Fans but not a lot of Fly Bys. This is a good indication of which audience your article is attracting: if Fans Pageviews are higher than Fly Bys Pageviews, this means the article appeals more to your loyal readers than your once-off readers.

These articles did not produce high engagement. Rather than ranking articles by pageviews alone, EIT ranks articles based on Engagement Scores.

The Engagement Score is a score out of 10 given to each article, based on performance against the three engagement metrics (pageviews, recirculation rate and completion rate). Each article is given a ranking against the other articles on your site for each of the three metrics, with 10 being the highest score and 0 being the lowest score. These three scores are then averaged to provide the Engagement Score for the article.

Use Case: this chart provides insights into what isn't attracting your most loyal readers. Keep in mind that this does not mean these articles were unsuccessful; they simply did not generate traffic within the Fans segment. How might this affect your social strategy? If these articles performed poorly with Fans but performed well with Fly Bys and Semi Engaged Readers, push them on your social channels to attract new readers.

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

The Take Action page provides your newsroom with recommendations on content development.

Article performance is assessed based on the Last 7 days of traffic to your site. The Take Action page is designed to cater to current site performance and to make actionable recommendations.

The Top Performing and Replicate tables feature articles that your readers loved.

The Optimise, Reconsider and Amplify tables identify areas for improvement.

Use the Take Action page within your newsroom and content topic teams to identify what is working and what you could change.

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

"Top Performing" articles are those that had the highest traffic and engagement over the last 7 days.

These are your most successful articles across the board, as they generated high pageviews as well as above average completion and recirculation rates.

Use Case: this table can be used to easily identify what is working well on your site and should be continued. Consider putting these articles behind a paywall to increase subscriptions.

"Replicate" articles are those that were successful with your readers and should be replicated.

These articles had high pageviews and above average completion rates, meaning they generated traffic and also sustained the interest of readers.

Use Case: your readers liked this content, so try to create similar types of articles in the future. Consider putting these articles behind a paywall to increase subscriptions.

"Optimise" articles generated a lot of clicks, but did not have high engagement.

These articles had high pageviews but below average completion or recirculation rates.

Use Case: these articles attracted clicks but did not sustain the interest of your readers. Optimise these articles to improve engagement.

"Reconsider" articles require some rethinking in how they are constructed and presented to your audience.

These articles had low pageviews and below average completion rates.

Use Case: these articles could be written or promoted differently to capture the interest of your readers.

Your readers loved "Amplify" articles, but these articles did not produce high traffic.

Articles in this table had low pageviews but above average completion or recirculation rates.

Use Case: these are highly engaging articles that should be pushed on your site or through your marketing channels to generate more traffic.

The Deep Dive pages take a closer look at engagement within each audience segment.

Use these pages to identify the articles that your users are enjoying and the articles that could be improved. You can also use these pages to see where you are acquiring users within each segment.

As publishers have an interest in increasing the loyalty and engagement of their readers, these pages can be used to move readers up the loyalty curve. Pinpoint the types of content these readers like and work to increase their engagement.

Users: the number of unique visitors in this audience segment over the time period.

Pages per User: the average number of pages viewed by individual users throughout the time period.

All Articles: the number of unique articles read by users in this segment throughout the time period.

Recirculation Rate: the percentage of readers that came from another article. This metric is calculated as (1-%Exits).

Completion Rate: the percentage of pageviews where the entire article was read. This metric is calculated as (Total Article Completions / Total Pageviews). Here, the completion rate shows the average completion rate for users in this segment throughout the time period.

Pageviews: the total number of pageviews by all users in this segment throughout the time period.

Well-Read Articles: the number of articles that had over 1000 pageviews throughout the time period.

These are your most engaging articles. Rather than ranking articles by pageviews alone, EIT ranks articles based on Engagement Scores.

The Engagement Score is a score out of 10 given to each article, based on performance against the three engagement metrics (pageviews, recirculation rate and completion rate). Each article is given a ranking against the other articles on your site for each of the three metrics, with 10 being the highest score and 0 being the lowest score. These three scores are then averaged to provide the Engagement Score for the article.

Use Case: this chart provides insights into the interests of users within this particular segment. What caused a spike in segment pageviews on a particular day? Can this content be replicated and pushed to readers in this segment to increase their engagement?

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

These articles did not produce high engagement. Rather than ranking articles by pageviews alone, EIT ranks articles based on Engagement Scores.

The Engagement Score is a score out of 10 given to each article, based on performance against the three engagement metrics (pageviews, recirculation rate and completion rate). Each article is given a ranking against the other articles on your site for each of the three metrics, with 10 being the highest score and 0 being the lowest score. These three scores are then averaged to provide the Engagement Score for the article.

Use Case: this chart provides insights into what isn't attracting readers within this segment. Keep in mind that this does not mean these articles were unsuccessful; they simply did not generate traffic within this segment. How might this affect your social strategy? If these articles performed poorly with Fans but performed well with Fly Bys and Semi Engaged Readers, push them on your social channels to attract new readers.

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

The Source Medium Table shows the traffic and engagement generated by your various sources of traffic.

This includes Internal traffic, which are pageviews that come from within your site. They are recirculations from other articles. Publishers should aim to have high traffic from the Internal source, as it indicates that readers are reading more articles within your site.

Users and Pageviews are aggregate measures of traffic.

Recirculation Rate provides a measure of engagement by source / medium.This metric can be used to assess the value provided by your various sources. Use Case: Use recirculation rate to determine where your most engaged readers are coming from and how this may influence your social and campaign strategies.

The Internal/External bar chart shows the split of your segment pageviews that are Internal (i.e. recirculations from other articles on your site) versus External (i.e. pageviews from landing on an article from an external channel source).

Use Case: Use this chart to measure engagement within each segment. Are your articles generating recirculations within your segments? What might drive readers to read more articles?

The Article Traffic Table measures traffic and engagement at the article level.

Pageviews are aggregate measures of traffic.

External Rate and Recirculation Rate provide a measure of engagement with each article.

  • Use Case 1: Use External Rate to measure the proportion of your traffic that landed on this article, as opposed to clicking through to this article internally. How might this impact your homepage content and social media pushes?
  • Use Case 2: Use Recirculation Rate to measure the further internal pageviews that were generated by this article. How might the success of this article inform your homepage content and social media strategies?
  • Use Case 3: An article has a high Recirculation Rate but a low External Rate. This means a small number of readers found this article, but those that did find the article found it engaging. Push this article in your social campaigns and promote it on your homepage to help more readers find it.

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

The pie chart groups your traffic sources into four traffic buckets: Internal, Organic Search, Marketing and Referrals.

This chart gives you a simple overview of where you are obtaining readers in this audience segment.

Learn more about the EIT traffic buckets.

This table provides a breakdown of pageviews in this segment generated by each traffic bucket.

It can be used to assess which of your articles are generating pageviews from internal and controlled sources, and which are generating pageviews from external and paid sources.

Use Case (Internal and Organic Search channels): your channels should be used strategically to engage with segments of your audience. Look at the articles that performed well on these channels. These appeal to users with brand awareness and subscribers (likely Fans and Engaged), so continue to promote articles of this kind on your homepage and in content recommendations.

Use Case (Marketing and Referrals): Look at the articles that performed well on these channels. These articles appealed to new readers (Semi Engaged and Fly Bys), so continue to publish articles of this kind on these channels. If you are a subscriber-based newsroom, consider putting these articles behind a paywall to increase new subscriptions.

Note: Article titles are in lowercase to prevent duplication caused by casing differences.

EIT groups your internal and external traffic into buckets based on their cost and value to your site.

The Internal bucket captures your loyal traffic, as it comes from channels controlled by your newsroom. This bucket represents readers with brand awareness and loyalty, and includes pageviews from recirculations.

The Internal bucket includes:

  • Internal clicks (recirculations),
  • The Direct channel,
  • The Email channel, and
  • The Affiliate channel.

Organic Search traffic is supportive to your reader acquisition and retention. These referrals are free and can be increased with an effective SEO strategy.

Marketing traffic is costly to your newsroom. These channels are important for increasing your brand awareness, but it is preferable to generate most pageviews from internal channels.

The Marketing bucket includes:

  • The Social channel,
  • The Display channel, and
  • The Paid Search channel.

The Referral bucket captures generic referrals and traffic from any other channels not captured above. This traffic has ambiguous value to your site, and may be good or bad depending on context and the specific source.

The Referral bucket includes:

  • The Referral channel,
  • The (Other) channel, and
  • All of your other channels not captured above.