Google Analytics Intelligence Tutorial

  1. What is Google Analytics Intelligence?
  2. How to use Google Analytics Intelligence?
  3. Introduction to Analytics Intelligence Insight panel
  4. The insights feed
  5. The saved insights feed
  6. The read insights feed
  7. Deleting insights
  8. Opportunities
  9. Anomalies
  10. The format of Analytics Intelligence questions
  11. Limitations of Analytics Intelligence questions
  12. Best practices for asking questions from Analytics Intelligence
  13. Using trends in Analytics Intelligence questions
  14. Using comparison in Analytics Intelligence questions
  15. Understanding data composition via Analytics Intelligence questions
  16. Find top 10/20… via Analytics Intelligence questions
  17. Using date or date range in Analytics Intelligence questions
  18. How to make Analytics Intelligence more powerful for you?
  19. How to use change explorations in Google Analytics AI?
  20. How change explorations work?
  21. Limitations of change explorations
  22. FAQ

What is Google Analytics Intelligence?

Analytics Intelligence is a machine learning algorithm used by Google Analytics which makes it easier to drill down data in GA and quickly get the insight you want.

The questions that you ask about your Google Analytics (GA) data or the questions which GA Intelligence suggests are called ‘Google Analytics Intelligence Questions’.

You can ask any questions about your data in plain English (natural language) and the GA machine learning algorithm will try to answer your question.

Note: AI feature is not available in any language other than English.

For example, you can ask Analytics Intelligence (or AI): “How many users did we have last week” and it will try to answer your question.

I used the word ‘try’ because getting an answer (let alone a correct answer) is not always 100% guaranteed. The quality of the answer will depend upon the quality of data, you have collected. 

So if your data collection is not accurate then the answer delivered by AI won’t be reliable either. AI uses historical data to answer your questions.

So for example, if your enhanced ecommerce tracking is not set up correctly then there is no guarantee that you will get a reliable answer from AI, regarding your ecommerce data.

Similarly, if your event tracking is not set up correctly, then there is no guarantee of getting a reliable answer from AI.

If your reporting view does not have enough historical data then AI may not be able to answer your question and you are likely to see the following message:

We understood your question, but there is no data for your profile in this time range”.

Sometimes AI does not seem to understand your question at all. In that case, AI will not be able to answer your question and you are likely to see the following message:

“Sorry, we did not understand your question.”

Sometimes AI can understand part of your question but not all of it. In that case, AI may not be able to answer your question and you are likely to see the following message:

“Sorry, we did not understand enough of your question to provide a reliable answer.

Your query contained the following terms we did not recognize:…”

Google Analytics Intelligence

Sometimes AI can understand your question but is not able to query the data. In that case, AI will not be able to answer your question but can suggest you another similar question which it can answer.

Such questions are displayed under the section ‘“Did you mean:….”

did you mean

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If AI can understand your question and there is data available for the answer then you see the answer to your question:

Question and answer from AI

If your question has got multiple answers then AI display the list of all possible answers:

Go to report

If you want to see the report from which AI pulled the data for your answer(s) then click on the ‘Go to report’ button:

Go to report 1

How to use Google Analytics Intelligence?

To use the Google Analytics Intelligence feature, follow the steps below:

Step-1: Login to your Google Analytics account and then navigate to the reporting view for which you have got historical data (ideally three or more months of data to get statistically significant insight)

Note: If you try to use AI for a brand-new reporting view, Analytics Intelligence will not be able to provide any answer to your question and you are likely to see the following message: “We understood your question, but there is no data for your profile in this time range”.

Step-2: Navigate to the Home report:

Home

Step-3: Click anywhere on the search box text field:

click on search

Step-4: Once you click anywhere on the search box, you should see a drop-down menu like the one below:

new drop down

Step-5: Now enter the question you want to ask from the analytics intelligence and then press the ‘Enter’ key.

If you are not sure what question to ask then click on the link ‘What questions can I ask?‘:

what can i ask

Once you clicked on this link, you should see a list of question categories from Analytics Intelligence:

ask analytics intelligence

Step-6: Click on one of the question categories that say ‘Content Analysis‘ and then click on a sample question say ‘What are my top pages in terms of pageviews

content analysis

All sample questions have got an intelligence icon next to them:

content analysis 1

Once you clicked on the question, Google will answer your question on the Analytics Intelligence panel located on the right-hand side of your screen:

top page by pageviews

Click on the ‘Go to report‘ button, if you want to see a more detailed report relevant to your question:

go report pageviews

Under the ‘Go to report’ button there is a section called ‘Ask a follow-up question‘:

These are the questions suggested by Analytics Intelligence. Click on one of them, if you want:

ask follow up question

Introduction to Analytics Intelligence Insight Panel

The AI panel that you see on the right-hand side of your screen, display AI insight:

AI panel

To generate this insight, the AI regularly scan your Google Analytics data and search for outliers in the time series data. These outliers are major changes in data trend which can positively or negatively impact your business.

In order to see the AI insight, just open the AI panel by clicking on the ‘Insight’ button (located on the top right-hand side):

Insights

Then look at the section under ‘Insights Saved Read’:

insight panel

The AI insights are classified into: Insights, Saved, and Read feeds.

The Insights Feed

This feeds list all of the insights which you have not clicked/read so far:

New insight fed

The AI panel display insights in the form of feed. The feed which contains new insights is called the insights feed.

The new insights in your feed are ranked over time according to your interest in particular insight(s). So the insights you are most interested in or the one which you click the most (to view it in detail), starts ranking higher over time, in the feed.

The new insights feed is personalised for each user even for the same reporting view. So different people using the same reporting view can see different insights listed in the insights feed.

Whenever Analytics Intelligence generates new insights, they appear in the form of a blue notification circle on the ‘Intelligence’ button:

blue color notification

The Saved Insights Feed

A saved insight is the one which you saved by clicking on the ‘save insight’ button:

save insight

Once you have saved an insight, you can access it again by clicking on the ‘Saved’ button in the AI panel:

saved insight

The AI panel display saved insights in the form of a feed. The feed which contains saved insights is called the saved insights feed.

The most recent saved insight, rank at the top of the save insights feed.

The saved insights feed is also personalised for each user even for the same reporting view. So different people using the same reporting view can see different insights listed in the saved insights feed.

If you want to remove a saved insight then click on the ‘Removed from saved’ option:

remove from saved2

Note: You can also save an insight without clicking/reading it.

The Read Insights Feed

A read insight is the one that you have not viewed/read.

Whenever you click on a new Insight in the new insights feed, that insight is marked as ‘read’ and is automatically transferred to the read insights feed. Click on the ‘Read’ button to see this feed:

Read insight

The most recent viewed insights, rank at the top of the read insights feed.

The read insights feed is also personalised for each user even for the same reporting view. So different people using the same reporting view can see different insights in the read insights feed.

You can mark an insight as read even without actually viewing it. To do that just click on the ‘Mark as read’ option from the Insight feed:

mark as read

Note: You cannot mark an insight as unread.

Deleting Insights

You can delete any new, saved or read insight from the AI panel by clicking on the ‘delete’ option:

delete insight

An insight once deleted can not be recovered.

Note: If you delete an insight from the ‘read feed’ which is also available in the ‘saved feed’ then it will be removed from both feeds.

Opportunities

The outliers which can positively impact your business are called ‘opportunities’.

For example, if AI tells you that your website performs above average on the screen resolution of 1366×768 then you can create an advanced segment ‘with sessions that include: Screen Resolution: 1366×768’ to determine the cause and how this performance can be replicated for all other screen resolutions:

Opportunities

If you want to see more details about an opportunity then click on the corresponding AI insight:

more details

opportunity details

Anomalies

The outliers which can negatively impact your business are called ‘anomalies’.

For example, if AI tells you that in India, your website has an average page load time of 11.5 seconds and this is slow compared to other top countries then you need to decide whether India is an important market for you.

If it is then you need to ask your developer to decrease page load time further so that the website pages can load faster on slower internet connections:

anomaly

If you want to see more details about an anomaly then click on the corresponding AI insight:

recommendation anomaly

The format of Analytics Intelligence questions

The questions that you ask from AI do not have to be in the form of questions. What that means, your questions do need to start with: ‘what’, ‘when’, ‘where’, ‘how’ etc and end with a question mark.

Your questions do not need to be grammatically correct either. You can also ask those questions which sound more like a statement or words than a proper question.

For example: “trend of new users this week” or “sales today”.

Limitations of Analytics Intelligence Questions

#1 AI is not very good at answering questions that begin with ‘why’. So if you ask a question like: “Why is my website bounce rate so high?”, you are not likely to get an answer.

#2 AI is not good at answering questions that ask for advice. So if you ask a question like: “Which marketing campaigns should I invest in?”, then most likely you won’t get any answer.

#3 AI is not good in answering questions that ask for an explanation like: “What is bounce rate?“, “What is ecommerce conversion rate?” etc.

#4 AI cannot answer generic questions like “What is the temperature today?” or “Who is the president of the US at present?”. The questions that you ask from AI should be related to your Google Analytics data.

#5 AI is not good at forecasting data/trends for you.  So if you ask a question like “What will be my website sales in the next 6 months?” then either you won’t get an answer or you may get an inaccurate answer.

Best practices for asking questions from Analytics Intelligence

Google recommends that you should be as specific as possible when asking your questions.

Using trends in Analytics Intelligence questions

If you want AI to chart trends then include the words in your questions that indicate trends. These words could be:

  • Trend of
  • “Graph of”

For example: “trend of sales last week

Trend of reenue

Another example: “trend of traffic United States vs United Kingdom last month

US VS UK Traffic trend

Another example: graph of pageview from Facebook in the last 6 months”:

facebook trend

Using comparison in Analytics Intelligence questions

If you want AI to compare different data sets then include the words in your questions that indicate comparison.

These words could be:

  • Compare
  • Vs

For example: compare traffic in sept with oct”:

sep vs oct

Another ExampleAverage time on page for mobile vs desktop in the last one month”:

mobile vs desktop

Understanding data composition via Analytics Intelligence questions

If you want AI to show you the composition of a certain data set then include the words in your questions that indicate composition. These words could be:

  • Share of
  • Percent of
  • Percentage of

For example: Share of traffic by device in the last one month”:

share device category

Find top 10/20… via Analytics Intelligence questions

You can use AI to ask top 10, top 20, or top anything questions.

For example: ‘Top 10 most visited landing pages in the last one week’:

top landing pages

Using date or date range in Analytics Intelligence questions

By default, AI assumes a default date range of the last 7 days or the last 30 days (depending upon your question).

If you want AI to answer questions relevant to a particular date range then you must always include the words in your question which indicate date or date range. These words could be:

  • Today. For example “sales today”.
  • Yesterday. For example “sales yesterday”.
  • Two days ago. For example “website traffic two days ago”.
  • Three days ago
  • Last week
  • Last month
  • Last quarter
  • Last year
  • Sept 2-30

How to make Analytics Intelligence more powerful for you?

Analytics Intelligence is a machine learning algorithm so the more you use AI the better it will become over time.

Overtime AI learns the following things about you:

  • The type of questions you usually ask
  • The way (i.e. format) you ask questions
  • The insight you are usually interested in
  • The answers you click on.
  • The feedback you provide.

Whenever you ask a question from AI, make sure that you always leave feedback by answering ‘yes’ or ‘no’ to the question: “Was this answer helpful?”:

give feedback

Whenever you use an AI insight, make sure that you always leave feedback by answering ‘yes’ or ‘no’ to the question: “Was this insight helpful?”:

helpful insight

This manual feedback will help your AI tremendously, in tweaking its algorithm and providing better and more accurate answer/insight on its subsequent usage.

As Analytics Intelligence learns more, via your feedback and AI usage, its: autosuggestion, autocomplete, auto-reference, and insights features get smarter over time.

However, bear in mind that the quality of an answer/insight from AI depends upon the quality of data, you have collected. If your data collection is not accurate then the answer/insight delivered by AI may never be reliable.  So it is imperative that you fix as many data collection issues as possible before using Analytics Intelligence.

Note: Analytics intelligence is also available in the Google Analytics app for mobile and tablet devices.

How to use change explorations in Google Analytics AI

Google Analytics AI also provides a feature known as change exploration. When any metric value changes from one time period to another, Google Analytics AI can identify the segments of your data that are responsible for such a change.

For example, if you see there is a drop in revenue for this week, compared to last week, you can ask AI questions like “why is revenue down?” The AI will show you major segments where the revenue went down like below:

exploration change

segment changes

As you can see from the above image, there is almost -42.34% less revenue generated from paid search. This may imply that you have to spend more on Google search paid traffic and campaigns.

How change explorations work

To get change exploration insights, you need to ask a question with “why” along with a metric. The word “why” lets AI know that you are looking for change exploration. Once you specify the metric you again need to provide the date range otherwise Google Analytics will take the default date range.

For example, a few sample questions could be

  • Why users were down this week?
  • Why revenue went down last month?
  • Why pageviews was down this week?

Once you frame the question, AI will calculate the difference in the metric for the date range provided. If the difference in the metric is less than 1%, AI will not show any insights but if there is a considerable difference AI will explore different dimensions like user type, default channel grouping, country, etc.

The AI will automatically analyze the changes in different dimensions and segments and it will display top segments with high score which are contributing the change in metric.

Limitations of change explorations

Change Explorations has few limitations as below

  • Limited metric: Currently you can use change exploration only for metrics that can be summable like revenue, pageviews, users, etc. The change exploration will not work on metrics like ratios for example bounce rate, conversion rate, ecommerce conversion rate. If you try it for metrics with ratios, it will through an error as:
    “We have encountered an error and cannot process your request right now. Please try again later.”
  • Threshold value: Change exploration does not provide any insights if the difference in the metric is less than 1%. Also, if the difference is less than 5%, change exploration won’t provide more detailed insights and may have very little information.
  • Explored dimension: Change exploration only works with a set of metrics and dimensions defined by Google Analytics and hence you do not have the option to choose your own set of dimensions.

Frequently Asked Questions for Google Analytics Intelligence

What is Google Analytics Intelligence?

Analytics Intelligence is a machine learning algorithm used by Google Analytics which makes it easier to drill down data in GA and quickly get the insight you want. Based on the questions you ask it quickly finds the relevant insight and provides you detailed information without manually digging into the reports.

What questions can I ask Google Analytics Intelligence?

Following are some example questions that you can ask Google Analytics intelligence.
·        How many users did we get yesterday?
·        Where is my traffic coming from?
·        How many new users did we get last week on mobile?
·        Why did my traffic drop?
·        Why is my bounce rate increasing?
·        What are the reasons revenue increase last week?
·        Is there a problem with paid search?
·        Is Canada traffic normal?
·        Is there anything unusual?
·        Which channel converted the best for [Goal X]?
·        Which landing pages with over 500 sessions have the worst bounce rates?
·        Trend of new users this month?
·        Graph of sessions from Chicago vs Seattle in December?
·        Percent of Direct traffic over time?
·        Conversion rate for referrals vs organic search?
·        Average time on page for mobile vs desktop?
·        How many event actions did we have in February vs January?
·        Share of sessions by browser?
·        What percent of sessions in the U.S. are from social?
·        What share of sessions is from men?
·        How did share of new users compare in January for Firefox vs Chrome?
·        Trend of new users this year vs last year.

How do you use Google Analytics Intelligence?

You can use Google Analytics Intelligence using the below steps
Step-1: Login to your Google Analytics account
Step-2: Navigate to the Home report
Step-3: Click anywhere on the search box text field
Step-4: Now enter the question you want to ask from the Analytics Intelligence and then press the ‘enter’ key.

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