Ten Hidden Gems In Google Analytics: Do Smarter Web Data Analysis!

Standing Out The 80/20 rule applies to our use of web analytics tools as well. Most of us use just a small amount of power our tools contain.

This hurts my feelings! Ok, not so much hurts my feelings and more that I'm sad you are not taking advantage of all of the features at your disposal to drive smarter decisions by your leadership teams.

Regardless of the tool you have, it is always prudent to take a fresh look at a familiar tool every once in a while and see what you've been missing. I recommend that periodically you gather folks around you for lunch, pull up Adobe Analytics on the big screen in the conference room, let each person expose one hidden report or feature. You'll be surprised at how much you learn, and, like an Easter egg hunt, the whole thing is fun all by itself.

As many of you already have access to Google Analytics, in this post I want to re-introduce some of the features/reports/concepts that most likely fall outside of the normal 20% you use regularly. My hope is to aid in your persistent quest to deliver more impactful IABIs (Insights, Actions the leadership should take, Business Impact).

Some of these hidden gems are small, some big, some you might know and have ignored, and some never crossed your radar. Pop open your GA account in a different tab, or your WebTrends or your WebTrekk or IBM Analytics accounts, and follow along.

But, first… It is important to point out that some things are a bit hidden and not used as much, like the Real Time reports in Google Analytics but I'm not quite filled with grief about them….

google analytics real time data

Even your best over-estimation of Google Analytics' scale will under-estimate it by 100x, minimum. In that context, Real-Time reports are an impressive feat of engineering by the team at Google. You can see what's happening right now . And, that's not all, when you consider that it is segmented data, across multiple dimensions, it really is impressive.

But, I'm a big believer in optimizing data access to be at the right time as defined by your decision-making/action-taking speeds inside your company. When you shift from right-time to real-time, you end up with a lot more activity and no actual value. [See rule #4, and video: A Big Data Imperative: Driving Big Action] If your company can take real-time action, then real-time data becomes right-time data. If it can't, figure out what the time from insight to action is, then optimize the data to insight process.

So, if you were expecting hidden gems in a similar spirit, I'm afraid dissatisfaction will follow. My gems are are all related to driving high value to most of you, and to drive smarter, timely, broader IABIs. Here are the ten hidden gems that we'll cover in this post:

Sounds really exciting, right? Let's learn why these qualify as hidden gems, and how you can extract high-impact IABIs by leveraging them.

1. Affinity & In-Market Segments: Understand Your People Better

I am first in line when it comes to being a bit too obsessed about understanding user behavior and intent, in believing that that is a superior method when compared to the silly obsession TV, Radio, Print marketers have with demographics (age, gender, income, et. al.). I'm not giving up my position in the line. Intent and behavior data is better!

But.

For so many humans who engage with us digitally, we know so little. Maybe, our platforms have never seen them (no cookies!). Maybe, we have no idea what they are doing as they click their way around the digitalverse. In these, and many other scenarios, it is wise to step off our high horses (mine!) and leverage the psychographic data so easily available in Google Analytics.

My first hidden gem, Affinity and In-Market Segments, allow us to get a better understanding of people who engage with our digital existence…

google analytics interests affinity in-market segments

This data is a nice complement to the behavior data on your site (what pages people are viewing, what internal site searches are they doing, what products they abandon in carts, etc). It helps us get a stronger sense of who our cookies, :), really are.

Affinity categories identify lifestyle preferences of our website visitors. You can easily see applications of this data in the content you might produce for your website or your social platforms – just to use one example of value.

In-Market segments identify the product-purchase interests of your visitors (as in, what are your visitors currently actively researching and purchasing). You can easily see how this will influence your marketing and advertising strategy – ad content, ad targeting and so much more.

Having this data integrated into your site analytics behavior data means that you don't have to guess which of these groups/segments are more or less valuable. You can simply click on either one of the two above and see the valuable-drilldown view…

in-market segments detailed report

All the standard Acquisition, Behavior and Outcome metrics you are used to can be leveraged to identify valuable segments. And, in this case, if you use Google's display advertising platforms, you can integrate with them and buy ads specifically to target your high value segments. Even if you don't use Google Display Network or DoubleClick products, see the earlier paragraph for how you can use this to simply understand your current cookies better and create more relevant content.

My favourite resource to understand all the possibilities of this hidden gem , and detail, is here: Analyze users by age, gender, and interest categories.

It is important to know that this report and associated features have to be turned on in your Google Analytics account. The data used comes not from your Google Analytics account/script, rather the data comes from the third-party DoubleClick cookie (for web traffic) and from anonymous identifiers for mobile apps (i.e., Advertising ID for Android and IDFA for iOS).

Use this hidden gem and strive to get a better understanding of the people behind your anonymous cookies.

2. Google Analytics Shortcuts: Save Your Complex Views.

There is a difference between reporting and analysis. There are, of course, many complex ways to do analysis and eschew the empty calories of reporting. But, one simple strategy is to start with a standard report, and monkey with it, technical term (!), to give you the analysis you need.

A typical strategy is to customize the view, to apply different filters, to be clever about adding data to it, so on and so forth. You get a more insightful look into your performance. Then, you go on to the 15 other things that need your attention (those tweets are not going to post themselves!), and you lose all that effort you put in.

The wonderful team at Google released a tiny feature a while back called Shortcut. It is on top of every GA report, in the gray bar, right under the name of the report.

I adore it.

Let's look at an example to understand why.

I love attribution! Correction. I love my posts on attribution! :) I want to know where these reports get traffic from and if they are generating money for me. Once I know these two answers, I can take quick action to unleash some of my precious marketing dollars in the right place.

I started with the standard Behavior > Site Content > All Pages report. I added two advanced filters to it to identify just those posts and a higher then normal Page Value. I also don't like the slew of metrics thrown at us in the standard report, hence I switch to the Comparison view and just pick the two metrics I want. Finally, add the secondary dimension Source.

Here's the report….

google analytics shortcuts report

It is super-insightful. It let's me see at a glance exactly what I want and take quick action. You don't see this in the above view, but I also added an advanced segment (separating out desktop and mobile).

Then, not wanting to lose all this work, and wanting to coming back to it again and again, I hit the Shortcut button.

Now, I can easily find it any time I want in the left navigation bar in Google Analytics…

google analytics shortcuts

Oh, the shortcut also remembers I want the main graph to be Page Value and not Sessions. Sweet.

My call to arms to you is to reject standard reports and segments. As you do that, leverage the hidden gem called Shortcuts to save your beloved final product.

Next time you need that insight, you'll get it faster and GA will automatically apply it to the latest time period.

3. Custom Dimensions: Deeper Unique-You Analysis

We touched on the fact that for the most part we analyze and understand cookies. [Super Analysis Ninja? Switch to User-ID by implementing Universal Analytics .]

We are also limited to the data Analytics collects by default. Yes, it is A Lot. But, we can add a bit more to it to get smarter insights. The bit we add to it is unique to our business, hence difficult for any analytics tool to address by default.

Using custom variables, sorry custom dimensions, is an amazing way to make our dataset in GA unique to us.

A simple example is the ability to track if people are your logged into your site as they visit, or not-logged. The hypothesis being that the logged in users are our existing customers. You can use custom dimensions to do this quite easily with an extra bit of code. This allows you to see this delicious report inside GA…

custom variables google analytics

66k sessions of 1.6 million were from 26.7k users who fall in the Yes bucket. You now have a dramatically different understanding of who is there by simply creating an advanced segment for these Yes (logged-in) users. But, well before that, just scanning the data from left to right (where the last column blows your mind) will have an instantaneous influence in the IABI you deliver to your boss.

Custom dimensions requires a small amount of technical work, and often requires you to get help from a GACP. But it is totally worth it for the higher quality insights, actions and business impact computations you'll be able to deliver.

If you are a content site, this means the ability to slice and dice your data by author names, content type, subscribers and free-loaders, commentators and non-commentators, and so much more to bring a new layer of insights.

If you are an ecommerce site, amongst many other things you can track customers who purchase multiple times, all kinds of product detail related to cart and checkout pages, your internal cross-selling and up-selling campaigns (small plug for event tracking on this one as well), multiple orders by the same customer, and like a million other things.

Take advantage of his hidden gem . It is difficult for me to imagine that you could be an analysis ninja without it.

4. Time Lag & Path Length: Pan-Session Ecommerce Analysis

I've been a big fan of any type of pan-session analysis (multiple visits by the same person). The loyalty reports, Recency and Frequency, are examples of pan-session analysis. As are all the attribution analyses that we do (more on this later in this post).

One hidden gem in an ecommerce context is the Path Length report in the Multi-Channel Funnels folder. It shows the number of visits (sessions) it took for a person to convert on your site. (If they deliver two conversion over multiple visits, it shows visits to conversion one and visits to conversion two.) It is really fantastic, looks like this for an ecommerce client…

google analytics path length report

You can see that around forty percent of the conversions happen on the very first visit (wowza!), the second forty percent take up to five visits, and then there is a long tail.

This data has small implications, like the fact that defining Conversion Rate as Orders divided by Visits is a terrible idea. Change. Divide Orders by Unique Visitors (or Users in GA lingo).

This data has big implications as well.

If sixty or more percentage of people are going to take longer than one visit to convert, do you have a user experiences that creates incentives to make the second visit easier (or even create incentives in the first so that the second and the third will happen)? Proactively requesting for a new account to be opened (or for a person to log in) is one. Encouraging people to save carts to access across devices is another. Changing landing pages to contain three buttons instead of one is a great idea (from just having Buy to Have, Save, and Buy – Have to drive personalization, Save to ease future visits and create wishlists and Buy, well, to make immediate money). Getting permission to email if the price drops is yet another. Segmenting this data and using that analysis to change your adwords ad copy, your display banner messaging, your YouTube trueview targeting, and much more, is a brilliant idea.

The power, of shifting your marketing strategy to pulse at the beat of customer expectations. Magical.

Path Length has a sister report called Time Lag. Pretty much the same spirit, except you get the view from a days to conversion perspective…

google analytics time lag report

Again, amazing insights can come from this data as well.

Both these reports can be segmented, click on Conversion Segments at the top of the report. If you have Macro and Micro-Outcomes (and shame on your company if they don't!), you can understand this entire sequence of user behavior uniquely for each of those outcomes. This is the space super Analysis Ninjas play in!

A small word of warning. In the Ecommerce folder, you will see a report called Time to Purchase. It seems to show the same information as the above two reports. Please skip the Time to Purchase reports. Hopefully one day the GA team will choose to only have one version of the truth (the real one of course!).

5. Assisted Conversions: Smarter Marketing Impact Attribution

If you have been reading my blog for any duration, or been to one of my keynotes, then this is not so much a hidden gem, rather it is Avinash keeps talking about this all the time gem.

The Assisted Conversions report builds upon recommendation #4, Time Lag and Path Length, and shows the performance of marketing channels in both delivering last-click conversions and assisted conversions. Think of it this way, the report illustrates credit being given to your marketing efforts (email, referrals, display and more) for introducing new people to your business, for working hard in the early part of the conversion journey, AND credit for driving the visit that lead to a direct conversion.

This is what the report looks like for one of my businesses…

assisted conversions report

There is a lot there, just look at that last column. Assisted/Last Click Conversions. A ratio of less than one is for channels where they drive a lot more direct conversions. A ratio of more than one is for channels that drive a lot more early visits (all of whom convert in the future, but via other channels).

That column shows how you have to change your paid or organic ad content, ad targeting and landing page experience (remember the Have, Save, Buy recommendation from earlier) to take advantage of the channel's strengths.

Clicking on any one of the channels above, will lead you to a lovely drilldown report that shows detailed performance for that channel….

assisted conversions report organic search

The above report proves my statement, all data in aggregate is crap! Just see the diversity in user behavior just for SEO. You should do this for all your core marketing channels (Email and Display are particularly insightful).

Another hidden gem for this hidden gem.

For Social Media Marketing, my favourite drilldown report is not in the Multi-Channels Funnels folder, where you find the above reports, rather it is hidden quite cleverly by the team at Google. Go to Acquisition > Social > Conversions > Assisted vs. Last Interaction Analysis tab. There, you will find this gorgeous beast…

assisted conversions social media

It is perhaps the cleanest view of assisted conversions behavior for social media efforts. Simply because the reports in the Social folders are processed a bit differently, using a different channel/source mapping strategy. This exposes more social networks, more cleanly, with your paid and owned efforts showing up in one place.

Again, look at that last column, there is a huge diversity in behavior. Your social media strategy (content, targeting, landing page experience) should reflect this user behavior.

Real. Golden. Stuff.

My recommendation #5 will become the gateway drug to attribution modeling, media-mix modeling, and multi-channel controlled experiments. A lot on that is in this post for Super Analysis Ninjas: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models. But your journey starts above. Think of how much cleverer your bosses and marketers will be just understanding the implications of the last column above. Do that first! Then read the aforementioned post.

6. Custom Alerts: Get YourKnown Unknowns!

There are three kinds of challenges we deal with when it comes to decision making. Things we know we know. Things we know we don't know. Think we don't know we don't know. The known knowns, the known unknowns, the unknown unknowns. [More here.]

When you log into GA every day, you have a sense for things you were anticipating, you go look for them, you are not surprised, perhaps you feel validated. The known knowns. Custom alerts are such a lovely hidden gem because they proactively let us know when the known unknowns have happened. We thought they might, but rather than check for them constantly, GA does it for you and alerts you, so that you can transform the activity into insight, come up with a recommended action and compute business impact.

Here's a lovely example. I am big on social as a channel (follow me, links top right!). I want to be proactively advised if my marketing is translating into success in terms of dineros. I know it does. But, I want to be proactively notified when it really does. Hence, I've crated this alert…

twitter custom alert google analytics

It is a daily alert (email, I'm old school, you can do text via phone too). It will identify twitter traffic. But only trigger the alert when the Per Session Goal Value is 50% greater than what is normal for my twitter traffic.

So it's not just an alert, it's an alert when something truly worth being alerted to is happening.

(This is why I am a huge fan of having high thresholds for alerts to be triggered. Remember, it will intrude into your life. So, don't create a hundred alerts for everything under the sun. Keep it focused on the clump of things on your strategic Digital Marketing and Measurement Model, and your tactical big priorities.)

Here's an excerpt of some of the alerts in my account. You can easily see what's most important to me.

google analytics custom alerts

You can get pretty creative with what you do.

I've been on a recent rampage on re-focusing audiences on computing Customer Lifetime Value. I've been speaking about it, writing about it and teaching about it. I wanted to know if this is triggering an increased interest in my posts on LTV, as I undertake this effort with evangelical fervor.

Here's the alert I'd created for that purpose…

lifetime vlaue post interest increase

It picks up all pages with lifetime in the title. The alert is triggered when pageviews increase by more than 25% compared to previous week. Nice!

Custom alerts is an immensely useful weapon in your ability to react quickly to things that you expect to happen, but don't know when. Setting them up means that you'll be surprised less, and that you'll be the first to find out when something happens (rather than Roger the other Analyst who is Newman to your Seinfeld!).

If you would like to explore all your possibilities, and learn more: Identify The Known Unknowns: Leverage Analytics Custom Alerts.

Your journey begins in the Admin section, in the View column, scroll down to Custom Alerts and click on New Alert. God speed!

7. Download Solutions: Benefit From The Wisdom Of Crowds

Enough of doing all the work ourselves. Time to mooch of others!

I mean, take advantage of our community of amazing peers who have already created an incredible collection of solutions!

I am surprised at how few people take advantage of the Google Analytics Solutions Gallery.

While you are creating your custom alerts in the Admin section of GA. Just scroll a bit more and locate the link called Shared Assets. It will show a list of assets you've shared with the world (and I hope you have!).

The button you are looking for is called Import from Gallery…

import from gallery

This opens an entire world of wonderful solutions you can simply download into your Google Analytics account! Initially you'll see all the solutions available to you…

google analytics gallery bundles

Obviously the very first thing you have to do is click on the very first Import button. :) With that click, you can download my solutions bundle, Occam's Razor Awesomeness. It has a useful, and dare I say, :), awesome, bundle of my favourite segments (six), dashboards (one, VP), custom reports (nine). They cover mobile, search, technical elements, internal site search, engagement, content analysis and more. Click inside the GA Admin section or the link in the prior sentence.

As soon as you are done with that, scroll through the most popular, and download the ones that are the most relevant.

The cool thing about the Solutions Gallery is that you can just go search for stuff whenever you are stuck. For example, you are just getting going to the complex world of custom attribution modeling. Fantastic. Rather than starting from scratch, just search for it in the Solutions Gallery…

attribution models

One of the ones you'll find is my Market Motive Mindblowing Attribution Model, uploaded in the Solutions Gallery by my dear friends at Loves Data, with one click.

This give you an informed starting point. Once the model is in your account, you benefit from whatever little wisdom I have. You can play with the model, understand how it was created and what trade-offs I'm making. Then, customize it to your liking.

This process reduces the time to something smart. You don't start from scratch, you start with something smart, layer in your even better smarts.

While you are at it, you can easily download the dashboards, reports and segments uploaded by the smart people at Loves Data

loves data solutions

Or whatever else you are in need of.

For example, custom reports for search engine optimization. With all the Social Media ROI pressure you might find the social media dashboards to be handy. Or anything else your boss is yelling he needs!

The Solutions Gallery is a great hidden gem, take advantage of your generous peers, and reduce time to market.

8. Search Queries: Get Your Organic Keyword Data Back!

Ok, so perhaps the exclamation mark is a bit of an exaggeration. But, this is still a valuable hidden gem.

With the advent of Not Provided, initially for Google traffic and subsequently for other search engines, we lost the ability to have organic search keywords for users who were logged into google.com when they did their searches. For me, and surely in the range for most other sites, Not Provided is around 90%.

But what Google taketh, Google giveth back some.

In your Google Webmaster Tools account the team has increased the number and duration of queries you have access to. This is at least giving us all the head queries, and a great ability to understand the effectiveness of our SEO strategies.

What is a hidden gem is the fact that you can also get all this data inside Google Analytics! Acquisition folder > Search Engine Optimization > Queries…

search engine optimizatoin report

In my case for the current time period I see 4,136 search queries that were performed on www.google.com to get to my site. I can see some things that I would not see in my prior GA reports, Impression (how often my site appeared in search results), Average Position of my site in those results, and the Click-through Rate. I then see Clicks, the metric that is close to (But Not The Same As) Visits.

While we get access to this query data (along with Landing Pages and Geo data from Webmaster Tools in GA), this is pretty much the end of the road. You cannot tie this data to anything else in GA (say, Conversions or Pages per Visit etc. etc.). You can't even do other stuff like, say, you read on a famous blog that analyzing search queries with multiple keywords is a smart idea. Well, you can't do that inside GA any more.

What you can do though, is take data out of Google Analytics…

export to excel

And, then do the analysis outside GA. Small victory.

Not everyone in your company has access to GWT and hence it is pretty smart to just get it into GA using this hidden gem. Just link your GWT data with GA.

[Bonus: If you want to do Super Analysis Ninja level analysis of Not Provided data: Search: Not Provided: What Remains, Keyword Data Options, the Future]

9. GA Applications: Your Everyday Challenges Amazingly Solved!!

You just saw above the simplest way to download your data from Google Analytics. You can do a lot more!

The Google Analytics API is perhaps the most scalable and lovely way to suck everything out of your GA account. But for that, you do need some technical chops or technical help. [Though this Query Explorer is astoundingly good, and even lay folks like you and I can use it to explore the API and do cool stuff!]

For us, the hidden gem is the Google Analytics Application Gallery. There, you are able to get access to a whole bunch of super-creative applications that solve every problem you might imagine. In almost all cases, taking data out of Google Analytics.

google analtyics application gallery

In the space of the screenshot above you can see an application that applies AI and transforms your GA data into natural language reports, a, how awesome is this name, data grabber for Excel to allow you to create refreshable dashboards and reports (and charge your clients more for "automation!") and a solution to analyze and integrate conversion analytics for phone calls that might originate from your online ads and website engagement.

And, that is just three of 'em!

There are tools that automate site audits so that you can make sure you are collecting data accurately (try Check My Analytics). There are dashboarding and visualization solutions (try Tatvic or NextAnalytics). There are Search Engine Optimization tools (try Analytics Portfolio). Way too many business intelligence options, and mobile solutions and email integrations and tag management and ecommerce and content management and everything else under the sun.

The App Gallery has both free and paid solutions. For all free solutions, click here and then from the left nav choose the category you are interested in.

The Google Analytics team, just like very other vendor, can only solve x problems. Yet there are x+y problems we all face (with y being niche problems usually). For y, just head over to the hidden gem that is the GA App Gallery and discover that someone's already solved the problem you are having (for free, or for a small price).

Boom! Happiness!

10. Shopping Behavior Analysis: Funnel Your World!

My last recommendation is perhaps a hidden gem because it is so new that most of you might not have heard of it. It is a part of the new Enhanced Ecommerce feature-set in Google Analytics. There are such amazing features that if you are still on standard ecommerce by April 30th, you'll fall into the super-lame category! :)

The hidden gem is the Shopping Behavior Analysis report.

google analytics shopping behaviour analysis

Thus far you only did funnel analysis for your cart and checkout experience. And, you should continue to do that. What the Shopping Behavior Analysis report does is stretch the funnel all the way to the start of the session.

In the above example you can see total sessions (visits) where no shopping activity happened. Of those, the sessions were product pages were viewed (and shopping activity could have happened like add to cart!). And then the number where carts were abandoned, followed by abandoned checkouts.

Isn't it heartbreaking, of the 173k sessions only 29k even saw a page with a product during the visits? What the heck were these people doing on the site? And why are we tolerating them! :)

You can imagine the investigations this can easily set off for the user experience on your site, the content being created, the shopping process, and so much more. This is why this hidden gem is so great. One report explains with clarity important issues, and kicks of very actionable next steps.

There are two additional cool possibilities.

You can apply advanced segmentation, there are a ton of cool ones already built in. I've applied the Direct Traffic segment, and you can see that the numbers changes, and what I might focus on in the report also changes.

google analytics shopping behaviour analysis direct

You can segment by Males and Females (connecting this recommendation to #1 above). Bigger or smaller purchasers, or for that matter any segment you can imagine. You can also click on any of the blue boxes above, and create an ecommerce segment for that group. For example, Sessions with Product Views. Now you can go and apply this segment to your Traffic Sources report.

The second cool possibility is right under the report. You see a table that initially breaks the details out by New and Returning Visitors. You can choose to see the Sessions metrics, I like seeing the Abandonments metrics…

shopping behaviour analysis direct new returning

New and Returning is rarely insightful. Hence, I'm grateful that by clicking the User Type button I can access a whole bunch more. My favourite include Device Category, City, Source and User Category (custom one that you can set up).

shopping behavior user category abandonments

Now we can separate out various users and their behavior on the site. What is up with our marketing team not buying anything?

And, the super amazingly useful segmentation of user behavior by Source…

shopping behavior source abandonments

Each collection of users behave differently, and this allows you to make changes to the end-to-end (from the visitor source to order confirmation) experience.

Shopping Behavior Analysis report is easy for even the most senior person in your company to understand, and yet has enough horsepower built in to allow you to dig deep to find high-impact issues.

Phew!

We are done.

Ten hidden gems in Google Analytics that likely fall on the 80% of the tool that you don't use. They'll help you double the impact you are having on your company, through your IABI recommendations. Not bad, right?

But, wait! There's more…

These gems are not the end of the story of course. There are others like Channel Groupings that allow you to change the way you categorize traffic. This can be often useful. There is an additional feature called MCF Channel Groupings that allows you to do sexy stuff with my favourite MCF reports. Certainly a feature for super-advanced users, quite useful if you are one. I've recently outlined the immense value of the Google Analytics Benchmarking reports. The Site Speed reports are a wonderful hidden gem – I wish more people understood how critical speed on multiple desirable dimensions.

Then there are standard features that we've talked about so much, but so few people use. Advanced Segments and Custom Reports (Known Knowns!). It pains me, massively, that so few people use these two features without which it is quite literally impossible to find anything that impacts the business bottom-line on a regular basis. If your analytics life (in any digital analytics tool) is not structured on those two core elements, please shift your approach this very moment if you want to retain relevance!

There is a lot to do. It is exciting to be an Analysis Ninja.

As always, it is your turn now.

I would love to hear what parts of Analytics do you consider to be a hidden gem? Are there reports, segments, analysis possibilities, alerts, applications, data collection strategies that have elevated your analytical game? Which of the above ten hidden gems will you find to be most useful? If you use them already, is there a facet of how you use them that I've not covered above?

Please share your incredible ideas, feedback on my recommendations above, battle scars, best practices, and anything else you think will add value to our readers, via comments below.

Thank you.

Comments

  1. 1

    I consider myself to be an expert in Google Analytics. After reading this post I've come to realize that I still have a long way to go to take advantage of all analytics has to offer.

    I am reminded of the famous Albert Einstein quote “The more I learn, the more I realize how much I don't know.”

    Love your blog Avinash.

  2. 2

    Deep knowledge with simple explanation!

    This why I read your blog regularly to sharpen my knowledge. Thank you so much for your blog :)

    Thanks,

  3. 3

    Google Analytics is an amazing tool, however it's even… better when you have amazing insights (like the ones shared here) to get better results with the analytics.

    Indeed the 80/20 rule definitely applies :)

  4. 4
    Matt @MagnetProfile.com says:

    Hi Avinash,

    Thanks for sharing this really great content. I want to point out only a small thing. In the first paragraph you've wrote "Understand Your People Better". The problem I found is that some of the information we can find in web analytics tools (such as age, gender, and generic interests) are useful to have an general idea about the customers, to create a good (web) marketing strategy to acquire the better ones, but this type of information are not useful to understand what type of needs they have. Of course, not all information are useful for all markets and industries, but I think that so often we focus only on those data because we don't have others.

    I've talked with different entrepreneurs and, if I can summarize in one phrase what they want to understand from their analytics data, is how to use that information to generate more business.

    Now I know that with the using this type of segments and reports we can understand a lot of things about our visitors, but at the end, businesses needs only one thing: the right information to sell more, generate leads, target their marketing campaigns to achive the right prospects.

    I'm agree with you in this phrase: "to get a better understanding of the people behind your anonymous cookies": we have to analyze datas to generate new opportunities and only in this way we can use internet as a useful business tool.

    What do you think?

    Matt

    • 5

      Matt: Absolutely agree. The demographic and psychographic data you'll find in your digital analytics and competitive intelligence tools will be just directional.

      It will also be better for bigger sites, and, for better or worse, for bigger countries with more established digital footprints.

      Yet, I do believe that it forms a valuable additional piece of data to give context to the decisions we need to make. We would not just use that, but we would use it in combination with other things (like our web analytics data, our survey data, etc.).

      If you do this, you will make smarter decisions.

      The closer you get to focusing on people (and their behavior and intent and not just age), the better you will do. Hence, I'm a big fan of leveraging solutions like User-ID in Universal Analytics.

      Thanks so much for sharing your wonderful guidance, and question.

      Avinash.

    • 6
      Levett says:

      Hey Matt and Avinash,

      @ Avinash – First off your topics have provided me with so much actionable tips. Thanks for writing on these!!!

      @Matt – I have also found this to be an age old question regarding "understanding the user"

      One way to use Google analytics to "understand your users" is to look at the #8(search query report in google analytics) Type this into the search box. Avinash wrote a blog topic using Regex in your search query reports
      \b(adding|does|do|who|what|where|when|why|how|will|can|\?|am|is|are|was|were|be|being|been|versus|vs|vs\.)\b

      This gives you the query report in questions and provides me with a wealth of insights of what questions users are asking and how you can improve content to answer these questions more effectively. It would be great if we could get more data from these reports such as bounce rates though….

      @Avinash – Google needs to giveth more on the search query report ;) all I want is bounce rates…

      • 7

        Hi Levett,
        yes, "understanding users" is an old question and I personally think that there aren't good answers yet.

        In my point of view, the analysis you have suggested is useful, but incomplete. I know, having some information is better than nothing, but at the same time don't allow us to have a 360° view of our website visitors.

        I try to do an example to be more clear on this point. Think about an ecommerce that sell home entertainment devices.

        A potential customer arrive on your website form a search engine query, like "buy [brand] hd tv". Goal! We have found someone interested on a product we sell, and our goal is to accelerate and increase the probability to close the deal. If the visitor buy the television, the overall strategy works.

        But what about the reason why the new customer has bought this television? Consider those two cases as examples.
        1) Because his old tv is exploded :), so he need a new television
        2) Because has just bought a new home and wanted a new entertainment system

        The value of a customer in those two cases are different: in the first case, the upselling opportunities are really low. We don't know anything about the customer, and the only thing we can try to do, is suggest other random products.

        Or, in the second case, the upselling opportunities are very high: we can recommend the best home theater audio system, providing a consultancy on how to improve the performance of the new system, a special guarantee, etc. Valuable things for the customer. We are able to customize the communication, promos, and assistance to his specific needs.

        I know this is only an example, and probably too hard to make real, but I hope the vision I'm trying to say is clear.

        • 8
          Levett says:

          Hey Matt,

          I totally agree with your vision. Wow, love the examples of the two cases(signals) you brought up. Really got me thinking about how we can get this kind of information.

          Quite honestly, Google may have this data via its browser activity(if applicable), but than your getting into ethics and anti-privacy and this finite detail would create a firestorm. Think about being able to track IP addresses…Now Imagine if you new somebody at an ISP who will give this info to you.
          askleo.com/finding_the_owner_of_an_ip_address/

          This is scary if achievable…..but will provide marketers or assasins with a "360" view.

          Now going back to the topic at hand about "understanding the user"

          You can look at your analytics and see what other pages(products) your customer viewed before making purchases? (please take this as a grain of salt)

          These are mere ideas and no where near to the finite details you are asking for.

          As for the search query analysis. I totally agree with you and feel the report is imcomplete. There is still so much more I want to know about my users. I did find a way to add on to this report by some articles I read about data blending on this blog.( And for the sake of simplicity, I am making assumptions that the data I collected is accurate…Further testing is required)

          Take a look at Avinash's response to you on the 3rd paragraph regarding combining different sources or as I like to call it.. "Signals". Overall I am creating a new dataset tailored to my specific needs. Think about the data you have and how they can be combined. (Is their a way to map census data with your users visits?) Ask yourself questions like, what data would be out there that provides me with Case1 or Case2 information..Browser activity?Census data? where are these sources? and are they obtainable?

          Now to the Search Query report..#8 on this blog.. you only get CTR,Impressions,Query, Clicks and Avg. Position, its good, but marketers need more than that to make smarter decisions.
          I'll break it down in steps and hope this makes sense.(and must emphasize that I have not tested the accuracy of this data set yet..)

          STEP 1: Lets say I type in some of the queries on Google to looked for the exact page and position that the query was on. (depending on the # of queries or organic visbility, you may need to find a solution to scale this up =)…)

          Now I have 2 additional signals in my data set. (for the sake of simplicity I am also going to assume that the first page I see that contains my query on Google SERPs, is also the page that the user clicked on.)

          STEP 2: Now that I have a page url..I can now go back to Google analytics and look for the metrics for those pages I found in my data set. (Lets forget about Google Sampling for now and it only letting me export 5k pages…=(….)

          STEP 3: Now depending on your data set, familiaritly with Spreadsheets Vlookups or SQL joins will be very beneficial in mapping(or combining) more to this. Think about a unique identifier in your data set. Right now we are mapping our data set "page" with Google analytics page. Our new dataset has now improved exponentially with all signals that google analytics provides.

          Now I know Bounce rates, time on page, pageviews etc etc. and can make more smarter decisions. I also have rankings to prioritize which queries I want to target.You can now see the potential of this hidden gem that Avinash has mentioned.

          An example of how I used this data set.
          With a query and page I can use this data set to quickly launch a longtail adwords semantic search campaign as I would like to call it =). Gather more data and analyze again.

          There are alot of holes in this data set but so far its working really well on PPC..=). SEO, Social and Video are currently being implemented. I am now making smarter decisions on what content I should publish or post. (I assume…=))

          I hope I didnt go off topic or confuse you here, but the overall message is, what Avinash is saying when he said to combine and look at other sources as well. You should look at the data you have available whether it be from GA or other sources and find ways to "blend" the data together to make your own customized data set. Google Analytics or other analytics tools provides you with solid foundatins in achieving these. Look for other data sources that help you obtain that information you seek and combine them all into your own data set about "understanding the user".

          This blog about web analytics has so many actionable topics to explore and like many others say…a hidden gem in itself.

          Explore some of the techniques Avinash has mentioned throughout this site and customize it to your own specifications is what Im saying.

          Now my usage of the #8 Hidden gem may be the most ludicrous analysis ever but my motto is ABT and ABL…always be testing and always be learning.

          Cheers,
          Levett

          • 9

            @Levett,
            thanks, thanks, thanks for your sharing. There is a lot of value on these comments.

            I totally agree with you and your examples, and thanks for sharing them.

            The only other thing that I want to add here, is my personal vision about the future of web analytics: if we'll be able to transform data into information that can be used into the business and decision-making processes, the web analytics will make a big quality jump. The value that digital marketing will provide, will be broadly understandable to those that want do business in the right way.

            I hope to hear from you soon :)

            Matt

  5. 10

    Hi Avinash,

    In our company we are using R and Google Analytics API to obtain beautiful insights.

    My favourite is the one that analyses the performance of the themes in our multinational sites. Thanks to content-grouping, userGender, userAgeBracket and Affinity Segments, we know nowadays what our cookies really want to consume and which style we have to use when we create new content. So we are able to deliver the best user experience ever, and the success is pretty noticeable.

    But I really love this specific insight, because they are also a thermometer of our society. A 100% antrophological study. For example, although our Family Themes are consumed mostly by women (35-44), the gap between gender is categorically smaller in northern European countries (the gap decreases proportionately as we move from south to north in Europe). Something similar happens with the 65+ group. In Netherland, for example, the interest of this group for Active & Adventure Holidays is remarkably bigger than in Italy.

    Thanks for sharing your gems with the community. I hope that even more people get fascinated from their insights as we are.

    Best Regards.

  6. 11
    Valerie says:

    Really great overview!

    I especially appreciated the Google analytics tips, and I like how you put your information in "simple terms" so I can actually understand it.

    Always enjoy your blog posts.

  7. 12

    Kaushik.net is itself a gem..

    I have added some of your applications from "Google Analytics Application Gallery" and they are also superb.

  8. 13
    Joshua U says:

    Thanks for the practical guide Avinash.

    What do you use for your screen grabs? You always have many that are neatly styled at a good resolution.

    • 14

      Joshua: I'm so glad you found the post to be of value.

      I'm very old school.

      I use Screenhunter Pro to capture the screenshots. It is completely invisible, I just press F6, and an image is in my clipboard and on the desktop. Easy. :)

      The images are styled in the software I use to write my posts, BlogDesk. It was discontinued years ago (!), but still works, is simple and distraction free. It has an image editor built into it.

      Avinash.

  9. 15
    Shreekant says:

    Hi Avinash,

    As I expected, This post give lot of knowledge and sharpen my skill in Analytics.

    Always inspired your blog.

  10. 16

    Hello Avinash!

    Excellent blog post again. Did not know about a few hidden gems and as always this is a kick ass blog post.

    Although I have been using path length and time lag report to understand how big our customer's sales cycle is, one thing I am finding difficulties trying to figure out where the actual conversion is happening on my page.

    For example, I am running an adwords campaign through which a user is landing on my page, but I have figured out that he might be browsing around the website for similar products and might drop an inquiry in a completely different product page.

    Is there any way I can track which exact page this is happening and the complete path taken by the user?

    Thank you very much!

    • 17

      Sanjay: I want to caveat that people will likely direct you to Path Analysis, I humbly believe that if you get more than 1000 people on your site a month, this is a complete and utter waste of time. I'm exposing my bias up front.

      On to your question…

      If you want to know where on the page something is happening, you can simply use the In-Page Analytics report. If you have duplicate links on that page, you might have to do a small amount of technical work, but this report should give you want you want.

      If you want to know the "path", :), I encourage you to leverage the much better User Flow reports. There is one Behavior section of Google Analytics. Remember to apply AdWrods segmentation on the report for magic.

      Good luck!

      Avinash.

  11. 18

    Can anyone give some examples of what actions you took from the Shopping Behavioral Analysis report?

    I agree that there is a lot of good data here, but would love to hear actual examples of actions that were taken with this data that led to additional revenue/goal conversions.

    • 19

      Corte: I'll also invite others to chime in.

      For a recent toy website I was working with… The report was super weird (kind of like the one in the post, where only a fraction of their site made it to the product pages). In aggregate this was not very useful of course.

      A segmentation of the sources of traffic highlighted that a big chunk of our social, email traffic was not interested in terms of immediate purchase intent, but that is what we solved for and spent money on. That was changed, these people go to a different section, and we are comfortable with them not buying right away.

      For email we also changed the content with the commercial content higher in the email itself, landing on more specific product pages (rather than uber-product category pages). These two changes lead to a higher cart addition and a bit higher checkout completion rate.

      The biggest influence was on what the heck to do with the home page (40% of the traffic entered here). We changed the balance to be a bit more commercial (we were shying away from this last year), and changed the top navigation structure to focus more on getting people to Do pages. We still have some See and Think, we just changed the balance. This has had the biggest impact so far.

      The SBA report just focused our attention in a big way, all other actions as you can see above came from digging deeper, segmentation and experimentation.

      We are only a few months in on this site, so we are learning and improving. But I hope this helps a bit.

      Avinash.

  12. 20

    Hi Avinash,

    Big thanks to you for your lesson here, so now I feel more understand about Google Analytics. And from your lesson here, I will try it to mine and hope that the result will come as I expected.

    Thanks again Avinash.

  13. 21

    Hello Avinash,

    From the moment I started my career in analytics, I've been getting lots of help from your posts.

    Thanking you for guiding newcomers like me with your inspiring posts.

    Really great post, thank you again very much.

  14. 22

    Thank a lot Avinash for sharing such wonderful and specific recommendations with examples in your posts.

  15. 23

    Shortcuts are really interesting.

    Sad thing is that you can't access them with a different user in the same account, they are not sharable.

    That's really too bad, because it would make sharing base reports so much powerful.

    • 24

      Benoit:It is indeed a bummer.

      For now you will have to recreate it for them once, then they can save it.

      Hoepfully the team will build sharing in shortcuts too, just like custom reports, segments, dashboards, attribution models etc.

      Avinash.

  16. 25

    As always, great post Avinash!

    A helpful thing to add on to #9, is that you can easily automate reporting in google spreadsheets too. It is called Magic (literally). You can setup, schedule, and forget about it. No technical skills required.

    More info can be found here – https://developers.google.com/analytics/solutions/google-analytics-spreadsheet-add-on.

    I find this to be better than the excel automation if you are able to use instead (it doesn't crash, no sending files back and forth so you are really taken out of the picture in terms of reporting, and can connect to databases better than excel (IMO) so connect online and offline data is easy).

  17. 26

    As always, thanks for taking the vodou (as spelled in Caribbean French), out of analytics.

    If I review your Web Analytics 2.0 book from 2010, I think much of the content is still valid, am I wrong? I think my copy signed by you at an SMX tradeshow must be very valuable now! :) jk

    Thanks again for the great insights.

    • 27

      John: You are so kind, thank you. I'm glad you found the post to be of value.

      Web Analytics 2.0 is a book that shares frameworks and approaches to think analytically (in a smart way!). In as much the content continues to be of value.

      Good luck!

      Avinash.

  18. 28
    Shuki Mann says:

    As always, an amazing and very inspiring post Avinash!

    One question – Do you really believe Google about the affinity and in-market data they give you?
    In your screenshot I can see that the bounce rate (for example) is almost the same for all the verticals and I can't imagine this situation for traffic sources for example. It must be some differences, don't you think so?

    • 29

      Shuki: It is important to point out that each person will form their own opinions, the good news is that you can read in detail where the data comes from as you form the opinion:

      Analytics article: https://support.google.com/analytics/answer/2799357?hl=en

      This one is for AdWords, but the context is the same, read this section: "How Google determines demographic information" https://support.google.com/adwords/answer/2580383?hl=en

      In the post I mention that this data is better for bigger countries and for countries with a more active digital ecosystem. The data gets better with a larger sample size. This is not something either small sites in big countries or big sites in small countries can find comfort in.

      Still, even in the best case this is a complement to your behavior data. So you still come out a winner! :)

      Avinash.

  19. 30
    Gena Swearngen says:

    Great article, with informative points that I can easily action in my own Google Analytics accounts.

    I am also glad that I found your post, as there is so much for me to still learn about google Analytics.

  20. 31

    Great post and very useful information!

    Thanks for the good work!

  21. 32

    There is a mistake in 3rd point:

    "…66k of 1.6 million people fall in the Yes bucket…"

    These are sessions, not users.

  22. 33

    Hi Avinash:

    Your blog is a gem itself. Excellent blog post as always. Learnt a lot.

    Best Regards
    Miraj Gazi

  23. 34

    Hello Avinash,

    Useful Blog for every one ,We can learn many things, Learn t many things

    Your Some different from other bloggers

    Keep on going !!!….

  24. 35

    Oh my god !!

    After reading this complete article very carefully, I can say what I have missed with google analytics for several months. I learned many interesting things from this tutorial about google analytics and its Web Data Analysis features.

    Thanks for this great help. Keep helping us !!

  25. 36

    I am new to all of this.

    Great article well worth the read.

    Thanks!

  26. 37
    AB Associates says:

    Thanks a lot for sharing this wonderful information about Analytics.

    We have a long list of to-dos based on your recommendations.

    Thanks Avinash.

  27. 38
    Nikolay Aganin says:

    Thanks.

    The post has really good advice with simple explanations!

  28. 39
    Sravani says:

    I am new to reading your blog.

    Your articles are insightful and share a really practical information with us.

    Thank you.

  29. 40
    Diwakar says:

    Great article with simple explanations.

    Thanks for sharing it with us. Now, these are not hidden to me. :)

  30. 41

    Woah!! I did not know many of the things mentioned here about analytics. It's time for me to start learning about Google analytics.

    Thanks a lot Avinash.

  31. 42
    kirsten burnett says:

    It's amazing how you can compile all this data through the use of analytics.

    Finding these connections of how people think and work while using the internet to help further your ability to either provide work for your customers or bring in work for yourself.

  32. 43
    Verna Haynes says:

    Data analysis is very important for any website. This is how they'll find out if how their ranking and site's going. You must get the help of google analytics for that.

    Thanks for sharing such valuable insights. It's really a big help.

  33. 44
    supriya says:

    Hi Avinash,

    Could you please tell me if you have written any post on Omnichannel ( pay online, collect from store) and e-commerce KPIs reporting as well. I am currently working on that..your inputs will be really appreciated.

  34. 46

    Very nice! I really like #8 as it provides direct input to generate hypotheses for AB testing. I'm somewhat more of a conversion guy than pure analytics :)

    It can often show benefits people are looking for, or doubts/questions they want to see answered before buying. Or products/services you don't sell yet of course.

    – Peter

  35. 47
    Sakura says:

    Hello, do you know any recommended forum about web analytics?

    I got lots of questions.

  36. 49
    Philip Easley says:

    I couldn’t be happier to learn about the Time Lag & Path Length features.

    There are some other features I didn’t know about but this one really lets you break down the conversion rate and tell you what you are doing wrong or right.

    Thanks!

  37. 50
    rajiv sharma says:

    Thanks for this valuable information Avinash.

    Web analytics tools seem to be extremely complicated. Your post helps demystify web analytics.

  38. 51
    Davinder Singh says:

    Thanks for sharing this useful information.

    The detail that you shared is extremely useful. It allows me to take action right away.

  39. 52
    Niroshan Samuel says:

    Great post Avinash, based on your loyalty insight we were able to plot graphs content consumption against count of session.

    So that now we know content consumption by time/session for users and we leverage multi-channel re-marketing campaign to guide them to our end goal. Especially our sales cycle around 6-12 months.

    Cheers

  40. 53
    Oremo Ochillo says:

    I could not agree with you more as far as the impressive nature of real time reporting. Google certainly has people that are beyond levels I could ever reach in development.

    Unfortunately what I have found is that real time reporting is great but decisions usually take forever from the powers that be. D

    o you have any suggestions on getting decision makers to speed up decision making and effectively leverage the information found in those real time reports?

  41. 56
    mark shrimpton says:

    Thanks for the great article.

    Analytics is such a minefield when you don't know what you are doing. This will be of great help to many.

    Keep up the awesome work!

  42. 57
    Jacky says:

    Thanks Avinash for this wonderful information. Great information about Google Analytics.

    All digital marketers need to read this. I learn plenty of new things here!

    Thanks.

  43. 58

    Hi Avinash Kaushik,

    Can you solve my question?

    I was trying long enough, create for solutions gallery. It has been a choice of URL, I do not understand what this means.

    Can you explain…..

  44. 60
    Erin O'Brien says:

    Great insights! Thank you! I'm particularly interested in #8. I've linked my GA account with GWT and it's opened the door to additional keyword information.

    One question, when I look at the information found at Acquisition folder > Search Engine Optimization > Queries, it states my website had 120 impressions, with a 83% CTR. Yet, the information found at Acquisition folder > All traffic > Source/Medium states 697 sessions originated through Google/organic. There is such large variation. Are these numbers supposed to match? Does the query tool only report a portion of the search results?

    Thank you!

    • 61

      Erin: It is simply a function of two completely different sources of data, and they'll always show different numbers.

      For small sites, the difference is bigger. For larger sites it gets closer (but still quite different).

      It is important to point out that they are also measuring different things, clicks in one case and visits in another.

      Avinash.

  45. 62

    Hi Avinash

    Great post indeed!

    A question for you: going through your hidden gem #4, I've checked data for one on my analytics accounts and noticed in the Path Length Report that only (?) <40% of conversions were given in 1 interaction (then I understand over 60% of users took two visits or more to make a conversion); however, when I then checked the Time Lag report, I noticed that nearly 75% of conversions were in same day of session: 0 Time Lag in Days.

    Does it mean that people made more visits to my website (as I said 60% two visits or more prior to convert) but all in the same day?

    Or this has to do with a wrong way to track visits?

    • 63

      Andrew: You are right.

      The reports are telling you that 75% of the conversions happened on the same day. A bunch them, 40%, had one interaction and converted on the same day, and rest of them took more than one interaction, but converted via multiple visits on the same day (from your 60% bucket).

      Avinash.

  46. 64

    We absolutely love using Google Analytics but boy has it become difficult over the past few years. It seems with every update it gets more complex and harder to find the keywords in which people are looking for your website.

    Great article and we will try to implement some of these tips!

    ~Kearny

    • 65

      Kearny: You are right that Google Analytics, like every tool that becomes that old and that widely used, is acquiring lots of complexity. The team is aware of this and my hope is you'll see innovation that keeps the complex power, but makes the experience simpler.

      I do want to point out that the keyword thing is not a GA thing. Google, Bing etc. decided that for encrypted search the keyword referrer is not passed to the site. More here: Search: Not Provided: What Remains, Keyword Data Options, the Future

      Avinash.

  47. 66

    I am a big fan of real-time analytics as well.

    Looks to be a really helpful post!

  48. 67

    Great article and that too, straight from an insider.

    Thanks Avinash, I was using analytics for almost six years and missed many of the things listed here. Made My day

  49. 68

    Very useful article. The In-Market Segment data was really useful in our case to target the audience with lesser bounce rate and high session duration.

  50. 69

    Truly enlightening article Avinash.

    I am trying to use the time lag report, but I have one question. If I change the look back window the number of 0 day conversions change. Would you know of a way to sort this and have a look at the real 0 day conversion data? It is my understanding that all conversions that began before the maximum look back window are attributed on 0 day.

    Thank you for your response and again very helpful article and a great blog all in all

  51. 71
    anurao @ TH says:

    The shortcuts part is really really helpful and saved us a tonne of time!

    The other sections are in-depth and greatly helpful for beginners, who usually spend hours searching about analytics tutorials.

  52. 72

    Hi Avinash, This post just blew my mind. Super actionable insights. Love this post too much.

Trackbacks

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