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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.<\/p>\n 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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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).<\/p>\n
Some of these hidden gems<\/em> 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.<\/p>\n 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….<\/p>\n 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<\/strong> . And, that’s not all, when you consider that it is segmented data, across multiple dimensions, it really is impressive.<\/p>\n 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<\/a>] 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.<\/p>\n So, if you were expecting hidden gems<\/em> in a similar spirit, I’m afraid dissatisfaction will follow. My gems<\/em> 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<\/em> that we’ll cover in this post:<\/p>\n <\/p>\n Sounds really exciting, right? Let’s learn why these qualify as hidden gems<\/em>, and how you can extract high-impact IABIs by leveraging them.<\/p>\n <\/a> 1. Affinity & In-Market Segments: Understand Your People Better<\/font><\/strong><\/p>\n 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<\/em> 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!<\/p>\n But.<\/p>\n 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.<\/p>\n My first hidden gem,<\/em> Affinity and In-Market Segments, allow us to get a better understanding of people who engage with our digital existence…<\/p>\n 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.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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…<\/p>\n All the standard Acquisition, Behavior and Outcome<\/a> 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.<\/p>\n My favourite resource to understand all the possibilities of this hidden gem<\/em> , and detail, is here: Analyze users by age, gender, and interest categories<\/a>.<\/p>\n It is important to know that this report and associated features have to be turned on in your Google Analytics account<\/a>. 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).<\/p>\n Use this hidden gem<\/em> and strive to get a better understanding of the people behind your anonymous cookies.<\/p>\n <\/a> 2. Google Analytics Shortcuts: Save Your Complex Views.<\/font><\/strong><\/p>\n There is a difference between reporting and analysis<\/a>. 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.<\/p>\n 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.<\/p>\n The wonderful team at Google released a tiny feature a while back called Shortcut<\/a>. It is on top of every GA report, in the gray bar, right under the name of the report.<\/p>\n I adore it.<\/p>\n Let’s look at an example to understand why.<\/p>\n 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.<\/p>\n 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.<\/p>\n Here’s the report….<\/p>\n 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).<\/p>\n Then, not wanting to lose all this work, and wanting to coming back to it again and again, I hit the Shortcut button.<\/p>\n Now, I can easily find it any time I want in the left navigation bar in Google Analytics…<\/p>\n Oh, the shortcut also remembers I want the main graph to be Page Value and not Sessions. Sweet.<\/p>\n My call to arms to you is to reject standard reports and segments. As you do that, leverage the hidden gem<\/em> called Shortcuts to save your beloved final product.<\/p>\n Next time you need that insight, you’ll get it faster and GA will automatically apply it to the latest time period.<\/p>\n <\/a> 3. Custom Dimensions: Deeper Unique-You Analysis<\/font><\/strong><\/p>\n 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<\/a> .] <\/p>\n 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.<\/p>\n Using custom variables, sorry custom dimensions, is an amazing way to make our dataset in GA unique to us.<\/p>\n 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…<\/p>\n 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.<\/p>\n Custom dimensions requires a small amount of technical work<\/a>, and often requires you to . But it is totally worth it for the higher quality insights, actions and business impact computations you’ll be able to deliver.<\/p>\n 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.<\/p>\n 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.<\/p>\n Take advantage of his hidden gem<\/em> . It is difficult for me to imagine that you could be an analysis ninja without it.<\/p>\n <\/a> 4. Time Lag & Path Length: Pan-Session Ecommerce Analysis<\/font><\/strong><\/p>\n 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).<\/p>\n One hidden gem<\/em> 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…<\/p>\n 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.<\/p>\n 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).<\/p>\n This data has big implications as well.<\/p>\n 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.<\/p>\n The power, of shifting your marketing strategy to pulse at the beat of customer expectations. Magical.<\/p>\n 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…<\/p>\n Again, amazing insights can come from this data as well.<\/p>\n Both these reports can be segmented, click on Conversion Segments<\/a> at the top of the report. If you have Macro and Micro-Outcomes<\/a> (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!<\/p>\n 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!). <\/p>\n <\/a> 5. Assisted Conversions: Smarter Marketing Impact Attribution<\/font><\/strong><\/p>\n 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<\/em>, rather it is Avinash keeps talking about this all the time gem<\/em>.<\/p>\n 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.<\/p>\n This is what the report looks like for one of my businesses…<\/p>\n 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).<\/p>\n 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.<\/p>\n Clicking on any one of the channels above, will lead you to a lovely drilldown report that shows detailed performance for that channel….<\/p>\n The above report proves my statement, all data in aggregate is crap<\/em>! 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).<\/p>\n Another hidden gem<\/em> for this hidden gem<\/em>.<\/p>\n 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…<\/p>\n 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.<\/p>\n 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.<\/p>\n Real. Golden. Stuff.<\/p>\n 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<\/a>. 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.<\/p>\n <\/a> 6. Custom Alerts: Get YourKnown Unknowns!<\/em><\/font><\/strong><\/p>\n 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<\/a>.]<\/p>\n 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<\/em> 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.<\/p>\n 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…<\/p>\n 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.<\/p>\n So it’s not just an alert, it’s an alert when something truly worth being alerted to is happening.<\/p>\n (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<\/a>, and your tactical big priorities.)<\/p>\n Here’s an excerpt of some of the alerts in my account. You can easily see what’s most important to me.<\/p>\n You can get pretty creative with what you do.<\/p>\n I’ve been on a recent rampage on re-focusing audiences on computing Customer Lifetime Value<\/a>. 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.<\/p>\n Here’s the alert I’d created for that purpose…<\/p>\n 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!<\/p>\n 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!).<\/p>\n If you would like to explore all your possibilities, and learn more: Identify The Known Unknowns: Leverage Analytics Custom Alerts<\/a>.<\/p>\n Your journey begins in the Admin section, in the View column, scroll down to Custom Alerts and click on New Alert. God speed!<\/p>\n <\/a> 7. Download Solutions: Benefit From The Wisdom Of Crowds<\/font><\/strong> <\/p>\n Enough of doing all the work ourselves. Time to mooch of others!<\/p>\n I mean, take advantage of our community of amazing peers who have already created an incredible collection of solutions!<\/p>\n I am surprised at how few people take advantage of the Google Analytics Solutions Gallery.<\/p>\n 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!).<\/p>\n The button you are looking for is called Import from Gallery…<\/p>\n 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…<\/p>\n 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<\/a>. 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.<\/p>\n As soon as you are done with that, scroll through the most popular, and download the ones that are the most relevant.<\/p>\n 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… <\/p>\n One of the ones you’ll find is my Market Motive Mindblowing Attribution Model<\/a>, uploaded in the Solutions Gallery by my dear friends at Loves Data<\/a>, with one click.<\/p>\n 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.<\/p>\n 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.<\/p>\n While you are at it, you can easily download the dashboards, reports and segments uploaded by the smart people at Loves Data<\/a>…<\/p>\n Or whatever else you are in need of.<\/p>\n For example, custom reports for search engine optimization<\/a>. With all the Social Media ROI pressure you might find the social media dashboards<\/a> to be handy. Or anything else your boss is yelling he needs!<\/p>\n The Solutions Gallery is a great hidden gem<\/em>, take advantage of your generous peers, and reduce time to market.<\/p>\n <\/a> 8. Search Queries: Get Your Organic Keyword Data Back!<\/font><\/strong><\/p>\n Ok, so perhaps the exclamation mark is a bit of an exaggeration. But, this is still a valuable hidden gem<\/em>.<\/p>\n 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%.<\/p>\n But what Google taketh, Google giveth back some.<\/p>\n In your Google Webmaster Tools<\/a> 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.<\/p>\n What is a hidden gem<\/em> is the fact that you can also get all this data inside Google Analytics! Acquisition folder > Search Engine Optimization > Queries…<\/p>\n In my case for the current time period I see 4,136 search queries that were performed on www.google.com<\/a> 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.<\/p>\n 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<\/a> is a smart idea. Well, you can’t do that inside GA any more.<\/p>\n What you can do though, is take data out of Google Analytics…<\/p>\n And, then do the analysis outside GA. Small victory.<\/p>\n 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<\/em>. Just link your GWT data with GA<\/a>.<\/p>\n [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<\/a>]<\/p>\n <\/a> 9. GA Applications: Your Everyday Challenges Amazingly Solved!!<\/font><\/strong><\/p>\n You just saw above the simplest way to download your data from Google Analytics. You can do a lot more!<\/p>\n The Google Analytics API<\/a> 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<\/a> is astoundingly good, and even lay folks like you and I can use it to explore the API and do cool stuff!]<\/p>\n For us, the hidden gem<\/em> is the Google Analytics Application Gallery<\/a>. 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.<\/p>\n 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.<\/p>\n And, that is just three of ’em!<\/p>\n There are tools that automate site audits<\/a> so that you can make sure you are collecting data accurately (try Check My Analytics<\/a>). There are dashboarding and visualization solutions<\/a> (try Tatvic<\/a> or NextAnalytics<\/a>). There are Search Engine Optimization<\/a> tools (try Analytics Portfolio<\/a>). Way too many business intelligence options<\/a>, and mobile solutions and email integrations and tag management and ecommerce and content management and everything else under the sun.<\/p>\n The App Gallery has both free and paid solutions. For all free solutions, click here<\/a> and then from the left nav choose the category you are interested in.<\/p>\n 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<\/em> 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).<\/p>\n Boom! Happiness!<\/p>\n <\/a> 10. Shopping Behavior Analysis: Funnel Your World!<\/font><\/strong><\/p>\n My last recommendation is perhaps a hidden gem<\/em> 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<\/a> 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! :)<\/p>\n The hidden gem<\/em> is the Shopping Behavior Analysis<\/a> report.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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! :)<\/p>\n 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<\/em> is so great. One report explains with clarity important issues, and kicks of very actionable next steps.<\/p>\n There are two additional cool possibilities.<\/p>\n 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.<\/p>\n 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.<\/p>\n 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…<\/p>\n 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).<\/p>\n Now we can separate out various users and their behavior on the site. What is up with our marketing team not buying anything?<\/p>\n And, the super amazingly useful segmentation of user behavior by Source…<\/p>\n 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.<\/p>\n 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.<\/p>\n Phew!<\/p>\n We are done.<\/p>\n Ten hidden gems<\/em> 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?<\/p>\n <\/a> But, wait! There’s more…<\/font><\/strong><\/p>\n These gems<\/em> are not the end of the story of course. There are others like Channel Groupings<\/a> that allow you to change the way you categorize traffic. This can be often useful. There is an additional feature called MCF Channel Groupings<\/a> 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<\/a>. The Site Speed reports<\/a> are a wonderful hidden gem<\/em> – I wish more people understood how critical speed on multiple desirable dimensions.<\/p>\n Then there are standard features that we’ve talked about so much, but so few people use. Advanced Segments<\/a> and Custom Reports<\/a> (Known Knowns<\/em>!)<\/em>. 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!<\/p>\n There is a lot to do. It is exciting to be an Analysis Ninja.<\/p>\n As always, it is your turn now.<\/p>\n I would love to hear what parts of Analytics do you consider to be a hidden gem<\/em>? Are there reports, segments, analysis possibilities, alerts, applications, data collection strategies that have elevated your analytical game? Which of the above ten hidden gems<\/em> 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?<\/p>\n 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.<\/p>\n Thank you.<\/p>\n","protected":false},"excerpt":{"rendered":" Even your best over-estimation of Google Analytics’ scale will under-estimate it by 100x, minimum. In that context, Real-Time reports are […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[11,9,12,10],"tags":[45,349,257,234,27],"class_list":["post-7046","post","type-post","status-publish","format-standard","hentry","category-advanced-analytics","category-web-analytics","category-web-insights","category-web-metrics","tag-actionable-web-analytics","tag-custom-reports","tag-excellent-analytics-tips","tag-google-analytics","tag-web-analytics-tips"],"acf":[],"yoast_head":"\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_real_time_data.png\")
<\/p>\n\n 1. Affinity & In-Market Segments: Understand Your People Better<\/a>
\n 2. Google Analytics Shortcuts: Save Your Complex Views<\/a>
\n 3. Custom Dimensions: Deeper Unique-You Analysis<\/a>
\n 4. Time Lag & Path Length: Pan-Session Ecommerce Analysis<\/a>
\n 5. Assisted Conversions: Smarter Marketing Impact Attribution<\/a>
\n 6. Custom Alerts: Get Your Known Unknowns!<\/em><\/a>
\n 7. Download Solutions: Benefit From The Wisdom Of Crowds<\/a>
\n 8. Search Queries: Get Your Organic Keyword Data Back!<\/a>
\n 9. GA Applications: Your Everyday Challenges Amazingly Solved!!<\/a>
\n 10. Shopping Behavior Analysis: Funnel Your World!<\/a>
\n ##. But, wait! There’s more…<\/a> \n<\/div>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_interests_affinity_in-market_segments.png\")
<\/p>\n![\"in-market](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/in-market_segments_detailed_report.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_shortcuts_report.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_shortcuts-1.png\")
<\/p>\n![\"custom](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/custom_variables_google_analytics.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_path_length_report.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_time_lag_report.png\")
<\/p>\n![\"assisted](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/assisted_conversions_report.png\")
<\/p>\n![\"assisted](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/assisted_conversions_report_organic_search.png\")
<\/p>\n![\"assisted](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/assisted_conversions_social_media.png\")
<\/p>\n![\"twitter](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/twitter_custom_alert_google_analytics.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_custom_alerts-4.png\")
<\/p>\n![\"lifetime](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/lifetime_vlaue_post_interest_increase.png\")
<\/p>\n![\"import](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/import_from_gallery.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_gallery_bundles.png\")
<\/p>\n![\"attribution](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/attribution_models.png\")
<\/p>\n![\"loves](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/loves_data_solutions.png\")
<\/p>\n![\"search](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/search_engine_optimizatoin_report-2.png\")
<\/p>\n![\"export](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/export_to_excel.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analtyics_application_gallery.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_shopping_behaviour_analysis.png\")
<\/p>\n![\"google](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/google_analytics_shopping_behaviour_analysis_direct.png\")
<\/p>\n![\"shopping](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/shopping_behaviour_analysis_direct_new_returning.png\")
<\/p>\n![\"shopping](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/shopping_behavior_user_category_abandonments.png\")
<\/p>\n![\"shopping](https:\/\/www.kaushik.net\/avinash\/wp-content\/uploads\/2015\/04\/shopping_behavior_source_abandonments.png\")
<\/p>\n