How to create insights from consumers’ click histories

Without any action behind it, data is just a bunch of numbers. Clickstream data is particularly valuable, providing insights about what consumers are doing.

Data alone does not lead to insights. Analyzed data backed by a hypothesis and placed in the right context, on the other hand, does.

Clickstream information is a particularly good set of data for marketers to examine if they want to understand their customers better and connect with them based on their actions.

The many benefits of clickstream data

With clickstream data, you can examine not only how customers are interacting with your brand, but also what they are doing before and after they arrive at your site.

Clickstream information is based on consumers’ actual click and browsing behaviors, with records of click-throughs and URLs visited collected in the order they occurred, giving marketers important, industrywide insight into online behavior, the customer journey through the funnel, and user experiences.

Rather than providing simple numbers of visits or sales, clickstream information reflects consumer behavior based on their activity and identifies areas companies could improve where the competition might be doing it better.

The insights garnered from clickstream data may not always match your hypothesis, but they are always useful if you ask the right questions.

Don’t collect data just because numbers are nice to fall back on. Instead, focus on collecting information like click history that is directly tied to your business objectives and key performance indicators.

Identify what you want to learn, and focus your collection and analysis on that specific data subset.

Make the most of your clickstream data

Creating actionable insights out of your data is essential to portraying a full and accurate picture of the customer journey. Maximize the effectiveness of your clickstream analysis by employing these three tactics:

1. Have a hypothesis

This is a minimum requirement for a data project to be efficient and lead to insights. Without a hypothesis, you’re just wasting time. The more specific you are in your data requests, the easier it is for your data team to pinpoint exactly what they need to pull, analyze, and provide.

You don’t have to be sure of the outcome, and the data may prove you wrong, but that’s OK. Just be sure your data team enters a project focused and that they reach a conclusion.

Let’s say you run a display campaign to drive awareness and clicks to your own site for a product. If you sell that product through third-party distributors, like Amazon or Target, your hypothesis might be that your display campaign is influencing purchase behavior and conversions on these third-party sites. Without clickstream data, it’s very hard to connect those two pieces and prove or disprove this hypothesis.

2. Tie your analysis to KPIs

Your analysis might reveal plenty of information about how consumers reach and interact with your brand or with your competition, but not all information yields actionable insights. You might find that consumers searching your website tend to search three times. That’s interesting, but you don’t gain real insights from it without understanding how their search activity affects their subsequent behavior or how it differs from consumer search activity on competitors’ sites.

Structuring your hypothesis and analysis around KPIs diminishes the risk of reaching insights that are not actionable. If your leading KPI is, say, trial subscriptions, look into the trial conversion flow of your competitors, and reverse engineer their customer journey through the funnel to detect conversion and abandonment trends at each step.

If the vast majority of consumers bounce during step three of five on your site (but not on your competitors’ sites), test out consolidation steps to improve the user experience and increase conversions.

3. Identify your output goals

Without a clear goal for what you intend to do with clickstream data, you cannot transform it into actionable insights. Are you studying customer journeys to optimize conversions or user experience? Are you looking for details about PR or case studies to grow brand awareness and generate leads?

Answering these questions and setting intentions for your data will help you in many ways, from filtering data requests from the get-go to guiding your thought process when focusing your data request and analysis.

By analyzing customers’ online actions – clicks, purchases on other sites, and their browsing history — with specific output goals, you reveal a world of insight into how they interact with your brand’s web properties, your competition, and how they react to your offering.

Don’t collect clickstream data just for the sake of collecting it. Understand what you want to investigate and how you can benefit from it. Make sure it’s relevant to your company, and then analyze clickstream data to better understand your customers’ actions and optimize their experience.

Marketers need to go beyond just the numbers and patterns that data provides if they want to successfully understand and connect with consumers. Focusing on customer actions will lead to a better understanding of your audience and what resonates with them, increasing the success of your marketing efforts and, ultimately, creating a better business.

This is an abridged version of an article published earlier this week on our sister site ClickZ.

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17 inspirational examples of data visualization

We can all collect masses of data, but it only becomes genuinely useful when we use it to make a clear point.

This is where data visualization comes in. Showing data in context and using creativity to make that same data tell a story can truly bring the numbers to life.

There are a whole bunch of data visualization tools out there to help create your own, but here are some existing examples for inspiration.

A day in the life of Americans

This excellent visualization from Flowing data uses information from the American Time Use Survey to show what Americans are up to at any time of day.

What streaming services pay artists

This from the wonderful information is beautiful website, looks at how the major online streaming music services compare in terms of paying the musicians.

Two centuries of US immigration

This fantastic visualization from metrocosm shows the various waves of immigration into the United States from the 19th century to the present day.

US population trends over time

This gif from the Pew Research Center is a great example of how movement can be used to convey shifts and trends over time.

Why you should take the bus

The German town of Münster produced this series of images back in 1991 to encourage bus use. It’s beautifully simple showing the relative impact of the same number of people (72) on bicycles, in cars, or on a bus.

What happens in an internet minute?

This infographic from excelacom presents what happens online in 60 seconds, including:

• 150 million emails are sent.
• 1,389 Uber rides.
• 527,760 photos shared on Snapchat.
• 51,000 app downloads on Apple’s App Store.
• $203,596 in sales on Amazon.com.

US wind map

This moving visualization shows wind speed and direction in real time.

It looks great and is easy to understand, which is key to effect data visualization. This one comes from hint.fm.

Daily routines of creative people

I’ve always been pretty cynical about this ‘X things successful people do before breakfast’ stuff – as if by following this, people are suddenly going to become Steve Jobs or Albert Einstein.

However, this one from podio showing daily routines of creative people is very interesting. It won’t turn you into a great composer, but it’s a fascinating insight nonetheless.

The impact of vaccines

This is a series of visualizations from the Wall Street Journal, which shows the impact of vaccines on various infectious diseases.

It’s striking stuff, which clearly demonstrates the incredible positive impact of vaccination programs in the US.

London food hygeine

This is a great use of freely available data to provide useful information for the public.

The one million tweet map

This uses tweet data to present a geographical representation of where people tweet about topics. The example below is for ‘Brexit‘.

The fallen of WW2

This, from Neil Halloran is a cross between data visualization and documentary.

There are two versions of this. The video version you can see embedded below, and an interactive version.

People living on earth

A simple but very effective visualization of the world’s population, and the speed at which it increases.

The ultimate data dog

This, again from Information is Beautiful, uses data on the intelligence and other characteristics of dog breeds, plotting this against data on the popularity of various breeds from the American Kennel Club.

How much did band members contribute to each Beatles album? 

This from Mike Moore, shows the relative writing percentage for each Beatles album, as well as the contribution over time.

A day on the London Underground

From Will Gallia, who used data from a single day’s use of the London underground to produce this timelapse visualization.

Fish Pharm

This is from way back in 2010, and illustrates the fact that antidepressants and other pharmaceuticals are now showing up in fish tissue.

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How to improve your CTR using Google Search Console

Last month I wrote a comprehensive guide on how to use Google Search Console, covering every aspect of what is essentially a giant toolshed full of useful stuff for all webmasters to use.

It was exhaustive, and probably exhausting. Don’t read the whole thing in one sitting, just dip in and out when you come across something you’re unsure about.

While wading through Search Console’s huge amount of features, I noticed a few elements that deserved to be highlighted, not only because I had no idea they existed or were even accessible to webmasters, but also because they may be able to help raise your click-through rate (CTR) on search engine results pages (SERPs), or at the very least, show you where to improve.

The first thing you need to be aware of is this… You can see all the search queries that bring traffic to your site in Search Console.

Yeah it was a massive pain when Google encrypted your search terms Google Analytics and replaced them with the ambiguous (not provided) but at least you can still find them here…

Just go to Search Console, then click on Search Traffic>Search Analytics.

There you go, a veritable bounty of delicious search terms, keywords and traffic-generating pages.

Now here’s the really good bit…

How can I use Search Console to help improve my CTR?

As I said in my original Search Console walkthrough, here you can toggle between a variety of options, filters and date-ranges.

Here are the Impressions and CTR for my own website Methods Unsound for April 2016:

Using this simple overview, ordered by number of impressions, I can see which posts have the highest visibility, but also the ones with a relatively low CTR.

Perhaps all these pages need is a tweak of a meta-description or the addition of some structured data?

And that’s what I did. I went through every article in the top 20 with particularly low CTR compared to impressions, and I made a number of changes to them in the CMS, including using the recommendations as featured in my guide to writing meta descriptions and guide to writing title tags.

These included:

• Making sure the most important keywords for the webpage showed up in the meta description.
• Making sure the most important keywords were first in title tags.
• Rewrote meta descriptions so they were more legible and meaningful.
• Made sure the meta descriptions were as compelling and as relevant as possible.
• Made sure meta descriptions were no longer than 135 – 160 characters long
• Made sure title tags were 50-60 characters long, including spaces.
• Made sure headlines (<h1> tag) were different from the title tag.
• Removed duplicate meta descriptions and title tags.
• Used rich snippets, in the form of Schema markup, to add elements such as visible star ratings to my results.

The results

Looking at the following 30 day period’s Impressions and CTR, here’s what I achieved in making these small changes…

If you look in the two last columns you can see the CTR for both April and May, and if I’m terribly honest it hasn’t been a ‘resounding’ success, but there has been some small improvements to a few of the pages…

Page 2 saw a 0.10% increase. Page 3 saw a 0.02% increase. Page 4 had a much more impressive 4.5% increase. Page 5 had a 0.64% increase. Page 10, a 0.73% increase…

Overall, the average CTR for the site has risen from 2.7% to 3.37%, but as you should already be pointing out, this can also be attributed to wealth of other factors – seasonal changes in traffic, algorithm fluctuations, general site health – and not the general on-page improvements to a handful of posts.

Also, sadly, a few of the pages’ went down in terms of CTR, and although I could blame the fact that most of those pages are more review and news based – and therefore have a limited shelf-life – that’s not strictly true for all of them.

This is far from an exact science, and clearly I have more work to do when it comes to my own on-page improvements. And for another test such as this, it would definitely be better to make changes to more evergreen posts (i.e. anything that’s not a review, news item or a specific timed event).

But what my intention is here is to show you that using Search Console you can clearly see which of your posts are doing well in terms of visibility but poor for click-through, and that by using some basic SEO techniques, you may be able to make a difference.

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15 data visualisation tools to help you present ideas effectively

The number of digital skills you need in order to be a functional and useful member of your organisation are increasing at a rate you might be struggling to keep up with.

As well as the ability to understand your analytics and be fully aware of basic SEO skills, you need to be able to present information and data in the clearest manner possible to members of your team and, of course, your senior management.

Luckily you don’t have to be a graphic design wizard to achieve this.

Here is a list of various free and premium visualisation tools that will help you communicate your ideas in a variety of formats, for a range of different experience levels. Hopefully you’ll pick up some impressive new skills here too.

Silk

With Silk you can publish attractive looking webpages featuring a variety of different interactive visualisations, based on your data-sets. These can exist as standalone pages, linking back to your own site for a little SEO benefit, or you can embed them wherever you like.

Sketch

Think of Sketch as a much easier to use, far more intuitive and BS-free version of Photoshop that’s also a damn sight cheaper. I’m including it here because after a recommendation from my learned friend Chris Lake, within the afternoon I had installed Sketch, messed around for a couple of hours and finished a fairly complex but crystal-clear multichannel content marketing plan. I love it.

Google Fusion Tables

Fusion Tables is a web app that allows you to gather, visualize, and share data tables.

You can filter and summarize across thousands of rows, then adapt the data to an embeddable and shareable chart, map or custom layout. Plus all your data organization is automatically saved in Google Drive.

Piktochart

I’ve recommended Piktochart so many times – as has everyone else on the internet in the business of making your data-vizs and infographics look brilliant. It’s just so easy to use and the templates help you achieve results very quickly.

Gephi

Gephi is an open-source data-viz tool for graphs and networks. It also allows for exploratory data, link and social analysis.

Easle.ly

Easle.ly possibly has the most satisfyingly meta-textual name on this list. It also has 1,000s of infographic templates at your disposal, as well as the ability to create one from scratch.

Hohli

Need a simple bar chart, line chart, venn diagram or graph rustled up in a flash, without any extra complicated bells and whistles? Hohli should have everything you need.

Gliffy

Gliffy allows you to make great looking flowcharts and diagrams, but its secret weapon is the fact it has collaboration at its core.

Infogr.am

Infogr.am has a really beautiful collection of templates for data-visualisation, possibly some of the best looking here, and it’s very easy to use.

Leaflet

With Leaflet, you can create incredible looking maps, that are fully interactive and mobile friendly, with tonnes of customisable features.

D3

D3 basically stands for data driven documents, but there is little basic about this tool. In fact, you should probably only use this one if you have some expertise already. However the results can be more than worth the work.

Bime

The analytics workspace, Bime has a great eye for stylish design, and its multi-device capabilities are impressive. Although it does come at a premium.

Chartblocks

The “world’s easiest” bar chart building app, plus also one of the nicest looking and quickest to use too.

Dygraphs

Dygraphs lets you make interactive charts which you can mouse over to highlight individual values, then click and drag to zoom-in, zoom-out or pan around.

Timeline

With Timeline you can create embeddable sequential timelines by uploading your data from a Google Spreadsheet. Each timeline is customisable and interactive, plus even though it’s open source it’s relatively easy to use for beginners.

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Tie your web, and mobile properties together in Search Console, plus three more recent changes

Since writing our comprehensive and barn-stormingly popular complete guide to Search Console a couple of weeks ago, Google has since released a few updates to make webmasters lives a darn sight easier.

We’ll discuss a few of these later in the article, but first let’s reveal the news that Google Search Console now lets you tie all your managed multi-platform sites together and track the combined visibility in search.

Search Console just launched a way to tie your sites together; something wanted by lots of people! https://t.co/FskytBdeyL

— John Mueller (@JohnMu) May 23, 2016

This feature is called ‘Property sets’ and will be found in the Search Analytics section of Search Console.

From the post on the Webmaster Central blog:

“[Property sets] lets you combine multiple properties (both apps and sites) into a single group to monitor the overall clicks and impressions in search within a single report.”

So all those separate platforms you operate for one single brand – websites, mobile sites, apps – you’ll be able to treat as a single entity if you wish. You can even add HTTP or HTTPS versions of the same site and combine multiple apps.

All you need to do is

1. Create a property set
2. Add the properties you’re interested in
3. The data will start being collected within a few days

This aggregated data from across all properties will be found in the Search Analytics section and you’ll be able to check everything from clicks, to impressions to CTR, as you would normally with single properties.

The roll-out will take place in the next couple of days.

This follows a few new recent features announced for Search Console:

Deeper integration of Search Console in Google Analytics

Google introduced the ability to display Search Console metrics alongside Google Analytics metrics, in the same reports earlier this month.

The new Search Console tab combines the data from both Search Console and Google Analytics, into one report. Previously you’ve only been able to see these in isolation.

As Google says, “By combining data from both sources at the landing page level, we’re able to show you a full range of Acquisition, Behavior and Conversion metrics for your organic search traffic.”

Search Analytics now has an AMP filter

As I reported last week, Google has just started rolling out an accelerated mobile pages filter in the ‘Search Analytics’ report.

Just head to the ‘Search Appearance’ option on the top filter selection and you’ll be able to see any queries that brought mobile searchers to your AMP content.

Google has also introduced ‘Rich Cards’ markup

And finally (for now) Google is also rolling out a new search result format, based on its rich snippets, that use schema.org structured markup to display results in a more visually engaging format, called Rich Cards…

You’ll only be able to markup recipe and movie review posts with Rich Cards, they will initially appear in mobile search results in English for google.com and there is already a Rich Card report set up in your Search Console…

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Google launches Firebase Analytics for mobile apps

Google has launched Firebase Analytics, a new analytics solution for mobile apps, at this year’s I/O 2016 developer conference. 

Firebase was acquired by Google in late 2014 and helps developers build apps for Androids, iOS and the Web. Current features include Realtime Database, User Authentication and Hosting.

However, based on app developer feedback, Firebase is adding more tools to help developers improve app quality and the acquisition and engagement of app users. It is also introducing new monetization tools.

Firebase Analytics

These new tools are all tied together by Firebase Analytics. The analytics platform is free and unlike Google Analytics, it is designed specifically for mobile apps.

That means instead of focusing on page views, impressions or sessions, developers can see what users are doing inside the app, how paid advertising campaigns are performing with cross-network attribution and where users are coming from.

All this can be viewed from a single dashboard.

Audiences

A feature called Audiences allows developers to define groups of users with common attributes. Once defined, these groups can be accessed from other Firebase features. We will come back to Audiences in a bit.

Crash Reporting

Developers will now be able to better understand why an app crashes using Firebase Crash Reporting. This is a set of actionable reports developers can use to diagnose and fix problems on both iOS and Android apps.

The tool is connected to Audiences in Firebase Analytics and will let developers see if users on a particular device, in a specific geography, or in any other custom segment are experiencing elevated crash rates.

Cloud Test Lab, (announced at Google I/O 2015), is now Firebase Test Lab for Android. Test Lab lets developers find problems in their apps before their users do by facilitating automatic and customized app testing on real devices hosted in Google data centers.

Notifications and Dynamic Links

Firebase wants to help developers grow and re-engage app user bases with the following features:

• Firebase Notifications is a user interface (UI) built on top of the Firebase Cloud Messaging (FCM) APIs. It allows notifications to be delivered to users without writing a line of code.
• Firebase Dynamic Links makes URLs more powerful in two ways. Firstly, links persist across the app install process so users are taken to the right place when they first open the app. Secondly, the destination of a link can be changed based on run-time conditions, such as the type of browser or device. This can be applied to web, email, social media, and physical promotions for insight into growth channels.
• Firebase Invites allows users to share referral codes or content via SMS or email to their networks. The idea here is to turn customers into advocates.
• Firebase App Indexing (formerly Google App Indexing), brings new and existing users to an app from Google searches. If the app is already installed, users can launch it directly from the search results. New users have the option to click a link to install the app.
• AdWords, Google’s advertising platform for user acquisition and engagement, has been integrated into Firebase. That means Firebase can now track AdWords app installs and report lifetime value to the Firebase Analytics dashboard. There are a number of cool things that can be done here. Among them, the Firebase Audiences tool can be used in AdWords to re-engage specific groups of users and in-app events can be defined as conversions in AdWords.

Storage

Google’s cloud-to-device push messaging service Google Cloud Messaging (GCM) is being integrated into Firebase’ s backend and has been renamed as Firebase Cloud Messaging (FCM).

FCM is a free service with unlimited usage and supports messaging on iOS, Android and the Web. James Tamplin, product manager, Firebase, says FCM has been optimized for reliability and battery-efficiency. (It currently sends 170 billion messages per day to two billion devices.)

In response to requests to be able to better store and download images, videos and large files, Firebase has launched Firebase Storage. This feature is powered by Google Cloud Storage.

Firebase Remote Config gives developers instantly updatable variables that they can use to customize apps in real time. Features can be enabled or disabled without having to publish a new version and can be customized for different audiences.

Backend products Firebase Realtime Database, Firebase Hosting and Firebase Authentication have been updated.

Monetization

AdMob has been integrated into Firebase. This tool lets developers choose ad formats, including native ads.

Finally, Firebase has a new home: firebase.google.com.

Here’s a short video explaining some of the new features:

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Google Search Console: a complete overview

Do bounce rates affect a site’s search engine ranking?

The bounce rate debate continues…

Bounce rates and how they affect a website’s ranking on Google has been discussed, dissected, and dismembered over and over again.

As fully transcribed on this site, a conversation between Rand Fishkin, CEO of Moz, and Andrey Lipattsev, Google’s search quality senior strategist, led to a surprising discussion on click and bounce rates affecting search rankings.

Rand stated that he has recently been running a few experimental tests with various crowds of 500 to a couple thousand people.

Everyone participating was prompted to take out their cellphones, laptops, and digital what-have-yous and perform a specific search. Once the search listing appeared, he had everyone in the crowd click one of the listings at the bottom of the results page and then click away from that site. He then monitored the results over the next few days.

Rand found a whole bunch of inconsistencies. In a little more than half of the experiments, the ranking did change on the search engine results page (SERP), and in a little less than half of the experiments, the rankings did not change.

This begs the question:

Do bounce rates affect a site’s search engine ranking? If so, how much?

Lipattsev believes that for each individual search query in the experiment, the generated interest regarding those specific searches impacts the rankings change rather than just the clicks and bounces.

He said that if a certain topic is gaining a substantial amount of searches and an increase in social media mentions, Google would pay more attention to that rather than a site getting more clicks.

Lipattsev says that it is certainly doable to determine exactly what causes a large rankings jump for an individual listing, but Internet-wide, it is much more difficult.

All this being said, what actually is a bounce rate?

The bounce rate is the percentage of visitors to a particular site who navigate or “bounce” away after only viewing that individual webpage.

Usually, the term ‘bounce rate’ has a negative connotation associated with it. People think that if a visitor only visits one page and then leaves, it’s bad for business. Their logic isn’t that flawed, either. After all, a high bounce rate would indicate that a site does not have the high-quality, relevant content Google wants out of its top ranked sites.

A great Search Engine Journal article shows nine negative reasons why your website could potentially have a high bounce rate, including poor web design, incorrect keyword selection, improper links, and just bad content. It’s true that these high bounce rates can reflect poorly on a website… sometimes.

So, what gives?

Having a high bounce rate on something like a ‘contact us’ page can actually be a good thing. That’s more of a call-to-action site, where the goal of that particular page is to have the user find the contact information, and then actually contact the business. The visitor got what they came for and then left. Extra navigation around the website doesn’t really mean anything in this case.

Of course, if your site is more content-driven or offers a product or service, then your goal should be to have a higher click-through rate (CTR) and more traffic to each page.

But what about Google?

Does Google know your bounce rate and are they using it to affect rankings? This Search Engine Roundtable article provides the short answer (which is “no”).

Many organizations don’t use Google Analytics, so Google has no way of tracking their bounce rate information. And even with the analytics that they can trace, it’s difficult to determine what they actually mean because every situation is different.

There are many factors that go into determining how long a visitor stays on a particular webpage. If a visitor remains on a site for over 20 minutes, they could be so engaged with your site’s content that they can’t even imagine leaving your wonderful webpage… or… it could mean they fell asleep at the screen because your website was so boring. It’s too difficult to tell.

If you are operating one of those websites that should have a lower bounce rate, these tips on lowering that number should be able to help. Some highlights include making sure each of your pages loads quickly, offers user-friendly navigation, avoids cluttered advertisements, and features quality content!

If bounce rates don’t affect Google’s rankings as much as you thought, you wonder how significant other ranking factors are. Well, Google recently revealed that magical information. They narrowed it down to three top ranking factor used by Google to drive search results:

• Links: strong links and link votes play a major role in search rankings.
• Content: having quality content is more important than ever.
• RankBrain: Google’s AI ranking system.

It’s no shock that links and content matter, but RankBrain is still relatively new. It’s Google’s new algorithm to help determine search results (after factoring in links and content). RankBrain filters more complex searches and converts them into shorter ones, all the while maintaining the complexity of the search, thusly refining the results.

Google’s newest AI technology – and whatever other secret technologies they are working on – may resolve the never-ending debate over bounce rates, but it’s certainly going to be a difficult process.

More research is to come and Andrey believes the challenge to make bounce rate click data a strong and measurable metric is “gameable,” but Google still has a long way to go.

“If we solve it, good for us,” Andrey said, “but we’re not there yet.”

There is no one-size-fits-all answer when it comes to SEO and all its intricacies. The greatest answer to any SEO question is always “it depends.”

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Taking your analytics practice to the next level

As both a Googler and ClickZ team member, I recently attended and participated in the always-inspirational ClickZ Live New York event.

Along with Katie Morse, Vice President, Social and Search at Nielsen and Pierce Crosby, business development and experienced data analyst at StockTwits, we had a panel discussion on how brands can take their analytics practice to the next level.

First, a quick description of the panel:

Data has become everyone’s domain, in all aspects of your marketing and business. Most companies do a good job at collecting and reporting data and have a basic process in place. But many are stuck as to what to do next to elevate value of data in their company.

As our conversation, and those questions the audience asked, were so good, I wanted to pull out some of the best questions and summary of answers we shared with attendees.

Pierce, Katie, and Adam presenting at ClickZ Live NYC. Photo by Search Engine Watch columnist Thom Craver (used w/permission).

1. Most companies have varying groups that need access to analytics insights. How do you efficiently get them all what they need and how do you ensure it’s most useful for them?

The answer is process. Ensure that you have the right metrics delivered to the right people at an anticipated frequency. Also ensure that you have conducted proper resource allocation in order to allow time not just to share dashboards, but flesh out insights for your teams to take action on.

If you are just delivering dashboards without context, you’re not doing your job. Actually, you’re performing the job a script can do – which isn’t a good place to be.

The more formalized you can be with your processes, the better, as this will make you incredibly efficient and free up time for the creative, valuable (and fun!) analyst projects.

2. How do you see a breakdown of time spent on analytics between data capture, reporting, and analysis? What are the best ways to help get organizations to move up the value chain?

The more time you can spend on analysis, the better. But if you’re not capturing the right data and reporting it in an articulate way, your analysis won’t be accurate or defensible. That’s why it’s important to spend time up front on ensuring your data quality is excellent and you’re effortlessly generating beautiful reports.

Need some hard numbers to serve as a guideline? Aim for 10% of time spent on data capture, 20% on reporting, and 70% on analysis and delivering insights to your team (my previous ClickZ column goes over the reporting part in more detail).

The way to get an organization to move up the value chain is easy: trend down the time you spend on capture and reporting. It’ll happen organically.

3. Can you talk about how you are using data across tactics — such as how does search inform social, email or other areas of marketing?

Data should not exist in a silo. You should be using it to inform everything you do, and you should be using it to understand your users, not simply to fill in dashboards.

For example: if you notice visitors to your ecommerce site are frequently querying a product name or type you don’t have in site search, you should share this data with your product team and persuade them to offer it. Marketing isn’t just about promoting products anymore.

Marketing now needs to be involved in the actual strategic decisions companies make, and data is how we get a seat here. Our user data should be informing what we do next, not just showing successes of our sites and apps. This all starts with breaking down silos and using insights cross functionally – beyond marketing.

4. Let’s talk about goal setting: how you can quantify success outside of just ROI? What are some other metrics that we might want to take a look at?

ROI in dollar terms is great. Everyone can understand this, especially your CFO. But generating revenue is just one outcome from your marketing and content, and just one thing to optimize.

For example, if your call center or social CRM team notices a recurring question about your company’s product they have to answer repeatedly, that’s a huge opportunity. What you need to do in this type of situation is measure what your user’s problems are and use this information to power answers in an automated / self-service fashion such as an FAQ page on your site or chatbot.

Creating this type of content in a data-driven manner can help trend down easily answered questions, freeing up your customer service team to focus on tougher problems which require a human touch and making your customers happier by simply getting the information they need immediately. That’s a win-win: and very measurable!

5. What are some actionable ways or things we could all do to become better at analyzing the “what happened” and “why” at our metrics?

This is an area of practice makes perfect. The answer is to hire skilled leaders for your team that can inspire and grow your team’s analyst skills. But personal growth helps too: so attending events like ClickZ Live, trainings and courses (such as our Analytics Academy) and reading blogs and books (like Avinash’s definitive book, Web Analytics 2.0).

Although, there is simply no substitute for hands on experience at making data-drive decisions and becoming fluent in the world of digital measurement.

Working at an agency and on hundreds of clients across industries helped me get to where I am, so that’s a path I can personally recommend. Although there’s no reason you can’t build your skills in-house too.

To learn more about the changing face of digital marketing, come to our two-day Shift London event in May.

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Google Analytics: a guide to confusing terms

Google Analytics is a hugely useful and in-depth tool for measuring and monitoring your website’s performance, as long as you can learn its language.

After setting up Google Analytics on your site for the first time, it can be hard work to navigate your way through all the different terms referring to parts of your site or the activities users carry out on it – especially when so many of them sound similar.

What’s the difference between a ‘session’ and a ‘pageview’? Are ‘users’ and ‘visitors’ the same thing? How does your site’s ‘bounce rate’ differ from its ‘exit rate’? Does ‘time on page’ really reflect what it says it does?

If you’ve wondered something like this at any point while staring down a mass of analytics for your site, worry not.

We’ve put together a handy guide to break down the meanings and uses of some key but confusing terms on Google Analytics, and how they differ from each other.

Quick Links

• Bounce Rate
  • Sticky content
• Clicks
  • Clickthrough Rate (CTR)
• Entrances
• Events
• Exit Page
• Exit Rate (% Exit)
• Hits
• Impressions
• Landing or Entrance Page
• Page Views
  • Unique Page Views
  • Pages/Session or Average Page Depth
• Sessions
  • Average Session Duration
• Time on Page
• Users, Visitors or Traffic?
  • New Visitor
  • Returning Visitor
  • Traffic Source
• Types of Traffic
  • Direct Traffic
  • Organic Search Traffic
    • Organic Search Keywords
  • Paid Search Traffic
  • Referral Traffic

Bounce Rate

The bounce rate of your site is the percentage of visitors who leave the site after only interacting with one page. This could be because they lost interest, were confused, or had already found the information they were looking for.

Individual pages have bounce rates as well as the site as a whole. A bounce rate for a page is based on all sessions that begin with that page and end without the user navigating to any other pages on the site.

A high bounce rate can be an indicator of problems, or it can indicate that for whatever reason, visitors aren’t finding anything on the site that entices them to stay longer, read more, or search for more content. A site that people spend a long time visiting and interacting with is often referred to as ‘sticky’.

For more, listen to Avinash Kaushik on the power of bounce rate, or “I came, I puked, I left”:

Not to be confused with: Exit Rate

Clicks

Clicks is a metric that appears on Google’s SEO Reports, which you can set up for your site to monitor your visibility in search results and how that translates into visitors to your site. As it says on the tin, the number of clicks on your SEO report records the number of times that people have clicked on a URL to your website in search results. This does not count clicks on paid AdWords search results, which are recorded separately in AdWords reports.

Clickthrough Rate, or CTR, is a number calculated by dividing the number of clicks to your site by the number of impressions (which records how many times it was seen) and multiplying by 100. This will tell you what proportion of users who see your site in search results actually click through to it.

Not to be confused with: Impressions or Hits

Entrances

Google Analytics records an entrance for each page that a user begins a new session on. So the number of entrances given for a specific page shows how many users began their session with that page.

Not to be confused with: Landing or Entrance Page

Events

An event on Google Analytics is a type of hit which tracks user interactions with content like downloads, mobile ad clicks, Flash elements and video plays.

Events on Google Analytics give insight into a range of user activities that are taking place across your site, and with a little bit of technical know-how, you can set up custom events to track all kinds of user behaviours that aren’t normally visible in Analytics.

Not to be confused with: Hits

Exit Page

The opposite of a landing page, an exit page on Google Analytics refers to the last page a user accesses before their session ends or they leave the site. The Exit Pages section of Google Analytics therefore allows you to see which pages people most frequently end their sessions on or leave the site after viewing.

Google Analytics has difficulty calculating the amount of time users spend on an exit page because there is no next page to help it judge when the user left that page. This issue impacts the accuracy of average time on page and average session duration figures.

Not to be confused with: Landing or Entrance Page or Exit Rate

Exit Rate (shown on Google Analytics as % Exit)

This figure shows how often users end their session or leave the site after viewing that particular page. The exit rate is calculated by dividing the number of ‘exits’ made from the page by the number of pageviews it has, to determine what proportion of visitors to that page leave it after visiting.

A page with a high exit rate may not necessarily have a high bounce rate, since users might be coming to that page from elsewhere in the site before exiting. However, a page with a low exit rate is likely to also have a low bounce rate, since users must be going on to other pages on the site before they leave.

Not to be confused with: Bounce Rate or Exit Page

Hits

In web terms, a hit is a request to a web server for a file like a webpage, image or JavaScript. In Google Analytics, hits are an overarching term for a variety of website interactions. Page views and events, for example, are both types of hit. A session is simply a collection of hits from one user, grouped together.

Google Analytics uses hits to determine when and how a user is interacting with a webpage. So if no hits are sent, the user is assumed to be inactive. The countdown to the end of a user’s session begins from their last hit. After thirty minutes with no new hits, the session automatically ends.

Not to be confused with: Clicks, Page Views or Events

Impressions

In Google’s SEO Reports, impressions records how many times a URL to your site was viewed by a user in search results. This does not count impressions by paid AdWords search results, which are recorded separately in AdWords reports.

By calculating clicks on those URLs as a percentage of impressions, Google Analytics can tell you the Click-Through Rate of your URLs that appear in search results. This appears in your SEO Report under CTR.

Not to be confused with: Page Views

Landing or Entrance Page

‘Landing Page’ and ‘Entrance Page’ are both used by Google to refer to the first page a user accesses (or ‘lands’ on) at the beginning of a session. The Landing Pages section of Google Analytics therefore allows you to view the pages through which users most often arrive on the site, and their statistics.

Not to be confused with: Exit Page or Entrances

Page Views

Page Views (also called screen views for mobile) are the total count of how many times any user lands on an individual page on your website. This includes repeatedly landing on the same page during one session, so if a user refreshes the page, this counts as an additional page view on your site.

‘Unique page views’ is a number that will tell you how many times a page was accessed at least once during a session. In other words, it doesn’t count multiple views of a page by the same user in the same session, instead treating them as a single view.

Pages per session, also called Average Page Depth, is the average number of pages viewed by each user during one session. On Google Analytics, this metric includes repeated views of a single page by the same user.

Not to be confused with: Hits or Impressions

Session(s)

A session is a measure of the amount of time a user spends actively engaging with your website. Session length is calculated from the moment a user arrives on your site until 30 minutes of inactivity have elapsed. Every new action that a user performs will reset the clock on when that session will ‘expire’.

The only exception to this is at midnight, at which point all sessions for that day are considered to have ended and a fresh session will begin, even if that user has been active throughout.

Average Session Duration calculates the average length of a user’s session by dividing the session duration by the number of sessions. However, there is a problem with this calculation: Google cannot calculate the time spent on an exit page because there is no next page for it to use as a marker. This can drastically throw off the accuracy of the average session duration, especially in the case of bounces where the session consists of a single page, and no session duration can be calculated at all.

Not to be confused with: Time on Page

Time on Page

If you look at the Google Analytics for individual pages on your site, you can see the average amount of time that a user spent on that page, as well as the amount of time that users spend, on average, on any one page of your site. This figure can be deceptive, however.

Google has no way of measuring the time a user spent on the last page of your website that they viewed, because it uses the next page they access to calculate how long they spent on the previous one. On the last page of a session, there is no next page and so the time on that page is recorded as 0.

Google does correct for this issue somewhat, calculating average time on page by dividing the time on page by the number of page views minus the number of exits from the site. The problem is, this still means the time on the exit page isn’t accounted for, so bear that in mind when looking at these figures.

Not to be confused with: Session Duration

Users, Visitors or Traffic?

These three terms are all ways of referring to the people who access your site. Google uses the words user and visitor interchangeably in different places, both to refer to an individual person who comes to your site. A new visitor is someone who comes to your site without having been there before, while a returning visitor is someone who has been to your site previously.

Traffic is an overall term to refer to the volume of users accessing your website. A traffic source is any place from which people are directed to your site, such as a search engine, social network or other website.

Types of traffic:

Direct traffic

Visitors to your site are classed as direct traffic when they access your site via a bookmark, or by entering its URL straight into their browser’s address bar. When viewing Traffic Sources on Google Analytics, the source for direct traffic is shown as ‘(direct)’.

Organic Search Traffic

Organic traffic is the name given to the amount of users who find your website ‘organically’ through search results, as opposed to via a paid ad, clicking a link on another site, or from a bookmark they already have saved. Organic search keywords can allow you to see which search terms are helping users to find your site, as well as the kind of things they are looking for when they access it.

Paid Search Traffic

Paid traffic is the amount of visitors to your site who came there via Google Adwords ads, paid search keywords and other online ad campaigns. With Paid Traffic on Google Analytics, you can track all traffic from paid sources in one place, analyse user behaviour and gauge the effectiveness of your campaigns.

Referral Traffic

A referral is a visitor to your site who is sent there, or referred, from a direct link on another site. Referral traffic is therefore the general term for the amount of people who are referred to your site from elsewhere on the web.

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How to fix discrepancies in your web analytics data

Google Analytics, like every web analytics tool, does not deliver accurate data.

There are many reasons behind this including:

• Visitors don’t allow JavaScript
• Visitors block cookies
• Pages missing code
• Location of the code on the page

There are certain actions though that can be exactly measured, as they are recorded in back end systems.

We know exactly how many transactions are placed, leads are generated, contact forms submitted, etc. For these actions, we can audit the accuracy of the web analytics and identify errors in the tracking.

This is critically important as these actions are nearly always macro conversions and, if they are not tracking correctly, we cannot evaluate the performance of marketing campaigns or the impact of website features.

The problem

These actions can never be recorded 100% accurately in any web analytics tool (you should not try and report your revenue to the tax office using web analytics data) but they should only be 2%-3% off reality.

If the difference is more than 5% (with a large enough sample size), you have an issue somewhere in your tracking. The code works, or no data would be collected at all, but it is not correctly submitting measurements to the web analytics tool in all cases.

Causes

To simplify the language within this blog post, I will be using transactions on an Magento ecommerce website compared to Google Analytics data as an example for the remainder of the post.

The first step is to check if there is a discrepancy.

Extract daily orders for 8 to 12 weeks for both Magento and Google Analytics and then compare performance at a daily level. As long as order volumes are high enough, the discrepancy should be fairly consistent for each day.

Ideally Magento should report transactions slightly higher than Google Analytics but no more than 5%. If the difference is more than that, you have an issue.

The key reasons for a difference in transactions recorded within Google Analytics (or any analytics tool) and Magento are:

1. Orders placed over the phone/offline are recorded in Magento but are not captured in Google Analytics
2. Orders placed on computers using internal IP addresses are recorded in Magento but not in the Google Analytics View (as exclusion filters applied)
3. There is a certain device/browser/browser version where the Google Analytics transaction tag does not fire
4. There is a payment method where the visitor doesn’t return to the Order Confirmation page, therefore never triggering the Google Analytics transaction tag
5. There are certain variable values that break the code e.g. a product name that contains “ or ;
6. The amount of the information included within the tag is too long (e.g. lots of product information is captured, exceeding the limit of 8,192 bytes
7. The visitor leaves the Order Confirmation page before the Google Analytics transaction tag can be fired

Identifying the cause

The challenge is to identify which one (or more) of these apply to your business. The first two reasons can be identified through an internal investigation into what data is being recorded in each of Magento and Google Analytics.

For the second, check into what filters are applied and/or create a new Google Analytics View with no filters applied to see if that changes the data.

The third reason requires some analysis within Google Analytics.

Check the conversion rate for each device and browser version. If it is 0% for a certain option (with a decent number of sessions), you may have identified the culprit/s. Check more into the data or even check through making a transaction on that device/browser to confirm the transaction code isn’t fired correctly.

For reasons four to six, extract a list of the transactions from Magento and Google Analytics for three non-sequential days during the previous period (make sure these days contain the typical discrepancy) including the transaction ID. Compare the two lists using the transaction IDs and identify the transactions which are not recorded within Google Analytics.

Review these transactions for patterns of payment methods, particular products or just very large transactions. The challenge is that some missing transactions were just not recorded while others should fit the pattern of one or more of the above reasons.

For the final reason, check the location of your Google Analytics code on the page. If it is lower in the page than immediately below the <body> tag, that could be the cause.

Solutions

Once the cause of the discrepancy has been identified, it should naturally suggest the solution. These solutions include:

• Ensuring you are comparing apples with apples e.g. transactions placed by external visitor on the website
• Adjusting the process for a payment method so that the visitor is returned to the Order Confirmation page
• Fixing the transaction code so that it works for all browsers and devices
• Removing or escaping all special characters within product variable names
• Ensuring that tags don’t exceed the 8,192 byte limit
• Changing the location on the Transaction code on the Order Confirmation page

Once you apply these fixes, the discrepancy should immediately reduce. Continue checking and making improvements until the discrepancy between your back end numbers and your web analytics numbers reduces to under 5%.

One final note, web analytics data can also be higher than that recorded in back end systems. This would be the case if duplications are recorded in GA but automatically excluded in back end systems (e.g. for transactions) or if data has been cancelled out of the backend systems e.g. cancelled orders, fake leads.

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How to track clicks to offline sales from a B2B lead generation website

Some products demand a very specific conversion strategy. If yours includes a process of generating leads through your website to nurture and follow up offline, then you may face an issue which has plagued marketers for years.

While it may make your old-school PPC account manager feel warm inside to see a healthy rate of conversion from form fills and phone calls, that often isn’t a good indicator of campaign success anymore.

The modern day digital marketer needs to understand which clicks are turning into sales and not just the ones that are generating interest.

So, where does the problem lie, and what can you do about it?

The problem

Let’s say you spend $100,000 each on two separate campaigns. Campaign A generates 1,000 online leads, whereas Campaign B generates only 500.

Using this information alone, you would probably choose to focus your resources on Campaign A as it seems to offer a better ROI. However, the problem lies in the fact that the lead-to-sale conversion rate is rarely consistent across different campaigns, keywords and channels.

If Campaign B converted its 500 leads at a rate of 50% and Campaign A only managed 10%, then it puts a dramatically different perspective on the success of both. The more granular you get with conversion analysis, the better you’ll understand these conversion rates and the more effectively you’ll be able to allocate your budgets.

When you’re spending $50 a click in some valuable and competitive markets, then it is a necessity rather than a bonus.

Failing to recognize and tackle this issue can mean you’re not aware of which of your leads are good or bad, and can cause a whole host of other issues including:

• Manual work to review and feedback on lead quality
• Not knowing which keywords are actually generating sales, so you can’t optimize AdWords/paid marketing accordingly
• Wasted ad spend on keywords that generate low-quality web leads

The solution

There are ways to tackle the problem, though. Digital marketers usually optimize their campaigns in one of two places:

1. Ad platforms such as AdWords or Doubleclick (or perhaps a third party management platform like Marin or Kenshoo)
2. Analytics platforms – such as Google Analytics, Adobe Analytics or IBM Analytics (formerly Omniture and Coremetrics)

To make this optimization more effective you need information about your final offline sales to be visible in those systems. This is now a straightforward process and can be achieved much easier than most people think.

The examples below are for AdWords and Google Analytics, but you may also need to explore other methods using your own specific setup and platform.

Injecting offline conversion and activity into Google Analytics

Using your analytics platform to hold information about offline activity and conversions, that started with an online journey, is the best solution to problem. This will give you a solution that works for all your online efforts and not just a specific ad platform.

For this to work, you need to make it possible for users to share an ID between their online sessions and your CRM database. This is then used to record what happens with the customer once you have their details.

There are two possible ways to do this, by using either the UserID method, which is the most effective, or the Client ID method.

Here’s how you can implement these changes:

UserID method

Google Analytics (GA) now has the ability to link sessions across devices and even activity that occurs offline (perhaps at the point of sale in a shop, or a face to face sales meeting).

It does this by making use of a feature called UserID tracking. This UserID is an ID that you set to uniquely identify each visitor to your website in your CRM. You probably already have this ID in your CRM.

In each session/hit that a user interacts with your website, you make a small customization to the tracking script to output this ID. This then enables GA to link this activity together whether it is on the same device, a different one or even offline. To implement this, take the following steps:

1. Set up a UserID view in Google Analytics (GA) – You need to create a new view that will have the sole purpose of presenting all sessions and activity that has a UserID associated with it.
2. Output that UserID at every opportunity – The most important time to do this is during the session that they originally make an enquiry in. Your technology needs to be integrated enough and capable of saving information submitted in a form in your CRM, getting the ID from that CRM record and then outputting it to the “Thank you” page of the form that the user has just submitted. Once this ID is output in the original, lead generating session you have the ability to join your offline activity with that session. More importantly, you will better understand the channels that drove it. Find out more information here: http://ift.tt/1oFMnVJ
3. Inject offline activity back into GA – Next, you need to be able to customize your business system so that it’s able to execute some very basic code when something you are interested in tracking occurs. This might be a sale when an enquiry turns into a ‘qualified enquiry’, when a sales visit occurs or any number of other checkpoints. You have to make use of what is called the Google Analytics measurement protocol to inject this data. Although this may sound complicated, it really couldn’t be much simpler. All the change does is allow your system to generate a simple URL (such as the one below) in a predefined format or protocol.

POST http://ift.tt/1bgZ9jH

v=1&tid=UA-XXXXX-X&cid=1234.9876&uid=123&t=pageview&dp=%2Fdummypv&z=ud7ckjr

The values of the parameters relate to what type of information you want to put into GA. More information and a reference to the measurement protocol can be found here:

http://ift.tt/1i01a61

http://ift.tt/10TJIWG

And that is it! One point to note is that to make UserID as effective as possible, it’s worth taking every opportunity to output the UserID to the web sessions of people when you know who they are. This could include:

• Storing this ID in a cookie so it is available in future sessions – important if your site does not require login
• Outputting this UserID whenever they log in
• Including this UserID in email marketing to set and store the UserID when they click a link
• Any other opportunity you get to inform the web browser that the user has an ID

ClientID method

As mentioned above, there are two possible ways to link your offline activity to online leads. If you do not have the ability to integrate your website and CRM fully to output the UserID on the ‘Thank you’ page after a form is submitted, then there is an alternative.

The ClientID is an internal ID that GA uses to identify an individual. The ‘Client’, in this sense, relates to the software client, most probably the web browser or app. Instead of pulling an ID from your CRM to output on your website, this method is slightly simpler in that you only need to capture the ClientID and ‘push’ it with the lead information they send.

GA provides an interface/function to capture this ClientID, which means you don’t have to go looking in cookies yourself – it is as follows:

ga(function(tracker) {

var clientId = tracker.get(‘clientId’);

PLACE CODE HERE TO UPDATE THE ‘VALUE’ OF THE HIDDEN FIELD WITH clientId.

});

You then simply find a way of populating a hidden field in your web forms with this value. You can then use this ClientID with the measurement protocol as described earlier.

Importing offline conversion into Google AdWords

Of course, if you implement the GA method above, then you have the option of importing GA goals into AdWords. However, if you prefer to import offline conversion data directly into AdWords, then there is now functionality to do so. The following steps should be followed if you wish to do this:

1. Enable auto-tagging – You need to enable auto tagging which will automatically put a parameter called ‘gclid’ onto each URL when someone clicks an ad. This parameter will contain a string value that uniquely identifies the click.
2. Capture the above-mentioned gclid parameter – When someone lands on the site, or the landing page contains the gclid parameter, then you need to program your site to capture this value and store it (probably in a cookie). This is a relatively simple task, especially if you use the script provided by Google shown here: http://ift.tt/1TkSPzk

It becomes even easier if you have Google Tag Manager installed, which makes this a two-minute job.

3. Push the gclid ID into your CRM when a lead is completed – When a form is submitted, you need to ensure that you take the gclid parameter value out of the cookie (mentioned in point two) and then place this in a hidden field. That way, it’s ready for your CRM to record this against the lead it records.
4. Push conversions back into AdWords – When one of the leads you accept, with a gclid against it, goes on to complete offline conversions (such as buying something), then you need to push this information back into AdWords. There are two ways of doing this, you can either:
   1. Upload a CSV or Excel file with the details of the conversion and the gclid it belongs to. This also contains other information like the conversion date. You can process a full batch of these at a time (perhaps every day or week). You can even automate this using AdWords scripts.
   2. Upload using the AdWords API – this is a more advanced method but is the most effective, and allows you to push conversions in instantly as they occur.

What about phone enquiries?

There are phone tracking systems on the market now that allow you to individually link online sessions to a phone call (for example Infinity or ResponseTap).

You can make a small customization to these systems to hold the information you send it from the web browser. This will enable the system to work with the above AdWords and GA (ClientID) methods. Although, there is a little more custom development required.

So, what does this all mean?

In summary, understanding the true value of the clicks you are buying or generating allows you to make a better-informed decision about their importance. This knowledge is what separates the market leaders, from the market followers.

In a competitive market, having confidence that a keyword is generating $2 per click instead of $1 can be the difference between setting bids that put you at the top of Google, or the bottom.

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How to use In-Page Analytics and how it can help boost conversions

Google Analytics is most certainly complex, so naturally there are a few options and features that go unnoticed.

So where do you begin if you’re trying to get more advanced and need a place to start? In-Page Analytics is probably one of the most under-used features that can also be the most impactful to a small business.

By looking at these specific analytics you can figure out which areas of your site are most important and which links visitors are clicking when they are actually on your site.

Once you can understand some of the details associated with user patterns, you can reformat your site and optimize in ways that ultimately will boost your conversions.

How to access your In-Page Analytics

The purpose of In-Page Analytics is to be able to tell what is working visually and what is not. In order to see your In-Page Analytics data you will need to sign into your Google Analytics account. Before you can do anything specific with the report, you will have to enter the URL for the page on which you want the report to launch. You enter that URL when you edit the settings for a Reporting view.

You can access this report two ways:

• Access—Way #1
• Sign in to your Analytics account.
• Navigate to your view.
• Select the Reporting tab.
• Select Behavior > In-Page Analytics.
• Access—Way #2
• Select Behavior > Site Content > All Pages.
• Drill into a page and select the In-Page tab.
• This opens the report for that page.

In both cases you access the report through the ‘behavior’ section. Once, you click on In-Page Analytics, your website’s home page will display the exact percentage of where users are clicking on your site. Below shows where you can find the In-Page Analytics report and what it looks like:

Once again, the job of the In-Page Analytics report is ultimately to infer the number of clicks on a page element (CTA, links, etc.) from the number of times that page appears as the referrer to subsequent pages.

In this way you can see which elements are leading to the more popular subsequent pages on your website. In many cases this is not just a preference of content, but something that stood out more than other elements on your website.

Customizing In-Page Analytics

According to Site Pro News, you can also customize in-page analytics for the needs of your site, which Site Pro News also touched on here. This can directly help to optimize your site, which in turn will help boost conversions.

Here are two ideas for how you can customize the report:

Importance of setting the date range

Just as with any report, you may customize your date range by clicking on the date panel located on the top right-hand side of your analytics dashboard and choosing your own date range.

This will allow you to understand exactly what was up on your site or any changes you have made, and when. Periods of time are incredibly important to consider with this analysis, so I recommend clicking the ‘Compare To’ button to see if you’re making improvements:

Keep in mind that the only way to say whether or not your numbers are ‘good’ or ‘bad’ is to compare them to what they were in previous months, and this is especially true with this report.

Every website is different, so you’re in a competition with yourself first and foremost before worrying about competition.

Using Segmentation

There are a lot ways to segment your data on the in-page analytics platform. This will allow you to look at how users arrive on your site (for example) and then the ways that they navigate it once they are there.

You can separate, as the screen shot indicates, by categories such as ‘made a purchase’, ‘referral traffic’, ‘direct traffic’, or ‘new users’. All of this can be used to optimize your site and figure out what focus you need to have to boost conversion rates.

To create a segment, click on All Users. This will take you to a screen where you can ‘Add a Segment’ (as shown below). You can then click to create a recommended segment or create a custom one. The screenshot below, for example, has segments for Bounced Sessions, Direct Traffic, and Converters. Just hit ‘Apply’ at the bottom when you’re finished.

Note: If you’re new to segmentation, segmenting your email lists is probably one of the easiest and most important places to start. Check out this article to learn more.

Making the Most of In-Page Analytics for Conversion Rates

Just as we discussed above in the section on data customization, there are a lot of different ways to make the most of your data to enhance your conversion rates. Segmenting data is one of the more successful ways to focus on who is finding your site and how these differences might effect interaction.

If you are interested, check this out this video on the visual context for your In-Page Analytics data from Google…

So now that you know how to read the data and what to look for, it’s important to understand how exactly to customize it. Below are some tips on customization that will help you make the most of your data for conversion rates:

• Make sure you segment or have a category for each of the streams/referral sites that people may be coming from—whether it be social media or other sites.
• For each channel, you want to construct a separate report (this includes direct traffic as well). This will give a clearer picture of the differences in where your audiences are coming from.
• Make adjustments as you see fit. For example, if you have a CTA that is either not being clicked, or people are leaving your site once they do, then you probably need to readjust and reconfigure the way this particular element is presented. There may also be differences for certain audiences that you want to account for, but remember to prioritize places where you are getting the most traffic from.
• Find out where maximum click happens. For example, if it happens on the top left side of the page, then put your conversion links there. Always check this when you run your analysis and make sure you adjust accordingly, as this can change over time.
• Make efforts to reduce whenever exit rate is high, especially when it is on most-linked or top pages on your site.
• Make it a goal to check back on a regular basis, as you do with your other analytics, so you are conscious of what needs to be adjusted over time

The Takeaway

It is difficult to understand why In-Page Analytics are as underused as they are when they provide such valuable insight. Definitely do not miss out on the opportunity to look at this as a tool of change and boosting conversion rates. The ability to segment your visitors and see how they interact with your site is very valuable; so start now!

Do you have experience with Google’s In-Page Analytics? Let us know in the comments section below, we would love to hear from you.

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