This is a guest post by Sheryl Davis. Sheryl is a digital marketer at Glew, an ecommerce analytics software provider, where she focuses on helping online stores understand and act on their data.

Are you frustrated with your conversion rate even when traffic to your storefront is up? Are you asking yourself why more visitors aren’t buying your products? You aren’t alone. Many stores struggle with converting their traffic to buying customers.

Let’s look at five specific places in Google Analytics that hold clues to help you solve this problem.

Clue #1:  Bounce Rate

Click on Google Analytics > Behavior > Site Content > All Pages. 

What is Bounce Rate?

Bounce Rate is the percentage of sessions during which a browser left a website from the entrance page without going to a second page. Having a high Bounce Rate can be an indicator of pages that need additional work. Lowering your Bounce Rate increases your chance of successful conversions.

Refocus your content

Look at pages that have a high Bounce Rate as well as a low Average Time on Site. Why are visitors leaving quickly and often? Are they looking for something else? Is there not enough content on the page to get them to stick around? Product pages can often be the worst offenders of a high Bounce Rate. Add a link to a blog post that features the product, show a video of someone using the product, curate a collection of customer photos, or incorporate links to product manuals or reviews.

Encourage users to keep clicking

Browsers are lazy. Don’t assume they will do the work to look around for places to keep reading. Without cluttering up your design, drop as many avenues as you can to keep them on your site. A great way to keep browsers clicking is through the use of a sidebar. Does your company have a unique story to tell? Include a link to a page about your company’s story. Are new collections debuting soon? Link to a preview of new designs to come! And don’t forget about content that was posted months or years ago. Since blog posts can keep a long shelf life in organic search, there should always be a quick way to get to recent content.

Clue #2:  New vs Returning Visitors

Click on Audience > Behavior > New vs Returning > Click on New Visitor. Filter further by adding Secondary Dimension > Source / Medium. 

Why is this important? 

This table will show a breakdown of visitor type by traffic sources.  Study channels that are driving new traffic (good) but are failing to bring in traffic that is converting (bad). Remember new traffic is useless if it isn’t driving conversions.

Paid Channels

Ensure your advertisements are bringing in more revenue than is being spent on ad dollars. This feels obvious, right? It’s surprisingly easy to overlook the revenue these channels contributed and instead focus on brand awareness metrics such as followers, visits or shares.

Double check that sales from paid channels like Google Adwords, Bing Ads, AdRoll or Facebook Ads are adding to your bottom line. Running ads should increase new visitors to your site, but without sales they are draining money away. Cut out advertising from costly channels with a poor return on ad spend and instead focus on organic methods.

Organic Channels

Organic traffic is good – simple as that. Organic traffic is any traffic that comes through a non-paid channel. The most common types of organic traffic are organic searches, referral traffic or traffic derived from your social accounts.

Since this traffic is free, having more of it isn’t an issue. Instead use this table to find areas of opportunity. If visitors are finding you for the first time from an organic method, add a Call to Action on the pages they are landing on. Referral traffic that is brining in new visitors can be a great place to look for future partnership opportunities. Bloggers are constantly looking for products to promote or sponsor, so use this table to understand what is working.

Clue #3: Search Queries 

Log in to Google Analytics and go to > Acquisition > AdWords > Search Queries.  

Google AdWords is a computer program. It can’t always distinguish nuances in language or differentiate between words that have multiple meanings. An easy and actionable way to lower junk traffic is to use negative keywords in Google AdWords. Negative keywords exclude unwanted traffic from people who are searching for an item unrelated to your offering.

Here is an example: Say you own a store that sells belts for men’s and women’s fashion. Negative keywords would eliminate searches for conveyer belts, seat belts, black belts, the Asteroid belt or even Belt, Montana.

Google AdWords is smart, but it won’t be accurate 100% of the time. Go through the search queries that brought traffic to your site. Take out any keywords that drove irrelevant traffic and enter those as negative keywords in Google Analytics. See a guide on how to do that here.

Clue #4: Exit Pages 

Click on Acquisition > Behavior > Exit Pages.

An Exit Page is the ugly stepsister to a Landing Page. It’s natural to spend more time focused on what is working rather than evaluate what isn’t working. But Exit Pages illuminate exactly where and when website visitors move on from your site empty handed.

Sort this table to see which pages have the largest amount of exiting traffic. (Most likely your homepage will be the first page, this is normal.) Similar to strategies on lowering Bounce Rate, work to build avenues for capturing visitors and keeping them engaged.

• Implement a popup with a discount code that will appear when a user starts to exit
• Provide links to webpages about your story and company
• Drive users to blog posts that feature hot products
• Show commonly purchased together items on the bottom of every product page
• Include a sidebar that offers links to upcoming releases
• Create stronger Call to Actions that heighten sense of urgency
• Ask for browsers to join your mailing list so you can sell to them at a later time
• Add a chat feature that will come up within your site to answer questions
• Use retargeting advertisements to later target browsers with the exact product they were viewing

All of these strategies work to hook browsers into sticking around and entice them with offers to convert.

Clue #5: Mobile Browsing 

Click on Audience > Mobile > Overview. 

According to research done by Custora, during the 2015 holiday season, smartphones and tablets drove 30.4% of online sales.

Can you afford to lose out on 30% of shoppers? Without a responsive storefront mobile browsers will leave en masse.

Tips for Not Losing Mobile Shoppers

Troubleshoot your entire checkout process by making sure your storefront, shopping cart and payment gateways have a responsive design. This can be as simple as pulling up your iPhone, or simply dragging your browser to be as skinny as possible and going through the motions of checking out.

Make sure buttons and links are large enough that a user can click on them on a tiny screen without tapping on a different link.

Eliminate any “hover” options on your site. Since tablet and mobile phones don’t use hover technology, this simple fix could have a drastic increase in your bottom line.

Reduce image file sizes as much as possible. Google provides a powerful free tool that shows a breakdown of what is slowing down your site speed on both mobile and desktop displays.

Final Note

Google Analytics can often feel overwhelming and daunting. The most important thing is to go in with a goal in mind and look for actionable ways to use the data provided. Stay focused on your goal of increasing conversions and use these five clues to start solving problems and continue reeling in sales!

Google AMP Project is a very hot topic in these days.

Today I’m going to show you how to implement Google Analytics (or “AMP Analytics”) in your website, and how to install it through Google Tag Manager.

Before we get started, here is a list of topics we will be discussing:

1. What is AMP

2. Setting up AMP on a WordPress site

3. Google Analytics for AMP websites

4. Implementing AMP Analytics through Google Tag Manager

Part #1: What is AMP?

A lot of content already published about this subject, and I’m not going to be reinventing the wheel here, but a short overview is in order to make sure everyone is on the same page:

AMP is an open-source project, spearheaded by Google. The initial goal of AMP was to shorten the load time of news sites viewed on mobile devices.

However, the project has grown and gained momentum. Consider, for example, that Google recently added AMP to its search results pages, which comes together nicely with the new prioritization of mobile sites, as announced by Google in April of 2015 (note that priority is not yet being given to AMP pages, at least not officially, but this will certainly happen soon).

The reason that Google initiated this project to begin with is due the growing trend of site traffic seeping from the desktop to mobile devices, however most site owners have not yet adapted their site to be properly mobile-friendly (and probably will never do that properly…).

So yes, “mobile friendly”, “adapted” and “responsive” websites are terms we are already tiring of hearing, but they don’t actually solve the most significant factor on mobile sites – i.e., loading times.

Speed critically affects user experience. For example, KISSmetrics’ study found that 40% of a site’s visitors will leave if the loading time is greater than 3 seconds. If that doesn’t scare you straight, consider another research finding that every second of delay when you website loaded, reduces your conversion rate by 3.5%.

It’s a lot!

In a funny Google video, they explained this issue in a rather amusing way by showing that the most problematic contributors to lag are the numerous advertising networks and analytics systems installed on the page.

So okay, AdBlocker can solve the problem on the user’s end – but then we’re looking at a serious loss of ROI for the big publishers. This appears to be one of the reasons that Google got involved, to find a solution that will address everyone’s interest.

There are Three Parts in an AMP Website

AMP is made up of three central elements:

1. AMP HTML – a list of custom tags and a whole lot of restrictions (and a few additions that enable rich content). So, for example, replacing the <img> tag with the <amp-img> tag enables the page to render the images only as the user sees it on his screen – instead of loading together with all the page’s elements, which would harm the user experience.

2. AMP JS – only specific tags can be used in AMP pages, one of the main goals of AMP JS being to turn anything that contains Javascript into an asynchronous element. Loading Javascript in parallel to the page’s other elements – instead of upfront, avoids additional load time, which again, would harm the user experience.

3. Google AMP Cache – Google’s proxy server saves the pages, and optimizes their display to the user, which of course includes faster loading times.

So, after our quick introduction, let’s go to the technical part:

Part #2: Setting up AMP on a WordPress Site

First you need to install this AMP Plugin by Automattic with the following link: https://wordpress.org/plugins/amp

[side note]

Since AMP creates a leaner version of your internet site, it is likely that you won’t like some of the design changes, and you may wish to play a little with the CSS. In order to do so, use a custom action addition to WordPress, as explained here.

[/end side note]

That’s pretty much it. From now on, the plugin will create an AMP version for every post or page you have on your site. In order to see it, simply add /amp/ after the post’s original URL (and if that doesn’t work, try additing /?amp=1).

Doesn’t this cause redundant content?

No, because the plugin adds a canonical tag to the AMP pages that leads to the original content.

How does Google know to index the AMP pages?

The plugin adds a special tag with rel=”amphtml” attribute, which leads to the AMP version of your page. So, when Google’s crawler indexes the original page, it will see that it also has an AMP version.

This is how this tag works: <link rel=”amphtml” href=”https://www.example.com/url/amp”>

Part #3: Google Analytics in AMP Sites

Before we get to talk about Tag Manager, let’s consider why do we need a different Google Analytics for our AMP site? Why can’t we just add them to our regular property?

That’s an excellent question, and the answer is simple:

The whole idea of AMP is to speed up mobile pages, but because Javascript can often significantly slow down its rendering time (particularly if it is loaded synchronously), the AMP technology doesn’t allow you to simply embed JS in your page. Instead, it requires you to use a special tag that has been pre-tested and approved by the AMP team.

The AMP team has created tags for the a number of leading analytics systems. You simply add in the desired vendor under the “type” attribute (which, as we already said, have been pre-tested and approved):

<amp-analytics type="XYZ"> ... </amp-analytics>

Amongst the leading systems already approved by AMP you can find Adobe, Segments, Chartbeat, Yandex and of course Google Analytics.

(Despite all of the above, you can still embed any JS through an iframe, but because we need the Google Analytics code to sit directly within the page, and not be loaded via an external iframe, this isn’t a solution).

Should I split them up into two properties, or measure it all under one property?

This is a good question, and it depends on the structure of your site. Google recommends opening a separate property.

As these are fundamentally two different kinds of sites, I would recommend including your AMP pages under the regular property, as well as setting up an additional property specifically for AMP, but since AMP uses a different format for tracking the clientId – you must read Simo Ahava‘s post first.

We need to suppose that the user will also be viewing pages that aren’t AMP alongside the AMP pages – so that if you track them across these different pages with separate properties, you may get a cutoff session and lose a lot of information about your visitor.

Part #4: Installing AMP Analytics using Google Tag Manager

Here comes the interesting part.

First of all, we need to open a separate container for our AMP website.

Yes, that’s right – you can’t just use your regular container. As I explained above, AMP was created to speed your site up, so you can’t use the regular container since it uses a non-adjusted JavaScript.

Besides which, AMP’s HTML is also customized, so you also can’t use the Triggers available in the standard container. So, we’ll open a new container, select AMP, and get the code to embed in our site:

Before we move on, make sure that you are using a child-theme, as we are going to change the template’s function.php file. Otherwise, if and when you decide to upgrade the template, this file will be replaced and you will find yourself without any tracking at all…

Another possibility is to do this using a plugin (like this one), but because the combination AMP <> Google Tag Manager is fresh off the press, there is not yet any plugin that enables you to do this without getting your hands a little dirty with code (at the time of this writing).

In any case, I always like to have things hard coded, as this allows me to control what’s going on, and because I believe that the more plugins you have, the heavier and lower is your website.

After all, AMP was designed to streamline your site’s rendering, and therefore, we don’t want to go about slowing it down with a lot of redundant plugins…

So, after you’ve created your child template, take the first part of the code and embed it as follows in your function.php file:

After that, take the second part of the code and embed it as follows:

Please note! If you’re not highly familiar with code, it is better to give the embedding instructions to an experienced developer. While this is not a complicated setup, the smallest mistake can cause your site to fall.

Please note #2: Don’t forget to change the number in GTM-XXXXXX according to your container id.

And… that’s it! Tag Manager is now embedded in your site. Now let’s see how to configure it.

Tag Manager for AMP website includes some really interesting triggers and variables that don’t come built-in with the regular Tag Manager, but before we discuss them, let’s create our first tag – Google Analytics.

And that’s it. There aren’t any special tricks here, and it works here exactly as we’ve done it up until now with the regular Tag Manager

Let’s move on to the more interesting topics:

Variables in Tag Manager for AMP

As you surely already know, the Tag Manager’s variables are actually “functions” that return certain values.

The Page URL variable returns the URL of the page, Data Layer Variable returns values from the data layer, and so on.

As in the regular Tag Manager, we can find built-in variables such as Page URL, Page Hostname, Event, Click Classes, Click ID, Click URL, Form Classes, Form ID, etc. (click here for the full list).

As well, we can also create additional variables manually:

 

In Google Tag Manager for AMP sites, however, we can find interesting and even downright cool values, such as user’s time zone, screen width/height, number of pixels the user scrolled, Total Engaged Time (the number of seconds the user was active on the page), page’s loading time and more (link to the full list).

All of these variables are available for use automatically, and all that’s left to do is to put them into tags, as we will see shortly.

Triggers in Tag Manager For AMP

Google Tag Manager for websites gives us triggers that can track page views, clicks on a certain element, sending a form and custom events that we can send to the data layer (there are of course others, but these are the main ones).

In the AMP container, we will find slightly different triggers, and it is interesting to see that Google also included triggers for scrolling and page visibility:

Sending an Event with Tag Manager For AMP

We saw the Page View trigger in action with the Analytics tag. Let’s demonstrate tracking the user’s scrolling actions, and send this event to Google Analytics when the user reaches 25%, 50% and 100% of the page.

All you need to do is to create a new tag called Universal Analytics, enter the number of the property (UA-XXXXXXX-Y format, or by using the Constant variable that we created earlier which contains this number), and enter the desired values under Category/Action/Label/Value.

In my case, I entered a constant value “Scroll” under Category, and under Action I put in a variable called {{Scroll Top}}, which returns the number of pixels the user has scrolled down from the top of the page. Under Label, I put in {{Scroll Height}} that will return the height of the page in pixels (both are built-in variables):

After this, I’ll create the trigger that is supposed to send this event, and under Vertical percentages I will enter the percentage points at which I wish to send the event. It is possible to enter a list of more than one area, by using commas:

Usually, I debug my events using Google Analytics Debugger, but it (as yet) does not support events that are sent by AMP pages.

As a bit of a shortcut, I will simply use the Network section in Chrome, and there I will be able to see all of the requests that the browser sends to the Google Analytics servers.

Of course, it is also possible to see the events sent to Analytics via the real-time report, but I just think it’s redundant to keep switching between the windows…

Tracking Clicks in AMP Pages Using Google Tag Manager

Tracking scrolling actions is nice, but let’s see how I track users that have left my AMP pages after clicking on Leave a Comment. Supposedly, they have left the site, but I want to know whether they have actually left my site, or just gone to my regular mobile site, which is being measured under a different property than that of the AMP property, which starts another session.

This is also exceedingly simple. All I need to do is to create a new Event tag for Universal Analytics, but this time I will use a different built-in variable, called {{Total Engaged Time}}. This will give me the number of seconds that the user was active on the page, giving me an indication of how much time it took the user to read the article and then leave a comment.

Afterwards, I will be able to compare this to other actions made by other visitors, and extract my insights about the ideal amount of time the user should be on my page in order to leave a comment.

The trigger for this tag should be Click event, then CSS Selector and then I will add “.amp-wp-comments-link a”.

Please note that in this case, we are talking about an a element which is inside a div element (which holds the class), and therefore I entered both elements, dividing between them using a comma. You can never know in advance which element the tag manager will decide to identify as the clicked element, and so it is always worthwhile to put in both the main element as well as any sub elements – just to be on the safe side.

Important: As the AMP completely changes the structure of your site, note that the selectors that we will want to use are completely different from the selectors that you are familiar with from your regular site.

Let’s debug this – we’ll click on the button and see whether the event was sent:

Indeed it has, it has been sent, but with a small bug. You may have noticed what appears under Event Label is the main domain, without the path, despite I used {{Page URL}} variable. I am working on this with Google to figure out why this happens, and will update this post once I have an answer.

Conclusion

Contrary to what you (might have) thought at the beginning, setting up Google Analytics via Tag Manager in AMP sites (and using Tag Manager in AMP sites generally) is much more simple than Tag Manager for regular web sites.

In light of the simplicity with which we can enable WordPress sites to support AMP, and in light of the fact that Google is pushing this so hard – it is very likely to become a standard in the near future. I think that every website manager and owner should make this change, and the quicker – the better.

And let’s not forget the improvement to user experience. This was the main reason that Google got into AMP, so no matter how you look at it, I believe it’s very worth your while to start planning this changeover today, and of course, to set up your tracking properly.

Google Analytics is a valuable tool that any marketer can use to optimize their content, website and overall campaigns, but there are still some pitfalls to the greatest free analytics tool on the web.

There are two main ways your GA data can actually mislead you:

(1) the metrics themselves have flaws and

(2) the way you think about the metric is flawed.

Here are 7 common metrics that you’re probably doing wrong.

Site Speed

Site speed is an important metric for optimizing user experience, however most marketers don’t have an accurate idea about their site’s speed because of the way it’s measured.

By default, GA measures site speed by sampling the loading time for 1% of your visitors. That’s a really small sample size, which increases the chances of outliers giving you inaccurate data. Luckily, you can fix this.

You can add a code in GA to increase your sample size to 100%. In the “Admin” section of your property, click “Tracking Info” and then “Tracking Code.” You’ll find a code like this:

Change the script to this:

ga(‘create’, ‘[YOUR GA ID]‘,{‘siteSpeedSampleRate’: 100});

Save your changes and you’re good to go!

Some metrics like site speed are designed with very high-traffic sites in mind. To avoid GA sampling too few of your visitors, it’s important to adjust these metrics to suit your unique needs.

To avoid GA sampling too few visitors, adjust metrics like site speed to suit your needs.
Click To Tweet

Bounce Rate

Most marketers think a high bounce rate is always a negative thing — it means that someone came to your site, didn’t like what they saw, and left. But that’s not always or even often the case.

Have you ever read an interesting blog post, got something out of it, and then left the page? I do it about ten times a day. There’s nothing wrong with that kind of website interaction for the marketer, but GA tags it as a bounce.

That person who read your blog post then left could be heading over to follow you on social media, or return to become a longtime customer later on. While very high bounce rates overall is a sign of something negative, there is a certain amount of it that is acceptable.

So instead of stressing over the bounce rate of every page on your site, consider the purpose of the content, and how you might expect your audience to react to it. Sometimes, there’s nothing wrong with reading and then moving on.

Exit Rate

Like bounce rate, exit rate is another metric that marketers tend to think about only in the negative, when that’s not always the case. For example, a page with content that’s designed to convert, and does so effectively, would have a high exit rate. A page with a high SERP rank for long tail keywords would also have a higher exit rate than others. That doesn’t mean it wasn’t valuable.

That’s why it’s important to consider your intent and the search position of the page when deciding if a high exit rate is good or bad.

Conversion Rate by Channel

GA calculates conversion rate by acquisition channel based on the last non-direct click. That’s the best they can do to determine what influenced the conversion. But sometimes, users return to the site as direct traffic, which isn’t taken into consideration. Because of this, the metric often underestimates the actual conversion rate by different channels.

Considering multi-channel funnels and attribution modeling reports in addition to conversion rate by channel will give you a much clearer picture.

You can find the model explorer tool under Conversions>Attribution in the menu:

This sample attribution model from Optimize Smart shows the channels for organic search.

Average Time on Page

Many marketers take average time on page to mean how much time visitors are actively consuming content. But GA’s measurement gives the metric a completely different meaning.

Average time on page measures how long your web page is open in the user’s browser. However GA can’t tell if the visitor has multiple tabs open, and is perusing a site in one tab while yours is open in another.

After 30 minutes of not looking at your page, the analytics will “time out.” But still, looking through a few pages of your site for a minute and then leaving the tab open while surfing elsewhere is not a very accurate measurement of user behavior. On top of that, GA is unable to include how much time someone spent on the last page they visited, because another pageview doesn’t follow.

At this point, there’s not much you can do to improve the accuracy of this metric, so just keep in mind that it will almost always be an overestimation of actual behavior.

New and Returning Visitors

New and returning visitors can also be a very misleading metric. That’s because GA tracks returning users with cookies, so any return visitor who deleted their browser history would be considered a new visitor. Also people accessing the same website from different devices (laptop, mobile, tablet) and would be counted as a new visitor each time.

Many consider a low number of returning visitors to be bad for retention. That is valid, but it’s important to remember that a large number of those new visitors are probably not new at all. Also, it’s possible that your website is so well-targeted that users buy your product or service on the first visit, never to return. That’s not a bad thing either.

Keep in mind that there’s a lot of unavoidable noise in your new and returning visitors metric. It’s still valuable to pay attention to, especially if it changes drastically, but don’t let it be the only driver for major adjustments in your content strategy.

Keep in mind that there’s a lot of unavoidable noise in your new and returning visitors metric.
Click To Tweet

Referral Traffic

Most marketers think that measuring referral traffic will tell them how many backlinks there are for their website, but this metric has a lot more noise than that. Clicks that come from social media or from links in your email marketing campaign can all be marked as referral traffic by GA. Even clicks from one page of your website to another can. But there is something you can do about it.

Social media: Use a link shortener tool like bit.ly to add a tracking code to your links so you know where they came from.

Then under GA Admin, click “Social Settings” and add the URLs to your “Social Sources.” Then GA will know it’s not referral traffic.

Email marketing: Use GA’s URL Builder to create campaign tracking codes for links to your site that appear in emails. Then you can track which clicks are coming from emails.

Your website: Make sure that all the cross-linking on your website references the relative page (/page), not the full URL (www.site.com/page). The full address will be counted as referral traffic in GA, but the relative page will not.

Make what efforts you can to reduce the noise from non-referral traffic, but understand that you’ll never be able to completely clean up the statistic. At best, your referral traffic numbers will only be a vague proxy of  the growth of your citations.

The Takeaway

GA is a valuable marketing tool, but it’s important to not take the data at face value. Here are some key points to remember about your metrics:

• High bounce and exit rates aren’t always a bad thing.

• Site speed and referral traffic have some limitations that you can fix.

• Conversion rate by channel, average time on page, and new and returning visitors have some limitations that you can’t fix, yet.

The best thing you can do is consider the big picture with each metric, remember its limitations, and focus on how the data actually translates to user behavior. The only way to really know if the data reflects something good or bad is to consider your overall goals for the website, as well as the goals of specific pages within it.

GA is a valuable marketing tool, but it’s important to not take the data at face value.
Click To Tweet

 Courtney Danyel is a content marketing writer who provides unique and valuable content per audiences, based on the latest  scientific and  industry research. Visit her website to learn more about her work.

Oftentimes the hardest part of testing is deciding what needs optimizing and where to get started. As a matter of a fact, 63% of marketers optimize websites based on intuition (MarketingSherpa). There are many ways and techniques to locating the leaks in a funnel, finding the pitfalls and then testing them. Fortunately we have a few experts who are happy to share their insights and AB testing tips for deciding what to test, and where to start.

To get us started, Jeffrey Eisenberg dives into a 3 step process which will help you locate your customer’s pain points and prioritizes tests according to impact and resources.

 Jeffrey Eisenberg

The CEO of BuyerLegends co-authored “Waiting For Your Cat to Bark?” and “Call To Action” both Wall Street Journal and New York Times bestselling books. He has trained and advised companies like HP, Google and NBC Universal to implement digital marketing strategies emphasizing optimization of revenue conversion rates for engagements, leads, subscriptions, and sales.

“We have a 3-step process we use as part of our Buyer Legends process.

1. Pre-mortem
2. Eisenberg’s Hierarchy of Optimization
3. Scoring Priorities

Of course, you cannot start the 3-step process without first creating actionable personas based on qualitative and quantitative data. Buyer Legends employ storytelling to optimize customer experiences.

Why do we focus on customer experience? We wrote in 2001 that conversion rates are a measure of your ability to persuade visitors to take the action you want them to take. They’re a reflection of your effectiveness at satisfying customers. For you to achieve your goals, visitors must first achieve theirs.

“For you to achieve your goals, visitors must first achieve theirs.”

Pre-mortem

The reality is that most companies lose more sales every day than they make. If you are converting less than 15% you need to evaluate what is broken in your customer experience.

Get to the bottom of what is going wrong, and plan to get it right. That is why, hands down, the pre-mortem step is the most impactful step of our Buyer Legends process. In fact, rarely does this exercise fail to produce at least one a-ha moment for our clients.  When you imagine the sale is already dead it frees up all the mental energy that you used to try and get the sale and points it at all the potential pitfalls and problems in your experience.

Eisenberg’s Hierarchy of Optimization

After you perform your pre-mortem you will likely end up with a long list of potential proof of Murphy’s law, but not everything on your list is equal.  Some thing are worth your effort some are not.  In my work with clients we often use Eisenberg’s Hierarchy of Optimization to separate the more pressing issues from the tinier ones.

First sort the list of problems into the follow categories:

• Functional. Does this product/service do what the prospect needs? How easy is it for a prospect to determine this?
• Accessible. Can she access it? What are the barriers to her ability to realize the need? Is it affordable, reasonable, and findable?
• Usable. Is it user-friendly? Are there obstacles?
• Intuitive. Does the sales process/Web site feel intuitive and natural based on her buying preferences? Is she forced to endure unnatural buying modalities to realize her need?
• Persuasive. Does she want it? Does she truly understand if it fills her need or solves her problem? Is her expectation reasonable? Will she be delighted?

Once they are sorted simply work your way up the pyramid.  Again, remember not every problem is in search of a solution, and you should focus on the problems that are likely to impact the most customers, and problems that you can actually fix. Be practical, don’t get caught up in the problems you can’t fix.

Scoring Priorities

Let’s consider another simple system to enable your organization to prioritize more effectively when planning tests. The system is based on prioritizing all your planned efforts by three factors with  a score from 1 to 5, with 5 being the best and 1 being the worse:

1. Time – How long will it take to execute a project (a change, a test, or full scale roll-out) until its completion? This includes staff hours/days to execute and the number of calendar days until the project’s impact would be recognized. A score of 5 would be given to a project that takes the minimal amount of time to execute and to realize the impact.
2. Impact – The amount of revenue potential (or reduced costs) from the execution of your project. Will the project impact all of your customers or only certain segments? Will it increase conversion rates by 1 percent or by 20 percent? A score of 5 is for projects that have the greatest lift or cost reduction potential.
3. Resources – The associated costs (people, tools, space, etc.) needed to execute a project. Keep in mind: No matter how good a project is, it will not succeed if you do not have resources to execute an initiative. A score of 5 is given when resources needed are few and are available for the project.

Next, take each factor and multiply them (don’t add them because these factors are orthogonal) for each project. The best possible score is 125 (5x5x5). Tackle and complete the highest-ranking projects first. Meet weekly with a cross-functional group to evaluate the status of each project. Be prepared to re-prioritize regularly; once a month or at least once a quarter.”

Tiffany daSilva dives deeper into buyer personalities and how she uses them to find the important leaks in the funnel and address them:

Tiffany daSilva

is a full stack marketer who has spent the last 10 years working on over 350 websites. Her past includes Geosign, Achievers, & Shopify and is currently the Director of Strategy at Powered by Search. Tiffany was named one of the Techwomen Canada of 2012 and can be seen speaking about marketing at events such as Unbounce’s CTA Conference, PPC Hero London, and 500Startups growth conference.

“I like to first look at data to understand what’s happening behind the scenes, the first metrics I look at are:

1. Time on site
2. Frequency
3. Mobile devices
4. and the usual paths users follow.

From there I go to user testing where I try to find people with different buyer personalities:

• Competitive: Logical and Fast Thinkers who tend to move through the site quickly because they know what they want.
• Methodical: Logical and Slow Thinkers who tend to read all the fine print (even privacy policies) to ensure that they know all the details before making a choice.
• Humanistic: Emotional & Slow Thinkers who take the time to read reviews, testimonials and ask their friends. They want to know what others think about the product before they make their decision.
• Spontaneous: Emotional & Fast Thinkers, they think with their gut but also love to play with things so finding things that might “distract” them in the right direction like check marks, lists, tours of the site, and quizzes will help them convert easier.

These personalities help me see how they move around the site, what areas they focus on more and what they think is missing from the site.

When it’s time to start my test I make sure that I have a hypothesis. Knowing what you’re going to test is very different than hypothesizing what your outcome is. By creating your hypothesis you’re essentially saying,

“I believe version X will beat version Y by __%.”

A few things happen when you do this:

1. You learn what works and what doesn’t because you’re invested in the outcome.
2. You’ve created your requirements. If you decide that version X will beat version y by 15% and it only beats it by 2%, than it’s not enough of a difference and you can go back and redo the test. Deciding what your goals are before hand will keep you honest, and make your tests bigger and better over time.
3. By setting out what you want your test to look like, you can ensure that your testing tool or analytics is set up in such a way that you will be able to measure the test. For example: If you say that version X will beat version Y’s conversion rate by 15%. You can run through your testing software, Adwords account or Analytics to ensure that this information is readily available to you.

Joanna Wiebe

is a conversion copywriter and the co-creator of Copy Hackers and Airstory, she is also one of my favorite writers and I strongly recommend you take her copy writing course.

“I work with a lot of tech businesses, and they tend to follow Dave McClure’s pirate metrics (AARRR) for growth:

1. Acquisition (sign-up)
2. Activation (use product)
3. Retention (keep using product)
4. Referral (tell others to use)
5. Revenue (pay for it)

We start by identifying the metric that is most off-target or most in need of optimization. Perhaps we see in our reporting that Acquisition, Activation and Retention are on track against goals right now but Referral and Revenue are flat or trending down. We work with the business to identify which of the two – Referral or Revenue – make the most sense to focus on optimizing, based largely on their business strategy and goals.

Let’s say they select Referral. Okay, now we need to find out what might be broken, not built, poorly executed, etc that’s potentially suppressing referrals. So we:

• Identify and document the tactics in play to generate referrals
• Analyze those tactics to find lower-hanging fruit; this is where analytics for web, email and the app come in especially handy
• Brainstorm overlooked referral opportunities (e.g., new and proven ways other businesses are getting referrals)
• Interview existing users to learn what’s keeping them from referring

Out of this exercise, we get not just split-testing ideas and food for hypotheses but also other growth hacks to boost referrals – like contests to run, businesses to partner with, content to create and repurpose, and apps and widgets to build.

To prioritize the lower-hanging fruit, we create a roadmap divided by channel: test these things in this order for user emails, test these things in this order for in-app prompts, test these things in this order in remarketing ads. Importantly, the roadmap has checkpoints at the end of each experiment so we can learn and apply what we learn to hypotheses for the next test on the map.

Peep Laja

is the founder of ConversionXL, and is one of the leading conversion optimization experts in the world. He helps companies grow via his conversion optimization agency, courses and coaching program. Take his free CRO course here.

“Figuring out what to AB test is the most difficult part of CRO – it’s what separates the pros from wannabes. If the site is terrible, it’s not very hard to come up with fixes, but if it’s decent or already well optimized, you have to have a data-driven process. I use ResearchXL framework to gather 6 types of data input to identify the problems the website has:

1. Technical analysis
2. Heuristic analysis
3. Digital analytics
4. Qualitative surveys
5. User testing
6. Mouse tracking

Where is it leaking money the most? What is the problem? What’s the discrepancy between what users want and how the website is? Once you know what the problems are, and are able to prioritize the issues (from major issues that affect a large number of users to minor usability issues), coming up with test hypotheses to address them becomes so much easier.

Next step: I figure out how many variations I can test against the control (depends on the transaction volume), and come up with as many different treatment alternatives as I can. Depending on the scope of changes, I might do a wireframe of the treatment, or just add annotations onto the screenshot of the Control – and then send it off to my front-end developer. If the changes are more radical, we might need a designer to be involved before coding up the test. One thing is for sure – speed of implementation (getting the test ready to go) is super important. We can not waste a day.

As Peep points out, the most difficult part of CRO is figuring out what to test. Which is why a huge part of our work at Conversioner is spent on understanding the data, the customer’s emotional needs and finding the point in which we can have the most impact.

Talia Wolf

As Founder and CEO of Conversioner, I help businesses build and execute their conversion optimization strategies, using emotional targeting, consumer psychology and behavioral data to generate more revenues, leads, engagement and sales.

For us, figuring out what to test is a two-step process. First, running an in-depth analysis of the funnel and understanding key behavior of customers. Using heatmaps, Google Analytics, surveys and any other analytical tool that can help discover the crucial pain points within a funnel that need optimizing and if optimized, can have a large impact on bottom line results. Next, once we’ve found the pain points within the funnel, is time to identify what the problem is and come up with hypotheses of how to fix it.

This is when a second step comes in: emotional targeting research. We dive into customer profiling,building personas, mapping out the customer journey and the emotional needs of the potential customers. Understanding the sate of mind a customer is in throughout each step of the funnel, running competitor research, SWOT analysis, market and trends research all help us identify the customer’s emotional triggers, their story and come up with a few hypotheses to test.

Once we have built these hypotheses the next step is presenting them to the team, getting everyone on board to ensure we’re all on the same page, creating the test (usually a more strategic test) and launching as soon as possible. For us, the first test for us is just part of the initial research, giving us indication if we’re on the right track and if we’re testing the right stuff.

Using Peep Laja’s process, Tommy’s ultimate goal is to build a plan that starts with low investment/high-reward and to prioritize tests from there.

Tommy Walker

is the Editor-in-Chief of the Shopify Plus blog. It is his goal to provide high-volume ecommerce stores with deeply researched, honest advice for growing their customer base, revenues and profits.

“For example, if a page with high-traffic & relatively high conversions has a slower load time, why do a radical redesign of the page, when you could look for ways to increase the page’s load speed or time to interaction? Once you’ve taken the time to put together a list of these insights, the question of “what to test first” is really a question of “what can I get away with without having to ask permission?” “

Within most organizations, people like the ​_idea_​ of being data driven to run tests (as long as they’re not the ones collecting the data), but when it actually comes time to test execution, everyone suddenly has an opinion, whether they’ve paid attention to the data or not. Most tests get shot down because of internal politics, not for impact potential, so just be aware.

So, “what to test first” really comes down to being able to gradually build up to the pages that have more stakeholders and require more resources. Essentially, you’re just trying to build a case that says “My research identified X,Y & Z problems on these pages, we had these hypotheses which turned out to be correct, made this much more revenue, and now I’d like to test these hypotheses on these higher priority pages, based on X,Y,Z things I’ve found here.”

CRO is as much (if not more) a game of politics as it is a game of statistics and insights. More tests die because someone internally shut it down, than from actual ability to drive revenue or change. So you need to do what you can early on to build trust in the process and ability to drive change.

Sujan Patel has his own methods and tools to formulating testing ideas and executing them.

Sujan Patel

has 12 years of experience in digital marketing and co-founded Content Marketer &  Narrow.io, tools to help marketers scale their content marketing & social media efforts. He is also an avid blogger and writes for Forbes, Inc, WSJ and Entrepreneur.

“1. I always start by formulating a hypothesis around the weaknesses of the site. I validate the hypothesis by surveying visitors using tools like Qualaroo and talking to potential and existing customers. This process usually gives me 5-10 different tests to run, typically around messaging and copy.
2. I prioritize the test based on impact or urgency and start a/b testing. I typically start with top of the funnel a/b test and move down the funnel but its different for every company and depends on where their biggest weakness are.”

Angie also uses a framework to determine what to test and to prioritize:

Angie Schottmuller

Helping organizations exceed goals and better understand customers using data-driven technology and persuasive marketing psychology.

“To decide what to test I map out and inventory issues and ideas we have for optimization, then I score them using the PIER framework. The PIE comes from the WiderFunnel model:

1. Potential – How much improvement can be made on the pages?

2. Importance – How valuable is the traffic to the pages?

3. Ease – How complicated will the test be to implement on the page or template?

4. Reusability – I added the “R” to score reusability of the insight learned

Once I’ve mapped out the highest scoring testing plan, the next step for me is getting the team aligned on what to test. You can work extremely hard on your end but you have to have your team members on the same page or you’ll be wasting a lot of time and energy.

1. Draft a test plan

2. Perform discovery for controlling the test environment — PPC ad management constraints, outside variables, potential pollutants, etc.

3. Regroup as a larger team to commit to the plan.

4. Execute”

Before looking at the numbers and finding the leak, Nichole first puts her customer to work on answering some tough questions and dedicates most of her time to defining the language a company should be using:

Nichole Elizabeth DeMeré

is a SaaS Consultant & Customer Success Evangelist. Chief Strategy Officer at @Inturact. Moderator at @ProductHunt & @GrowthHackers. Co-Founder at @GetTheCraft & @SaaSCommunity. Previously: Growth at @Inboundorg. INFJ.

״Before starting out, I have the website owner fill out the Ideal Customer Profile Framework and the Value Proposition Canvas, then I look at the data. It’s a lot of work filling out both forms, however language is the most important aspect of converting/acquiring the right customers.

These frameworks and AB testing tips the CRO experts shared are simply our best practices and our tested methodologies . Now it’s up to you to take these processes and try them out for yourselves to figure out where to start testing on your site, and what to test in order to increase your conversions.

Which expert’s methodology best fits with your style? do you have a different way you go about finding what to test and where to start?

When I take a look at data from a website for the first time, it’s with a specific goal in mind.
Usually that goal is improving conversions: increasing the number of people who buy a product, make a phone call, or leave their contact information.

The thing I look for most is anomalies.. Did they have a traffic spike after implementing an advertising campaign? Are all of their sales on a Sunday? Maybe (like Hasselhoff) they’re huge in Germany. All of these things
are important to know as they guide me in deciding how and where to start optimizing.

I have to be very careful though, because sometimes anomalies can be due to things that aren’t interesting. This can oftentimes be filtered out with common sense (it’s pretty unlikely that my local Seattle area plumber is attracting a ton of legitimate traffic from Russia), other times it requires digging a little deeper into the actual data.

Why is this important? Using Google Analytics is like using a telescope to try to see the Martian
Landscape, if you point it in the right direction and focus it properly you’ll be able to see hills and
valleys, rivers and ocean beds.

It’s amazing what you can see when everything is put together properly!

https://sandpaw.weblogs.anu.edu.au/2014/05/20/lichen-on-mars-the-potential-for-a-green-future-on-a-red-planet/

The first thing you have to do is point the telescope at Mars (direct GA to your website) and then focus it properly (implement the tracking code). But that isn’t
enough!

You also have to make sure that your lens is clean, and there isn’t a bat flying between you and the sky. Using fuzzy data to make marketing and business decisions is like trying to plan a rover journey on Mars with a dirty telescope. A waste of time at best, and with the potential to actually be harmful!

Let’s take a look at some of the more common issues in Google Analytics.

Sometimes anomalies can be due to things that aren’t interesting.
Click To Tweet

Data Spikes

(Things in front of your telescope)

If we see something unexpected in our analytics data, the first thing we want to do is make sure it actually is something we’re interested in. We want to see the martian landscape, not a bat flying by, or worse yet some kids deliberately throwing a paper airplane in front of you.

I don’t think that shadow is actually part of the landscape…

 http://onwardstate.com/2013/03/18/32-people-who-are-better-qualified-to-serve-on-the-board-of-trustees/batman-the-dark-knight-batman-27026728-1600-1200/#prettyPhoto/0/

Bats

The Problem

We’ll start with benign bots and spiders. What are bots or spiders? Basically these are computer
programs that automatically crawl your page. Search engines use these to index your site. There
are a lot of other reasons why these programs do that as well but I won’t go into them here. Bots
may or may not influence your analytics data, depending on if they run JavaScript codes;
however they will register as a hit on your server (so if you’re comparing server logs to Google
Analytics reports this will account for some discrepancy).

The Solution

There is a very simple way to deal with this traffic built right into Google Analytics. In the
Reporting View Settings page, simply check the box labeled “Bot Filtering”. (As demonstrated in the picture below). Will this filter out all bots? Of course not, but it filters them out based upon
the IAB/ABC International Spiders & Bots List, which should get the majority of them, and the list
is updated monthly.

Those Pesky Kids

Now lets learn to deal with those kids throwing paper airplanes in front of your telescope. This is
known as referrer spam and comes in mostly two types, Ghost and Crawler.

The Problem – Ghosts

Ghost referrals are called that because they never actually visit your site, instead they merely show up in your Google Analytics data by sending data directly to the Google Analytics Servers. They cannot be blocked by blocking access to your site because they never actually visit it.

The Solution

You can block Ghost Spam from interfering with your Google Analytics data by setting up filters to block invalid hostnames. Ghost spam uses fake hostnames, because usually they aren’t even aware of what site they’re spamming! We can take advantage of this and simply set up a filter that only includes only hostnames we actually want to see. How to do this is described in more details here or here.

This is a filter I set up to block Ghost Spam on our property. Easy peasy.

The Problem – Crawlers

Crawler spam operates more like traditional search engine bots. One of the main differences is that they’re “rude”. They ignore the site rules you post in your robots.txt file and just crawl over your entire site. These bots are not only interacting with your Google Analytics data, but they’re
also costing you money as they’re registering as hits on your server.

The Solution

There are two common ways to deal with this problem. One way is to make a filter very similar to the filter you made to block Ghost Spam, detailed here. This method has the advantage of not requiring any coding or uploading anything to your website, but it doesn’t stop the bots from hitting your servers and you have to manually update the filter as you find new bots. The second method is slightly more technical. Basically what you do is set up a trap for spambots by making a link to a part of your website and then telling all bots that the link is forbidden in your robots.txt. Good bots will obey your robots.txt, bad bots will ignore it. Once they’ve registered a hit on the forbidden page they are IP banned and can no longer access your site. Instructions and downloads are available here.

It’s no danger at all if you just follow the signs and walk around

http://www.maggieestep.com/bamboo-booby-trap/

Good bots will obey your robots.txt, bad bots will ignore it.
Click To Tweet

Not Seeing Data

(Dirt on your lens)

The Problem – GIGO

Google Analytics, like all computer programs, operates on the basis of GIGO, Garbage In Garbage Out. If you change something in your site, are trying to track something new, or if this is the first time you set up Google Analytics it’s very possible that you messed up somewhere. As an example, one of our clients redesigned their entire website (including their purchase funnel) and we noticed in GA that suddenly they were having zero conversions! We went through everything and found that it was because the goals were pointing to a purchase confirmation page that no longer existed. Once we figured that out it was very simple to make the switch to start tracking conversions again accurately.

The Solution

There is no silver bullet to fix this problem. That being said there are some steps you can take to try to minimise this as much as possible. First and foremost, make sure that you’re implementing Google Analytics properly. (See our guide on how to do this here). After this, just make sure you’re constantly doing sanity checks on your data, and if something doesn’t make sense, dig in a little and see what that is. If you just made a change to your website, make sure all the relevant URLs are up to date.

The Problem – Filters

Filters are a very powerful tool in Google Analytics. They let you see exactly the data you’re looking for, and exclude extraneous information. Of course like any powerful tool, the potential to injure yourself is ever present. Filters can behave unpredictably (or at least in ways we didn’t predict, computer programs are never actually unpredictable).

The Solution

Always, always, always leave one view unfiltered. This view will be your “reset button” if you mess up implementing a filter. And when you make a new filter, let it run for at least a week before you start analysing the data from it. That will allow you some time to analyse any kinks that need to be worked out.

The Problem – Size

Google Analytics only records 10 million server hits in a single month, and one visit can generate multiple hits. Not only that, but when you have more than 500,000 sessions, Google Analytics starts to sample your data.

The Solution

If you find that you’re hitting this wall, consider upgrading to Google Analytics Premium.

Misinterpreting Data

(Seeing UFO’s)

An alien ship that has travelled hundreds of light years? Or a cloud?

https://en.wikipedia.org/wiki/Identification_studies_of_UFOs#/media/File:Lenticulariswolke.jpg

The final thing to keep in mind, is that analysis is only useful if you have a goal in mind. Anyone
can look at data and analyse it until the sun comes up, but if they aren’t analysing it with a specific
purpose in mind then they are just wasting your time as well as their own! That’s why it’s very
important to fully implement Google Analytics with Events, Goals and, if you’re an Ecommerce
site, Ecommerce tracking and Advanced Ecommerce Reports. Some of these (especially that last
one) take a little bit of know how and time to set up, but if you’re not tracking them you’re missing
out on valuable data.

Another important thing to do is make sure that all your Events and Goals have values attached to
them. Unless your site is purely a vanity project, you have some sort of bottom line; you should
be able to figure out exactly how much each view of a page is worth to you. Calculating ROI and
making sure you’re not wasting your money will be impossible otherwise.

Analysis is only useful if you have a goal in mind.
Click To Tweet

A Cool Trick!

One more cool trick that’s often overlooked. In Google Analytics it’s possible to track your users across different devices! This feature can really give you a whole new perspective on your returning visitors and it’s really simple to set up. Here is a guide to setting it up on your webpage. Give it a shot and see how people interact with your site across all of their devices!

Take It Away!

Keeping all of that in mind when you’re looking at your data on Google Analytics should help you see a much clearer picture. And if any of that sounds a bit overwhelming, don’t worry! You can get in touch with us and we’ll help you get crystal clear images of Mars!