The Geek Guide to Understanding Funnels in Google Analytics

 

In order to make your business a success, you should be spending more time and resources in converting existing traffic than acquiring new traffic.  When you work with the mindset of increasing sales by just sending more traffic to your website your cost per acquisition tends to be high and your revenue per acquisition tends to be low. So you may eventually end up making less profit and sometimes even loss.

The traditional way of converting existing traffic is by mapping the entire conversion/sales process from lead generation ads to post sales follow up and then looking for biggest drop-offs from one step to the next. You do that mapping in Google Analytics through Funnel Visualization reports.

In order to truly benefit from funnel visualization reports you must know how this report actually works. If you create wrong funnels then you won’t be able to map your conversion process correctly and without proper mapping there is no conversion optimization (or Conversion Rate Optimization, if you are from the old school)

 

Quick Recap of funnels and funnel visualization report

Before I go into the geeky details, I want to make sure that we all are on the same page. So in case you are not 100% sure, in Google Analytics a funnel is a navigation path (series of web pages) which you expect your visitors to follow to achieve website goals.

Through funnels you can determine where visitors enter and exit the conversion/sales process. You can then determine and eliminate bottlenecks in your conversion/sales process. There are two types of funnels: Conversion Funnel and Sales funnel.

A conversion funnel is a series of web pages which you expect your visitors to follow to complete a non-transactional goal like ‘newsletter signups’, ‘downloads’ etc.

A sales funnel is a series of web pages which you expect your visitors to follow to complete a transactional goal like placing an order on the website.  Checkout process is a good example of a sales funnel.

Note: There are two more types of funnels in Google Analytics: Multi channel Conversion Funnel and Multi channel Sales funnel. Both of these funnels are based on multi-channel attribution model. I have talked about multi-channel funnels in this post: Attribution Modeling in Google Analytics – Ultimate Guide.

types-of-conversions

 

In Google Analytics, a funnel is made up of a goal page(s) and two or more funnel pages (also known as the funnel steps). You can set up to 20 pages as funnel pages in GA. However don’t do that (more about that later).

As I mentioned earlier, a funnel visualization report is used to map the entire conversion/sales process in Google Analytics. Use this report to determine the biggest drop offs from one step of the funnel to the next. These drop offs can help in explaining which part of the website/ conversion process needs urgent attention.

drop-off-from-one-step

Note: The funnel visualization report is available under Conversions > Goals in your GA account. You can learn more about setting up goals and funnel visualization in Google Analytics from here.

 

Common issues while creating and optimizing funnels

The first step to conversion optimization is setting up the correct funnel(s). It is only after analyzing funnel(s) you can find out where visitors are dropping off before completing the website goals. So you need to set your funnel right.

Another issue that can cripple your conversion optimization efforts is misinterpretation of Funnel Visualization report(s). Misinterpretation leads to wrong conclusions which in turn lead to making wrong marketing decisions. Let’s first talk about correctly interpreting the funnel visualization report(s) in Google Analytics as most of us have already set up funnels.

 

Interpreting funnel visualization report

 uniquePageviews-notVisitors

Many marketers assume that the number 2,037 in the screenshot above denotes the number of people (visitors) who completed the purchase. They think so because they see a line at the top left hand side of their funnel visualization report which looks like this:

completed-purchase

 

But this is not true and simply misleading. The number 2,037 denotes the number of unique pageviews and not visitors. A unique pageview is the number of visits (also known as web sessions) during which a page was viewed once or more times.

A unique pageview is counted only once during a visit. So no matter how many times a visitor navigates to the same page in a given web session (or visit), the number of unique pageviews for the page will remain one.

For example if a person navigates to the home page three times in a given web session then:

  • the number of pageviews for the home page will be 3
  • the number of unique pageviews for the home page will be 1

 

Also the number of unique pageviews is not equal to number of visitors (or unique visitors).This is because a visitor can navigate to the same page multiple times during multiple visits and thus can generate multiple unique pageviews.  For example if a person view the home page three times in the first web session and 4 times in the second web session, then the number of unique pageviews for the home page would be 2 but the number of visitors (or unique visitors) will still be 1.

unique-notVisitors2

 

Funnel Visualization report doesn’t show the actual conversion path

Example-1

example-1

Let us suppose a visitor landed on the website via home page. He then navigated to the ‘shopping cart’ page and again visited the home page. All of this happened in a single web session. The funnel visualization report will not show the actual order in which the funnel steps were viewed. It would show an entrance to the home page, a continuation to the shopping cart page and an exit from shopping cart page to the home page (here index.php)

This happens because funnel visualization report doesn’t show ‘loop back’ .The ‘loop back’ is the activity of going back to the previous step in a funnel. In our case, the vistor went back to home page from the shopping cart page and thus created a loop back.

So people don’t always move through your sales/conversion funnel exactly the way you set it up in Google Analytics. Visitors can also enter or exit the funnel midway. Also note the the number of unique pageviews for the home page. It is 1 despite the page being visited twice. This is because the page has been visited twice in a single web session. Had it been visited in two different web sessions, the number of unique pageviews would be 2.

 

Example-2

example-2

Here the visitor landed on the website via home page. He then navigated to the ‘shopping cart’ page, then navigated to the home page and refresh it for some reason. All of this happened in a single web session. We have got two ‘loop backs’ here. One loop back occurred when the visitor went back to home page from the shopping cart page. The second loop back occurred when visitor refreshed the home page through his browser.

Since the funnel visualization report doesn’t show ‘loop back’, It would show an entrance to the home page, a continuation to the shopping cart page, an exit from shopping cart page to the home page and an exit from the home page to the home page.

 

Example-3

example-3

Here the visitor landed on the website via home page. He then navigated to the ‘shopping cart’ page, then navigated to the home page and then again navigated to the shopping cart page, all in a single web session. We have got two loop backs here. One loop back occurred when the visitor went back to home page from the shopping cart page. The second loop back occurred when the visitor went back to shopping cart page from the home page.

Since the funnel visualization report doesn’t show ‘loop back’, It would show an entrance to the home page, a continuation to the shopping cart page, an exit from shopping cart page to the home page and an exit from the home page to the shopping cart page.

 

Example-4

example-4

Here the visitor landed on the website via Product-A page. He then navigated to the home page, then ‘shopping cart’ page and then navigated to the contact us page, all in a single web session. The funnel visualization report would show an entrance from the product-A page to the home page, a continuation to the shopping cart page, an exit from shopping cart page to the ‘contact Us’ page.

Here no ‘loop back’ has occurred as the visitor did not return to any previous step in the funnel.

 

Example-5:

example-5

Here the visitor landed on the website via Product-A page. He then navigated to the ‘shopping cart’ page, then to Home page and contact us page, all in a single web session. The funnel visualization report would show an entrance from the product-A page to the home page, a continuation to the shopping cart page, an exit from shopping cart page to the ‘contact Us’ page.

Google Analytics simply check whether the funnel pages were viewed during a web session and if they were, then that is represented in the funnel visualization report in the order in which you set up your funnel, regardless of the order in which the visitors viewed the funnel steps.

 

Example-6:

example-6

In the first web session the visitor landed on the website via Home page and then navigated to the Shopping Cart page. In the second web session the visitor landed on the website via Home page, then navigated to the Shopping Cart page and finally navigated to the Checkout page.

Here no ‘loop back’ has occurred because the visitor navigated to the home page and the shopping cart page for the second time in a different web session. However since the home page and the shopping cart pages were viewed in two different web sessions, the number of unique pageviews for both home page and shopping cart pages is 2. Wherease the number of unique pageviews for the checkout page is 1 as it is viewed in only one web session (or visit).

 

Example-7:

example-7

Here the visitor landed on the website via Home page, then navigated to the Checkout page and then to the ‘order review’ page. Note the visitor did not navigate to the shopping cart page and thus skipped it. When a visitor skips one of the steps in a funnel which comes after the step at which the visitor entered the funnel then the funnel visualization report backfills the skipped step.

Here the shopping cart page is the skipped step which comes after the home page (the step at which the visitor entered the funnel) and hence it will be backfilled by the funnel visualization report.  So the funnel visualization report would show an entrance to the home page and then continuation to the shopping cart page, checkout page and order review page.

 

Example-8:

example-8

Here the visitor landed on the website via Shopping Cart page, then navigated to the Order Review page and then to the ‘Completed Purchase’ page. Note the visitor did not navigate to the Home Page and Checkout page and completed skipped them.

Since the home page is the skipped step which comes before the ‘shopping cart’ page (the step at which the visitor entered the funnel), it will not be backfilled by the funnel visualization report.  So number of unqiue pageviews for the home page would be 0.

The checkout page is the skipped step which comes after the ‘shopping cart’ page (the step at which the visitor entered the funnel), therefore it will be backfilled by the funnel visualization report.  So number of unqiue pageviews for the checkout page would be 1.

So the funnel visualization report would show an entrance to the shopping cart page and then continuation to the checkout page, order review page and ‘competed purchase’ page.

 

Example-9:

example-9

Here the visitor landed on the website via Home page, then navigated to the about us page, membership page and then signed up for the membership. But in the same web session, he again navigated to the home page and membership page before signing up once again for the membership but this time on behalf of his wife.

So here the visitor has repeated the funnel twice and completed the goal conversion (signup) twice. But in the funnel visualization report a goal is incremented only once during a visit. So no matter how many times the visitor signup for the membership in a give web session, you will see only one 1 signup in the funnel visualization report.

The goal will be incremented in the funnel visualization report  for the visitor only when he converts again in a different web session.

 

Factors which almost always result in misinterpretation of Funnel Visualization report

I have found following factors which almost always result in misinterpretation of funnel visualization reports:

  1. Not segmenting the Funnel data
  2. Ignoring Data Sampling Issues
  3. Using small time frame and small data set

 

Not Segmenting the Funnel Data

 not-segmenting-funnel

From the visualiation report above we can see that only 0.47% of 8266 visitors proceeded to the shopping cart page.  If we can make more visitors to reach to the shopping cart page, we can generate more sales.

Now the problem is, we don’t know which visitors (visitors from organic search, Paid search, email campaign or social media etc) are exiting the funnel in great numbers. Without segmenting the funnel there is no way we can determine the main reason of visitors’ drop off from the home page to the shopping cart page.

Unfortunately Google Analytics doesn’t allow segmenting the funnel visualization report on the fly. It also doesn’t allow creating funnels based on the historical data .

Note: When you changes an existing funnel in Google Analytics, you won’t be able to see historical data for that funnel. This is because funnel visualization report only shows data going forward. It can’t show retroactive data.

 

In order to understand how different traffic segments convert in Google Analytics, follow the steps below:

Step-1: create filtered profiles for each of the following traffic sources:

  1. Organic Search
  2. Paid Search
  3. Referral Traffic
  4. Direct Traffic
  5. Social Media

Step-2: Set up goals and funnel page for each filtered profile.

Step-3: Wait for at least a month so that the traffic data populate into the funnel visualization reports of each filtered profile.

Once the 30 days of data is populated into the funnel visualization reports, you are ready to interpret sales/conversion funnel for each traffic source.

I can’t wait for a month to get the data, so I use a special tool called PadiTrack to segment sales/conversions funnel. Through this tool you can create funnels on the fly and apply both default and custom advanced segments (set up in your Google Analytics Account) to your funnel visualization reports which are based on historical data.

To learn more about segmenting funnels through PadiTrack, check out this post: Conversion Funnel Optimization through Paditrack


Note:
When you use the date comparison feature of the funnel visualization report, Google analytics doesn’t show you the difference for different funnel steps. It only show you the difference in the total conversion rate for the funnel goal.

 

Ignoring Data Sampling Issues

If you manage a high traffic website (million of pageviews each month) then you simply can’t afford to ignore data sampling issues. When Google Analytics is sampling your data badly, you can’t blindly rely on the metrics reported by it. This is because there is always a strong possibility that the reported metrics are 10 to 80% off the mark.

If your funnel visualization report is based on more than 100k visits then Google analytics is going to sample the data whether or not you use Google Analytics Premium. So in order to fix data sampling issues run the report for shorter time frame which would include less than 100k visits.

To know more about data sampling issues in Google Analytics, check out this post: Google Analytics Data Sampling – Complete Guide

 

Using Small Time frame and small data set

Many marketers take marketing decisions based on small time frame or small data set. You can’t determine the best conversion path used by your visitors and then optimize your conversion funnel just on the basis of few weeks of data or handful of conversions.

You need at least one month of data in your funnel visualization report before you take marketing decisions or even consider funnel optimization. If you have a low traffic website, getting enough conversions in the desired time frame is difficult. Your best bet is to buy some extra traffic (via PPC or ads on social media) so that you can validate your tests/assumptions faster.

Note: Make sure that you always use descriptive names for funnel steps as they show up in your funnel visualization reports. Use a name which describes what the goal /funnel page is all about. Don’t use names like ‘step-1’, ‘step-2’ etc.

 

Impact of Funnel on Conversion Rate and Conversion Volume

There is no impact of the funnels you create either on the conversion rate (both Goal conversion rate and ecommerce conversion rate) or the conversion volume of your website. The funnels you define affect only your funnel visualization reports.

The other thing which is worth mentioning is that the funnel conversion rate is not the same as goal conversion rate or ecommerce conversion rate.  The Funnel conversion rate is the percentage of funnel visits which result in conversions. These conversions can be goal conversions or e-commerce transactions.

Funnel Conversion Rate = (Total Conversions/Total Funnel Visits) * 100

For example:

funnel-conversion-rate

Here the funnel conversion rate is calculated as:

Total Checkout Completion/Total Funnel Visits = (26,346/73,333) * 100 = 35.93%

Note: Goal Abandonment Rate = 100-Funnel Conversion Rate

 

Common issues while setting up Funnels in Google Analytics

Following are the common issues I have encountered while analyzing the funnels, set up by other marketers/analyst:

  1. Selecting wrong conversion path
  2. Entering incorrect data while defining goal and funnel pages
  3. Capitalization issues
  4. Assigning monetary value to transactional goals
  5. Using incorrect REGEX for Goal and Funnel Pages
  6. Not understanding the required first step
  7. Not Testing the Funnel Setup

 

Selecting wrong conversion path

Create a funnel only when there is a well-defined path you can see/expect your visitors to follow to complete your website goals. If a website goal (like file downloads) can be easily achieved by following dozens of different paths then don’t define a funnel. If you do, it won’t help you much in understanding how different traffic segments convert.

I am often asked the following question:

 How to decide pages for a funnel?

The answer is pretty simple. The pages which are most frequently viewed prior to conversions or transactions are strong candidates for funnel pages. Use the page value metric to determine such pages.

Also use the reverse goal path report (under Conversions > Goals in your GA account) to determine the actual navigation paths that triggered goal conversions and the number of conversions each navigation path triggered. This report shows the last 3 steps visitors took before viewing the goal page.

The navigation path that has triggered maximum conversions should be used as a funnel. You can also apply advanced segments to the reverse goal path report.

Note: You can only create funnels for URL based goals. So if you want to create funnels for event based goals then you need to use virtual pageviews.

You can learn more about virtual pageviews from this post: Google Analytics Event Tracking Tutorial

 

Entering incorrect data while defining goal and funnel pages

When you set up a goal or funnel page you specify only Request URI. The Request URI is what that comes after the domain name. For example in the URL http://www.abc.com/event-education.aspx the request URI is ‘/event-education.aspx’:

incorrect-funnel-data

Tracking Goals/Funnel Steps hosted on a different website

Google Analytics can track goal or funnel pages only when they have got the Google Analytics Tracking code installed. So if your goal/funnel page is on another website (quite common in case of affiliate websites where the final part of the checkout process occurs on a different website) then you should track the link to goal/funnel page using virtual pageviews and not event tracking.

This is because you can’t use events for funnel steps in Google Analytics.

 

Example

If a visitor navigates to http://www.xyz.com/checkout.php from http://www.yoursite.com/shopping-cart.php in order to checkout then you can track the visits to http://www.xyz.com/checkout.php by generating virtual pageviews using the following code:

<a href=”http://www.xyz.com/checkout.php” onClick=”_gaq.push ([‘_trackPageView’,’/checkout.php’]);”> Checkout</a>

So whenever a person clicks on the checkout button, a virtual pageview will be recorded by Google Analytics. You can now use this virtual pageview as a funnel step and get a complete picture of your sales process. Use the same methodology for goal pages hosted on a different website.

 

Capitalization issues

If you want to make goal page URL and funnel page URLs to exactly match the capitalization of visited URLs then you need to check the ‘case-sensitive’ check box while setting up funnel:

capitalization-issue

There are lot of websites out there which have got URLs in both uppercase and lowercase letters or in some weird combination of upper and lowercase letters. So if your goal/funnel pages didn’t match the capitalization of visited URLs then you will get incorrect data in your funnel visualization reports.

The capitalization issue is one of the most obvious, yet the most overlooked according to my analysis of hundreds of GA accounts.

 

Assigning monetary value to transactional goals

You should never specify goal value for transactional goals as this can inflate the revenue metrics in Google Analytics reports:

monetary-value

You should assign monetary value only to non-transactional goals (like ‘file downloads’, ‘newsletters signups’ etc), so that Google Analytics can calculate the ROI and per visit value.

 

Note(1): Goal value is the value of a website goal which is determined by calculating what you will get when a goal is achieved. For e.g. if you sell leads then revenue per lead can be the value of each goal.

Note(2): A non-transactional goal conversion can happen only once during a visit per visitor. For example if PDF file download is one of your goal, then Google Analytics will count only one conversion in a single web session (or visit), no matter how many times a visitor downloads the PDF file.

 

Using incorrect REGEX for Goal and Funnel Pages

One of the most common and very difficult issues to resolve while setting up funnels is using the correct regular expression (or REGEX) for goal and funnel pages.

Example:

incorrect-regex

In the funnel visualization report you may sometimes see 100% continuation rate from one step to the next. Like in our case there is a 100% continuation rate from shopping cart page to check out page and 100% continuation rate from checkout page to the order review page.

This usually happens when multiple funnel steps contain or match same web pages.

If you look at the funnel set up, the first step is the home page (/) which matches with all other funnel pages as they all  contain ‘/’. This is because of the ‘regular expression’  match type selected for the URL destination goal ( which is /completed-purchase.php)

The match type (regular expression, begins with, equal to) you select for URL destination goal is continued throughout the funnel set up.

So if you select ‘regular expression’ match for the URL destination goal then it will be the same match type for each funnel step.

Similarly, if you select ‘Begins with’ match for the URL destination goal then it will be the same match type for each funnel step.

Remember funnel steps can accept regular expressions.

In order to solve the 100% continuation issue in the funnel visualization report here, you should select ‘Begins with’ match type for your URL destination goal otherwise  you need to change the whole funnel set up.

Note: Just like 100% continuation rate, you can also see 100% exit rate in your funnel visualization reports whenever two or more funnel steps contains/match same web pages.

 

Another Example

If the goal URL is /.*/signup\.php

Then Google Analytics will match it with signup page in any directory. For example the goal URL will match the following URLs:

http://www.abc.com/signup.php

http://www.abc.com/offer1/signup.php

http://www.abc.com/offer2/signup.php?query=jay

http://www.abc.com/offer3/signup.php?query=shoes&id=2013

To learn more about the uses of regular expressions in Google Analytics, check out this post: Regular Expressions Guide for SEO & Analytics

Note: You can also use wild cards to define a goal or funnel page. For example, you can use *.pdf to define a goal page.

 

Not understanding the required first step

requiredFirstStep-1

When you mark first step of the funnel as required, the funnel visualization report includes only those conversions that pass through the required step. That means you funnel conversion rate could be different for the funnel in which the first step is marked as required.

In our case the required funnel step is the home page. So the funnel visualization report would include only those conversions in which the home page was viewed.

If you want the funnel visualization report to include only those conversions in which one of the product category pages was viewed then you can set product category pages as the required step:

requiredFirstStep-2

Similarly if you want the funnel visualization report to include only those conversions in which one of the product details pages was viewed then you can set product details pages as the required step:

requiredFirstStep-3

You can create multiple funnels for a single website goal using ‘required step’ and can get deep insight into how people are converting on your website.

 

Not Testing the Funnel Set up

Viewing an empty funnel even after waiting for weeks is one of the worst situation to be in. You can’t go back in time, fix the issue and get the historical data. Even if you fix the funnel set up now, the funnel visualization report will only show data going forward. That means you lost weeks of data in your funnel visualization report for good.

Therefore before I set up any funnel in Google Analytics, I always test it via PadiTrack to make sure that I am getting the data in various funnel steps. If my regex is incorrect or there are capitalization issues, I wont see any data and this will alert me to the potential problem.

To learn more about testing your funnels via PadiTrack, check out this post: Conversion Funnel Optimization through Paditrack

You can test funnel setup in Google Analytics by clicking on the ‘Verify this Goal’ link:

not-testing-goals

Note: In case of Google Analytics standard, it could take up to 24 hours for the data to populate in your funnel visualization reports. In case of Google Analytics Premium, it can take up to 4 hours to get the data.

 

Optimizing Google Analytics Sales Funnels

In order to increase sales you need to make sure that following 2 activities happen on your e-commerce website as often as possible:

  1. Website visitors add items to the shopping cart.
  2. Visitors who have added items to their shopping cart make a purchase.

I focus on two metrics to achieve the aforesaid objectives:

  1. Add to Shopping Cart Rate (NEW)
  2. Checkout Abandonment Rate (Traditional)

 

Add to Shopping Cart Rate

You website visitors will add items to the shopping cart when:

  1. You send highly targeted traffic to the website. This is one of the main requirements.
  2. Your website is visually appealing. Design matters a lot.
  3. Your products are enticing.
  4. Your offers create a sense of urgency. For example: “Order in the next 2 hours and get …….  “
  5. Your landing pages have got clear call to action.
  6. Your website has got no major usability issues
  7. Your website has got no credibility issues

 

How to calculate Add to Shopping Cart Rate?

Track the clicks to ‘add to shopping cart’ button as event goal in your Google Analytics account and measure the ‘Add to Shopping Cart’ rate from conversions report in Google Analytics:

add-to-shopping-cart

The ‘Add to Shopping Cart’ rate is calculated as:

(Total number of clicks on the add to cart button/total visits to the website) * 100

Focus on improving your ‘add to shopping cart’ rate to increase the probability of generating more sales. There is no point optimizing your sales funnel any further if the people are not ready to buy in the first place.

Note: Make sure that you segment the ‘add to shopping cart’ rate to its most granular level before you interpret it. All the data in aggregate form is crap.

 

Checkout Abandonment Rate

Asking people to add items to the shopping cart is the easy bit. Asking them to complete the purchase is hard.

If you want visitors who have added items to their shopping cart to make a purchase then don’t give them nasty surprises during the checkout process. Following are some nasty surprises which are worth mentioning as they almost always result in high checkout abandoment rate:

1. A very loooong checkout process – Each additional funnel step gives the opportunity to a visitor to leave the funnel and not convert. Therefore you should aim to minimize the number of funnel steps. I am a big fan of one page checkout.

2. Hidden Charges – Any extra charge/fees during the checkout process can immediately put off a visitor and can cause him to exit the funnel straightaway. Therefore be upfront with your prices as much as possible.

 

3. Forced Registration – It is the number 1 way to put off a visitor from converting. Never force a person to register in order to complete a purchase. Ask him to register only after the sale has been made. Sometimes people don’t convert just because they don’t want to register. For such people provide a guest checkout option. Your first priority should always be generating the sale.

4. Out of stock Product – The last thing you want your potential client to do is to add a product to his shopping cart which is out of stock and he comes to know about it only during the checkout. Make sure that the out of stock products can’t be added to shopping cart by any visitor.

 

5. Please also buy this and this and this…  – Cross promotion can result in increase sales when done in a moderate amount. But when you try to shove multiple products down a person’s throat, it can put him off from converting. Godaddy is pretty notorious in cross promoting its products. You try to buy one domain and it will try to shove every product in its catalog right down your throat. Avoid doing that.

6. Asking same information multiple times – When you ask same information multiple times during the checkout, you are literally telling your customers to exit the funnel right now or I will haunt you by asking again and again and again. It’s a really cool way to make sure that a customer doesn’t convert. So make sure that you never ask same information again.

Note: You must collect visitors email addresses in the first few steps of the checkout process so that you can later remind them of their checkout abandonment. According to various studies, email reminders have proved to decrease the checkout abandonment rates.

 

7. Poor Navigation – Sometimes poor navigation doesn’t allow a person to go back to a funnel step to make some changes.  In such cases he can either choose to restart the checkout process or exit the funnel for good. Lot of people choose the later option.

8. Limited Payment Options – The worst thing your customer could experience during checkout  is that his desired payment option (like Paypal) is not available.  So even when he was ready to pay, he couldn’t pay. So provide as many payment options as possible.

 

9. Website Errors – Any technical error can cause your customer to loose all the filled information. Forcing your customer to retype the information is a fire shot way to loose him for good. So always make sure that your checkout process is error free.

The Checkout abandonment rate is calculated as

(Total number of orders placed on the website / the total number of clicks on the ‘checkout’ button) * 100

You should aim to keep your Checkout abandonment rate as low as possible. In order to better understand the Checkout abandonment rate, segment this metric to its most granular level using Google Analytics filtered profiles.

Other Posts you may find usefulGoogle Analytics Tutorial – Understanding Traffic Acquisition

 

 

Himanshu Sharma About the Author: is the founder of seotakeaways.com which provides SEO Consulting, PPC Management and Analytics Consulting services to medium and large size businesses. He holds a bachelors degree in ‘Internet Science’, is a member of 'Digital Analytics Association', a Google Analytics Certified Individual and a Certified Web Analyst. He is also the founder of EventEducation.com and EventPlanningForum.net.

My business thrives on referrals, so I really appreciate recommendations to people who would benefit from my help. Please feel free to endorse/forward my LinkedIn Profile to your clients, colleagues, friends and others you feel would benefit from SEO, PPC or Web Analytics.

 

 

  • http://www.andykuiper.com/ Andy Kuiper – SEO Analyst

    Thanks Himanshu :-)

    • seohimanshu

      Glad you like it.

  • richard

    Very detailed. Well done!

    • seohimanshu

      thanks.

  • http://www.ewebplace.com/ Online shopping stores

    nice post

  • Александр Небылица

    Good tips. Thank you for that.

    But i have one advice. I think it would be more effective if you divide one such long topic on several more short topics. Because i’ve read only 80% of this topic. It is really too difficult to grasp all this information at once.

    • seohimanshu

      You can always come back and read the rest of the post. The blog is not going anywhere :)

      • Andy Detweiler

        This is phenomenally helpful. Really appreciate your efforts.

        • seotakeaways

          Thank you :)

  • Nitin Choley

    its a great post, and i liked ‘the blog is not going anywhere’ one thing i would like to add here even you are not stop writing such a great post

  • http://www.Afixi.com

    hi himanshu i am just agree with Александр Небылица, its true that you wrote a very informative and quite interesting topic over Geek Guide to Understanding Funnels in Google Analytics, but its not easy to understand at a time.. u should partition this topic so that we can understand it in a much simple way. thank you..

  • priyanka

    such a nice post…

    http://www.Afixi.com

  • Valentina

    I read your blog often to understand concepts related to Analytics. There was this one sentence you mentioned in this post “From the visualization report above we can see that only 0.47% of 8266 visitors proceeded to the shopping cart page.” You mentioned these are not UV or Visitors but Unique Pageviews. I got a lil confused when I read this and so wanted to let you know.

    • seohimanshu

      yes technically it should be unique pageviews. But you also need to keep the context in mind. It would be difficult to explain the concept if i don’t talk about visitors (people) in conversion optimization.

      • Valentina

        Sure.. that makes sense. However, Im trying to match UP for a funnel step and they dont match. Any ideas why. I’ve read that if the URL has two different page names it is considered as 2 UP but one goal. I dont have that issue..

        • seohimanshu

          what you have heard is not true. Without looking at your account, it is difficult to diagnose your issue.

          • Valentina

            unfortunately, Its a company account and I cant share it. But was looking for pointers I can check at my end to verify why the unique pageviews dont match the funnel numbers.

  • Arshad

    Hi Himanshu,

    If i want to track home page visitors in funnels and i don’t have index.php as default url for home page what url i should use in my funnel.

    • seohimanshu

      Use ‘/’ to track home page visitors.

      • Arshad

        When i put just / with no regex codes it shows me double visits for home whereas behavior report shows just half of the visits. Example: funnel report shows 45k visits but behavior report shows only 23k visits. Please let me know exactly how to crack this.

        • seohimanshu

          Use the match type ‘begins with’. Don’t use regex.

          • Arshad Shaikh

            Thanks for helping out but am using ^/$ with regex to track home page and it is giving accurate data now :)

  • Samuel

    Great post, and super useful articles – I’m now signed up!

    Quick question: how do you suggest setting up funnels for paypal checkout?
    On our website, customers have the option to pay by credit card (on our checkout page), or by PayPal (they are redirected to PayPal webpage). In both cases once the payment is completed, they are sent to the ‘thank you’ page.

    At this time, in funnel visualization, we have a lot of exit pages displayed as (exit). I assume these are the customers who leave the checkout page to go to the PayPal website.

    However, since even the paypal customers are then returned to the ‘thank you’ page, their purchase still count as a goal. Therefore I believe that the overall funnel conversion rate is correct, but not the conversion rate between each funnel step.

    Thanks for your input!

    • seotakeaways

      To get accurate set up, you need to use your own payment system. However this is a common problem for those who use 3rd party payment systems.

  • Hatt

    Hi there! Please could you answer something for me: How can visitors ‘land’ on a page which they have to get to by going through a few steps first? So my website visitors have to fill out a form to get some price quotes, however this price quote page is showing to be quite a prominent landing page in my report. Many thanks!

    • seotakeaways

      This can happen when your web page is not configured properly. Your web developer can help here. Ask your developer to make the price quotes page visible to a visitor only when he/she fills out a form.

      • Hatt

        Just saw this reply – thanks very much! :)

  • puja

    If I need to determine which of the registered users dropping of from a cart page is there any way? I mean here the numbers are obtained and filtered profiles results in segregated numbers from a particular source. But if I want to know say the emails of the registered users dropping of is there any way ??

    • seotakeaways

      No

  • Tim

    Hi Himanshu, I want to track exactly which user from which source (eg. FB or Google AdWords) converts into a sale and how many users from which source leave our homepage at different points in the process.
    Goal is to determine whether my FB campaigns are leading to more sales compared to my AdWords campaigns and vice versa. So far I can only determine from which source the user entered our website. After this I cannot find an exact allocation. I appreciate your help! Many thanks!