Linking AdWords And Google Analytics Accounts Finally Gets Easier

Linking your AdWords and Google Analytics accounts opens up a whole new world of opportunity for campaign execution, management and analysis. Yet, the linking process has been cumbersome and not particularly intuitive. That is finally changing.
In the coming weeks, Google will be rolling out a simpler linking process–down to just three clicks–to all Analytics accounts.

The New Process

From the Admin section of your Analytics account, you’ll click on “AdWords Linking” in the Accounts column and then on “New Link” to follow the linking wizard. You can also access this in AdWords by selecting Google Analytics from the Tools and Analysis menu.

Why Link Your Accounts

Once your accounts are linked, you can import goals and conversions, site engagement metrics like bounce rate, and remarketing lists from Google Analytics into your AdWords account. Likewise, your AdWords data will import into your Analytics account (be sure to either turn on auto-tagging in AdWords from My Account > Preferences or tag your URLs).

The 10 Must-Read Blogs for Conversion Optimizers and Content Marketers

List of our 10 favorite blogs.
These are the blogs that share the latest research, thought leadership and best practices from some of today’s most respected marketers in landing page optimization, content marketing, search engine marketing and analytics.

Here’s the list:

1.   Marketing Experiments

One of the biggest dilemmas internet marketers face today is: “what actually works” vs. “the hype.” With millions of blogs about internet marketing, about 95% of what you read is garbage.
But Marketing Experiments leaves little doubt about their mission of truth. As they say on their home page: “MarketingExperiments is a research laboratory with a simple (but not easy) seven-word mission statement: To discover what really works in optimization.”
Every blog post is a mini case study about a real web optimization experiment.

2.   Conversion Scientist

Brian Massey, The Conversion Scientist, also takes a scientific approach (was the name a dead giveaway?) to optimization. On his blog he shares articles written for Search Engineland, ClickZ, the Content Marketing Institute and his own blog.
We really like his style of writing. He uses chemistry terms as analogies to explain complex web conversion topics with simple to understand language.

3.   Conversion XL

Peep Laja from Conversion XL never writes a blog post less than 1,000 words long. That’s because he literally gives away all his secrets in his blog posts (pay close attention). If you can’t conduct an A/B test or build a high converting landing page from on the advice on his blog, it’s because you haven’t made the time.

4.   The Content Marketing Institute

The term “Content Marketing” has become the latest hype-filled term, overtaking “Social Media” as probably the most hyped-up concept in 2013.
But content marketing is a real, irreversible and powerful force, and the Content Marketing Institute (CMI) has got the keys to the kingdom.

5.   Copyblogger

2^nd in line after CMI is Copyblogger. With free online courses on “Content Marketing 101,” “Copywriting 101,” “SEO Copywriting” and “Email marketing 101,” Copyblogger is probably one of the best resources for freelancers and consultants who are hoping to master the digital channel.

6.   Convince and Convert

Jay Baer of Convince and Convert has a different twist on Content Marketing. He talks about “Youtility Marketing,” which is also the title of his upcoming book of the same name.  What is Youtility Marketing? It’s marketing by providing real value to your target customers before they spend a penny with you. Read Convince and Convert to learn more about YouTility marketing.

7.   Kissmetrics Blog

The Kissmetrics blog is one those corporate blogs that represents content marketing done right. Kissmetrics sells a solid online analytics product, and their blog provides valuable advice to their target market (an example of Youtility Marketing).  Each one of their blog posts provides practical advice on conversion, internet marketing and how to grow your startup company.

8.   Social Media Examiner

No internet marketing reading list would be complete without something related to Social Media. However, Social Media Examiner is more than just a blog about social media. Started by Michael Stelzner, who originally rose to prominence after writing the book “Writing White Papers and launching his blog of the same name, Social Media Examiner provides advice on social media marketing, content marketing, and how it all works together.

9.   Moz Blog

Your internet marketing list wouldn’t be complete without a blog about SEO, courtesy of the SEO heavy-weight champion Moz.

10. Lander Blog

Finally we had to mention our own blog. From our Search Engine Marketing series, to our Lander Academy, webinars hosted by prominent internet marketers, we’re trying to distill the latest and greatest for those of you who are starting out and those of you who are veterans in the internet marketing field.

Honorable Mentions

Here are some of our other favorite blogs, and though they didn’t end up in our top ten, you’d be shooting yourself in the foot if you ignored them:

1. SEOBook is another great SEO resource, and many argue it’s the SEO heavy weight champion.
2. TopRank blog is a content marketing blog that consistently publishes valuable actionable content.
3. Six Pixels of Separation, by Canadian internet marketer Mitch Joel and author of the book by the same name, provides content that goes beyond just internet marketing advice. Joel provides a sort of crystal ball into the future on topics as varied as business, marketing and life.
4. A List Apart is the online magazine “For People Who Make Websites,” as their title tag states. It’s a fairly geeky website, with a focus on web design and web programming, but there is solid content for internet marketers here as well
5. Social Media Today publishes thoughtful articles by some of the biggest names in social media on strategies, tactics and industry specific knowledge for social media professionals looking for practical information in various fields.

6 Parallels Between Old-School B2B Sales Tactics & SEM

Today’s article is about the initial setup of your B2B search campaign. It also touches on the parallels between old-school B2B sales tactics and search engine marketing.

1. Set Business Goals For Your SEM Campaign

The first step to creating your SEM campaigns is to determine how you will set up your business goals. Best practice dictates one match type per campaign and tightly themed ad groups of keywords. You can utilize broad and phrase match to refine and find new queries that are related to your business, and then add them into your campaigns for full visibility.
What will your KPI be? Awareness is not the best, as we’re in business to make money, not to spend it (unreasonably)!  If you’re e-commerce, a return on ad spend (ROAS) goal is best, but if you’re a service or a B2B solution, lead-gen or cost-per-lead is the best route to go. Once you establish what your search program can generate out of the box, you’ll then be able to start optimizing accordingly.

2. Understand Your Customer & Message Them Properly

So, what do you say in your copy to your potential customers? From a B2B side, pricing is king. CTOs & CEOs only care about cost savings and getting the most bang for their buck, so ensure that yours is competitive.
Where you lack the ability to utilize pricing in an ad copy (e.g., in a solution or service), make use of messaging that details awards won for your products, prestigious projects accomplished, or highly pertinent and relevant details of services offered (e.g., support details, custom solutions or a free trial or consultation).
The simple call-to-action — “Buy now!” “Shop now!” “Official site!” — isn’t enough anymore. Customers want to know what you’re offering immediately — they must be able to read, trust and differentiate your ad from your competitors at a glance.
We recently scrubbed our account and saw this generic copy as an opportunity to improve performance. When we phased out old ad copy that had very generic calls-to-action and created new copy to highlight performance, scalability and durability of our products, we saw increased ad click-through rates and site engagement.

3. Go Above & Beyond For The Customer

Once you get that customer to your site, you’ll need to make sure you engage them and give something back to your potential customers to make them interested in your company, whether it is a whitepaper, video or other information. While there is no such thing as a free lunch, there is an ability to hook a customer and build loyalty early.
If your business is the best in class (which is is!), give some of that informational wealth back to the customer. The same principle here applied to B2B marketing prior to the Internet – treat your customers right, and they will return. Provide them with a wealth of information so they are not only convinced to buy your product, but are also (if necessary) armed with the data they need to secure funding for it.
Make it easy for these customers to engage with your brand on your site. I’ve seen plenty of sitemaps that trap the customer in a specific portion of the site, preventing them from returning to what they were viewing or navigating freely to other solutions. I’ve also seen sites that required visitors to populate lengthy forms in order to gain access to consumable (and shareable!) content.
A customer who’s not interested in cloud computing would not, for example, accidentally end up on the commercial section of the AT&T site and click to download a whitepaper. Trust that if your customer is looking to engage in your content, they’re interested in the product you offer. Make it as easy as possible for them to access and consume your content so they return to your site for more and eventually close the sale on the products you offer.

4. The Customer Is Always Right

Customers want to be nurtured, and different customers need different types of content — some more advanced than others. Advanced customers are turned off when there’s only basic content available, so ensure that you cater to this crowd if that is your target audience.
Conversely, there also exists a niche to cater to smaller businesses, with easy to consume concepts that shows you’re the expert and are ready to help them during all steps along the way. The beauty with small businesses is that they may eventually turn into medium businesses and large businesses — remaining your customer for life if you nurture and do right by them.

5. Businesses Want A Personal Touch

Lastly, allow for ease of conversion on your website. Have a phone number present and easily accessible so the customer can quickly reach you for ad hoc questions or concerns, and ensure that call tracking of this number is enabled to tie value to customer calls.
Businesses don’t have time to waste looking for an answer on your site when they can just pick up the phone and get the answer immediately from you. When it comes to forms, the more that a customer needs to fill in, the more disgruntled and less interested in your product they become.
Utilize forms that have the minimum number of  fields necessary to obtain pertinent information in order to reach the potential customer. Now that the customer has done their research and has raised their hand in their final stages of choosing your company for their need, allow for the sales team to seal the deal on the phone — or organize a face-to-face meeting, the way business was done before the Internet.

6. Word Of Mouth Is Still Important

Despite living in a digital world, word of mouth yields some of the easiest and best leads and sales that business can buy. Ensure to always link back to your social media, and allow customers to share your content with other colleagues, linking back to you and your product.
Business on the Internet isn’t done much differently than it was in the past. These opinions are formulated out of extensive research and testing we’ve done that speaks to how IT decision makers, as well as small and medium business owners want to engage with business technology and solutions. Understanding your product and choosing it out of a sea of competitors should be simple, easy, and clear, with minimal roadblocks to make the sale.

Infographic: 2013 SEO Ranking Factors, From SearchMetrics

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.

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.

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

 
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:

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.

Funnel Visualization report doesn’t show the actual conversion path

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

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

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

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:

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:

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:

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:

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:

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

 

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:

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’:

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:

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:

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:

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

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:

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:

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:

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:

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.

Read more: http://www.seotakeaways.com/the-geek-guide-to-understanding-funnels-in-google-analytics/#ixzz2XJql4wah

Goodbye Enhanced Campaigns, Hello Bing Ads

Once July 23^rd rolls around, I hope we can all agree to stop referring to ”enhanced campaigns” as such and get back to simply calling them “campaigns.”
It was a great message spin on Google’s part to select this antonymic adjective to describe campaigns which offer fewer targeting options and higher CPCs — but, as marketers come to see the change for what it truly is, I believe the time has come to retire that modifier.
I suspect that few people actually believed the “enhanced” bit, and fewer still do now that enhanced campaign cost performance data are emerging.  To continue to associate the word “enhanced” with the new campaign structure will only lead to more cynicism and mistrust of Google within its advertising base.  It’s a shame, really, because Google is an amazing company that has done (and continues to do) amazing things for its advertising platform.
I have noticed a shift in advertiser attitudes toward Google over the past few months, and it is most noticeable when contrasted with attitudes toward Microsoft’s Bing Ads. In my unscientifically-validated opinion, it seems that advertiser respect for Google has dropped a few pegs, while Microsoft is gaining new admirers and renewed respect.

Search Marketers are going wild over Microsoft’s Bing Ads. Image via Shutterstock.

Is Microsoft Winning New Hearts And Minds?

To  illustrate my point, let me share an experience from the SMX Advanced Conference a few weeks ago. Paul Corkery, Microsoft Program Manager for Search and Tools, was speaking on the Amazing PPC Tactics panel about some cool new features in Bing Ads.
He started off by stating that Microsoft was committed to supporting the import of AdWords Enhanced Campaigns into Bing Ads, but also he hoped advertisers would appreciate that Bing Ads will continue to support desktop, mobile, and tablet targeting.
A spontaneous cheer arose from the crowd.
“And advertisers can still control bids for mobile devices at the keyword level on Bing,” he continued. The audience erupted again.
With each new announcement Corkery made about Bing Ads, the hooting and hollering became more intense. It got so loud, you’d have thought you were at an old-fashioned revival meeting. People continued to hoot and holler, clapping and loudly showing their support for Microsoft. For Microsoft!!
This was a true out-of-body experience for me. I remember back in the old days when Microsoft was (un)lovingly referred to as “the Death Star of the Pacific Northwest” because they were so dominant in the PC software space. But here it was — crowds going bonkers for Microsoft and Bing Ads!
That spontaneous outburst in Seattle probably says as much about Microsoft’s growing momentum in our search advertising community as it does the collective frustration with Google. It sure feels like lines have been crossed, and a tipping point has been reached that will lead to advertising budgets shifting away from Google and toward Microsoft — that is, once all this enhanced campaign migration baloney is over and done with.

Advertisers Returning Verdicts On Enhanced Campaigns

The first major studies of the economic impact of enhanced campaigns have been hitting the news — and the news is not that good.
At SMX Advanced, a few PPC experts shared their experiences on a panel entitled, Best Practices for Enhanced Campaigns . My good friend and colleague, Christine Churchill, wrote a great recap of the panel in her last SEL column, but one of the most important takeaways from that session was the fact that after spending $5 million within enhanced campaigns, CPAs across all devices had risen alarmingly.
Last week, a few other leading advertisers reported similar findings.
Search Engine Land contributor Ginny Marvin wrote an eye-opening article about digital agency iProspects’ results from $6 Million in enhanced campaign ad spend. iProspect reported that while they have seen increased traffic and revenues since April, they’ve also observed higher CPCs for mobile (9%) tablets (12%) and desktops (14%).
Most significantly, Dr. Sid Shah, Adobe Director of Business Analytics, published a research and analysis report entitled, “Google Enhanced Campaigns to Impact Google’s Ad Revenue; New Algorithms Crucial For Advertiser Success.” In his analysis, which was based on $100 Million of Google AdWords enhanced campaign ad spend, Dr Shah has observed a 6% CPC increase from March through May. The report goes on to forecast another 5-10% CPC increase over the next two quarters, compared with the CPCs in the same quarters in 2012. These increases are being driven in part by enhanced campaigns.
Lisa Raehsler wrote about the Adobe research study, and Google responded to that article with an incredible statement:

Only Google could dismiss a $100 Million, 3-month ad study like this.

Really? A study involving $100 Million of ad spend isn’t a large enough sample size to make a reliable conclusion about the economic impact of enhanced campaigns? Wow. Pity the small advertisers this whole enhanced campaigns thing is supposed to help — they could gather data from now until the sun burns out and they still wouldn’t know whether it is working or not. Wow. Wow. Wow.

What’s An Advertiser To Do?

Reading these economic impact reports, which reasonably mirror my own observations and those of numerous other advertisers I’ve talked with, it is clear that advertising on Google has just become more expensive. Even if, like iProspect, you see increased traffic and revenues, these come at higher costs and take some more of the fun out of advertising on Google.
Unless Google relents on keyword level control of mobile bids (yeah, right), allows for expanded bid modifier ranges (I am still betting on this) and adds targeting of tablet devices back in (fuggedaboutit), it sure looks like the net impact of enhanced campaigns is going to be lower returns on Google ad spend.
Does that mean you should stop advertising on Google? Heck no! There’s still way too much good traffic and revenue to be had — and Google’s Display Ad network is still, in my opinion, hands-down the best in the industry. However, what we should all do is consider shifting more search ad budget over to Bing Ads.

What To Expect On Bing Ads

If you are not yet advertising on Bing Ads, and want to know if it’s worth your while or not, here are two back-of-the-napkin calculations you can use to estimate your potential on Bing based on how you are are doing now on Google.
To estimate Conversions on Bing:

• Conversions on Bing Ads = (Conversions from Google Search) x 20%

In other words, if you get 1,000 conversions on Google, you can figure that the same campaign imported into Bing Ads should be capable of ~ 200 conversions in the same time period.
To estimate your Cost Per Conversion (CPA) on Bing:

• Bing Ads CPA = (CPA from Google Search) * 80%

So, if you are averaging $50/conversion on a Google search campaign, expect that same campaign to bring you conversions at around $40 on Bing Ads.
These are rough estimates from a sampling of our US and Canadian clients, and it is quite possible to achieve this level of performance by simply opening up a Bing account and importing your existing Google campaigns. You can do better with some time and attention. We’ve seen CPAs range from 60% – 95% of their AdWords equivalent. We’ve seen conversion volumes as high as 25% of the AdWords equivalent, but rarely below 15%.
As you can see, there’s plenty of low-hanging fruit that’s yours for the easy picking by just getting started with Bing. So, once you’ve finished dedicating your waking hours to converting and tweaking your Google Enhanced Campaigns, start spending more time over on Bing Ads. You’ll be glad you did.

Testing New Keywords Without The Anxiety

New keywords are like the life blood of any established PPC account.

Was that analogy too weird? Eh, either way, you see what I’m saying. Your account is like an old, wrinkly hot mess vampire and you need to keep feeding it new keywords to keep it all Tom Cruise fresh.
Here’s the rub, though: new keywords are scaaary. Will they bring you conversions? Will they spend a lot of money, really quickly? Will the CTR be crap and bring your quality scores down? AAAAAHHH! There are some ways to predict the future for these keywords. You’ve got the traffic estimator tool and the like. But there’s no way to know for sure what will happen. So, I’d like to present two ways you could test new keywords to help you deal with the anxiety behind it.
Create A Campaign For New Keywords
I had an eCommerce client that I had some major new keyword anxiety for. So, I decided to make a new campaign that I could use to test new keywords in. I split ad groups based on product and modifier. So, let’s say the site sold pencils. I had an ad group for generic pencil keywords, specific color pencil keywords, adjective+pencil, etc. I’d just create a new ad groups when I found new keywords that didn’t fit in the existing ones, and I used the same ad template that called out the product and touted our best features/benefits. This was pretty easy to do with the template I made in Excel. But the main point is to keep it as simple as possible without being so simple your keywords won’t make sense with your ads.
This let me keep a super close eye on my new keywords and give them their own little budgets so I’d not have to worry about them stealing money from nicely performing keywords in their campaigns. When I had enough data, I would know that either the keyword was a turd and I could scrap it or the keyword did well and I can add it in to its forever home (whatever existing ad group or a new one within an established campaign). If the keyword seems to do all right, but not well enough, try relocating it to its forever home and see if the increased ad relevancy helps!
Here’s what this method covers:

• Easy to keep track of
• No worries about new keywords stealing budget from other, established keywords
• Can be time consuming to build out new campaigns and ad groups
• Small risk that CTR won’t be as great if ad relevancy isn’t as great

(I’d like to point out that the last two bullets depend on each other. The less time spent building out ad groups and writing ads, the more risk of the last bullet point. The more time spent building out ad groups and writing ads, the less risk.)
Use AdWords Labels & Automated Rules
Using AdWords labels for all of your new keywords will help you keep track of them with just a couple clicks. Filter by label, and badda-bing, you can see all the keywords you’ve labeled as “new”.  This allows you to place all your new keywords exactly where they should go in your account, with optimal ad relevancy. No CTR issue risks!
But, what about budgets!? Well, this is where automated rules come in. Set yourself that label filter for your new keywords. Select all of them. Then, click “automate”.

Then, you can pause the new keywords once they’ve spent whatever amount of money each day that you’re cool with each keyword spending.

The problem here is the time set-up. You can’t tell it to do it just whenever it’s spent whatever amount that day. You have to set a time for the rule to run. So it would be best to set a rule to run each hour past noon or something like that. Which is kind of a pain in the bum to set up.
Then, like the other method, you wait for your data to get nice and relevant, and then make your decisions!
Here’s what this method covers:

• Easy to keep track of
• No worries about new keywords spending over what you allow them to each day
• Optimum ad relevancy
• Total pain in the bum to set up automated rules to run each hour.

Predictive Keyword Research for PPC

I just watched a fascinating video by Rand Fishkin on predicting keyword volume. It’s geared to his neck of the woods (SEO) but was important and insightful enough that I wanted to shed some additional thoughts on predictive keyword research for PPC.

What is predictive keyword research?
To me, it means getting ahead of a term or topic before it becomes popular. Think about the term “attribution modeling”. Before a few years ago this didn’t show up in search at all. Today it is all the rage and those who built the first landing pages, ads and bid on the keywords we ale to ride that keyword to some lead generation success until it became more crowded (currently 8 ads for that search query and the average CPC is projected at around $3).
Google Insights for Attribution Modeling:


Why bother with PPC keywords that won’t get any traffic today?
Well, you probably shouldn’t if all you are worried about is today. But if you are in it for the long haul then these keywords are where your account will find it’s future growth. Getting them in your account with the proper ad and landing page will help you build history, you will have a higher CTR once people do start searching for it and this a higher quality score and you will start getting the conversions as soon as people start searching for these terms and thus will aggregate a higher number of total conversions versus being the last to the party.

How do you conduct predictive keyword research?
Rand recommends a few methods. These include staying up to date on news alerts, social sources and checking in with Q&A sites to see if anyone is asking follow up questions about the news and social media topics. These all make sense to me and are a good place to start but certainly not the only place.

Here are a three additional ways to predict if a keyword that isn’t currently popular will gain some traction.

1. Look at conference topic titles. Do any stand out as having some potential? If you saw a presentation titled, “What is Local Search Marketing” by a prominent speaker and you had a local search marketing service you may consider getting ahead of that curve.

2. Take sales calls. Then look for patterns in what they are selling. If a company is investing a lot of dollars in outbound telemarketers they may be 1, creating interest in a unique service that you could capitalize on or 2, they have already identified a trend and are trying to jump on it quickly too.

3. Movies and TV. This one is the best. Mostly because it involves you killing some brain cells. But also because movie and TV terms and products spread fast. Think of Luwak coffee. Did anyone know what that was before the movie bucket list? (By the way, it is delicious.)

For eCommerce this can apply to potentially new products to start stocking, to keyword qualifiers that you should be bidding on or negative keywords you should add because the trend isn’t what you sell but could get spill over traffic (think someone who sells Olympic watches during Olympic season).

Lead generation companies can use predictive keyword research to find cheap clicks and take advantage of big spikes in traffic when everyone else will be rushing to get in on the action after it is too late.

In addition to the ideas I have mentioned, I am looking for additional tools to use for predictive keyword research, any of you have suggestions? Leave them in the comments below, thank you!

Google Display and Placement Fraud – Is Your Money Being Wasted?

The Google Display Network is nearly the whole internet. If you’re on auto targeting, even with some contextual keywords, it’s going to get crazy. There’s obviously always going to be click fraud, which is just like the click fraud you deal with in your Search Network campaigns. But, something I encountered for the first time recently was placement fraud. Now, I’ve seen MFA’s before, or Made-For-Adsense.
These are websites or blogs that were created only to generate money for some evil nerds likely dwelling in their mothers’ basement, spending all their cash on Star Wars collectors items. No offense intended to Star Wars fans! They use Google AdSense to make their cheddar. AdSense is the Google program that allows AdWords ads to run on their sites, in case you didn’t know. The quality of the content is pretty bad on these sites. Sometimes they’re just scraped from other sites, which is referred to as a “scraper site”.  I know that I’ve seen scraper sites of PPC Hero, even whilst Googling myself. It’s a dead give away when there’s more ads than there is content. Because these little mouth breathers don’t care about content and just want clicks, they’ll employ armies of low-paid ad clickers or automated programs known as “click-bots” to increase the number of clicks. What jerks, right? These sites are a big reason placement reports and placement exclusions are so important.
So, how is placement fraud different? Well, it’s almost the same thing. Still jerks employing shady tactics to steal your money, but this time–it’s not even a site.
I was digging through a placement report looking for awful placements to exclude when I found a site that had spent a lot of money across all my differently targeted ad groups called meviodisplayads.com. Having Display Ads right in the title made me think “ugh, this MFA has spent so much money, what jerks!”. But when I went to the site, it didn’t generate anything. Just a 404 error. Trying to understand how a 404 error page with no ads on it spent over $300 in a single week, I did some sleuthing, but all I could find was this forum post from another frustrated PPCer. I didn’t understand how a non-existent website was showing my ads and making me pay Google hundreds of dollars, so I got in touch with AdWords help.
Their response? “I’ve never heard of this.” Their advice for preventing it? “Run placement reports and look for fraudulent websites.” Their response to me wondering about the over $300 I spent on a fraudulent website? “Sorry.” He also told me to switch to managed placements to avoid this issue. Super helpful!
So, unfortunately, their awful advice is the best advice. Be on the look-out for placements in your placement report that have spent money without converting or just sound like junk. If you’re a lead generation site, be on the look out for any site that sounds like junk, leads or no leads. Lead fraud is very real, my friends! Another tactic being used by those fraudulent gum smackers is creating false leads so their site looks good on your placement reports.
Let’s sum up your action plans!
To find placement fraud in your accounts:

• Perform placement audits at least weekly if you have automatic targeting on
• Look for websites that sound fishy, and check them out
• Look for websites that have spent a decent amount of money without converting that you’ve never heard of before
• If you’re in a lead generation account, look for websites that have spent a decent amount of money that you’ve never heard of even if they have leads

If you find a placement that’s fraudulent:

• Exclude it in all of your display campaigns!
• Make sure Google is aware of the issue by calling the Google AdWords help line (866) 246-6453) with your account’s customer ID number

Have any of you ran into this same issue? How do you prevent fraud on the Display Network?

AdWords “Remarketing Lists For Search Ads” Coming Out Of Beta

On the heels of releasing dynamic retargeting for retailers in AdWords, Google has announced it will be rolling out remarketing lists for search ads (RLSA) to all enhanced campaigns advertisers over the next few days. RLSA, which launched in beta last July, allows marketers to modify and tailor their search ads, bids, and keywords based on visitors’ past activity on their sites.
In the beta, a European online tire retailer saw a 161 percent conversion rate increase with RLSA, which led to a 22 percent overall sales increase. The new conversions had a 43 percent lower average CPA than previous campaigns, according to Google.
Using RLSA, you can increase bids for past site visitors who looked at specific high-value pages, added items to their carts or spent a certain amount of time on your site. You can also bid on more generic keywords, or broader match types of keywords for site visitors or past customers that you don’t include in your regular campaigns because they are too broad for general search traffic.
You can then show different ads to specific sets of site visitors. For example, you can write ad copy targeted to shopping cart abandoners.
RLSA bid adjustments combine with other bid adjustments for location, device and time in enhanced campaigns.
To use RLSA, you’ll need to tag your site with the Google Remarketing Tag for the Google Display Network. So if your site is already set with the remarketing tag, you are ready to start running RLSA.

What's a Good Conversion Rate on Google AdWords? Average Conversion Rates by Industry

Google AdWords Conversion Rates

Many businesses often wonder how much mileage their industry competitors are getting with Google AdWords. This is a tough problem because the data isn't publicly available. While I was able to create a create an aggregated model based on spend we've analyzed through our AdWords Performance Grader, we're sad to tell you that this data cannot be shared without violating Google's latest terms of service. However, there's a narrative we'd wish to pass along about Google AdWords and how PPC performs as an ad medium.

The Average Conversion Rate on AdWords Varies For Search And Display

We were able to estimate an overall summary conversion rate metric for Google Search ads and Google Display Network ads. While these estimates would be useful for financial investors to evaluate the effectiveness of Google generating ad revenues compared to other internet advertising platforms, we did not feel it would be helpful to businesses actually practicing search and display advertising on Google AdWords. For this reason, we dug deeper, and analyzed the average conversion rates on AdWords by industry, Google Search, and Google Display Network.
Ultimately, the end goal was to create benchmarks that John the internet retailer selling Persian carpets or Jane the local hostel owner to evaluate how well they're advertising against companies bidding for the same ad space.
The results were delightful and shed insights on a myriad of industry differences:

• The Google Display Network consistantly serves more ad impressions than Google Search, but these ads have a much lower click through rate.
• In some industries, Google Display Ads outperformed Google Search ads in conversion rates
• In others, Google Search ads had higher conversion rates than Google Display ads

In summary, the average conversion rate on AdWords varies by industry. Which leads to an unsurprising second insight.

The Average Click Thru Rate on AdWords Varies For Search And Display

In any given industry, the click through rate of Google's ads in Google Search were always higher than the click through rate on the Google Display Network. However, the average Google Display Network click through rate of any industry was still significantly higher than a Facebook ad.

The Average Cost Per Click on AdWords Revealed Conversion Opportunities

In our analysis we found a lot of industry verticals where Google's Display Network had lower average cost per click and higher average conversion rates than Google Search ads. Yes, you heard that right. There's still cheaper ads opportunities on Google that on average convert better than .
We believe this might be due to the effectiveness of Google remarketing, and the trend may even increase once dynamic remarketing becomes more widely adopted!

So How Do You Know What is a Good Conversion Rate?

If you really want to have an industry benchmark on Google conversion rates, give our AdWords Performance Grader a run. Otherwise, you should look at a metric called cost per lead. Take the average cost per click you are paying for an ad and divide it by your current conversion rate and you will arrive at cost per lead.


(e.g. If your ad's CPC is $1.00 and the conversion rate for the visitors that come through that ad is 5%, then your cost per lead is $1/.05 or $20 per lead)
Industry average conversion rates will not matter if your cost per lead metric is higher than the profit a customer can bring! Simply put, the higher the conversion rate, the less you'll be paying on PPC ads for bad leads!
 

Bounce Rate Optimization in Google Analytics – Complete Guide

The number 1 way to optimize your website conversion rate is by asking the right questions. Why is my conversion rate so low? Wrong question. Why is my bounce rate so high? That is the right question. Your conversion rate is low because majority of people come and leave your website without completing the actions/goals you desired (like making a purchase).

If people are not sticking on your website then it is highly unlikely that they will make a purchase or complete any other conversion. User engagement is the key to make your business more profitable. Unique visitors won’t make your business more profitable, engaged visitors will. If you can figure out, exactly why people come and leave then you are going to get a high conversion rate. The number 1 way of optimizing your conversion rate is to optimize your bounce rate.

Bounce rate is one of the most useful and powerful metrics available in Google Analytics. Through bounce rate you can effectively measure the quality of traffic on your website. If you are getting crappy traffic through a marketing channel (SEO, PPC, Email, Display etc) then bounce rate will be the first to shout and alert you. Then it depends upon you how you interpret the metric and take actions.

Before I dive deep, we all need to be on the same page which means refreshing the basics first.

What is a visit?

In order to understand bounce rate it is very important that you are absolutely sure about the metric called ‘visit’. In Google Analytics a visit means a ‘web session’. Web session is a period of interaction between a web browser and a web server. A web session ends when a visitor closes his browser or remains inactive on a website for more than 30 minutes. A Visitor can start two or more web sessions in a single day. That’s why Visits are generally more in volume than the number of visitors in Google analytics.

What is a single page visit?

Single page visit is a web session in which a visitor views only the single page of a website and then leaves the website from the landing page without browsing any further.

Layman definition of a Bounce Rate

Bounce rate is the percentage of single page visits (or web sessions) in which a person leaves your website from the landing page without browsing any further.

Geek definition of a Bounce Rate

Bounce rate is the percentage of single page visits in which only one GIF request is sent to the Google Analytics server. I will explain it later what GIF request means and how it impacts your bounce rate.

Types of Bounce Rate

Google analytics calculates the bounce rate of a web page and bounce rate of a website.

Bounce rate of a web page= total number of bounces on a page (in a given time period) / total number of entrances on the page (in the same time period). For example in the chart above:

1. The bounce rate of the page 1 = total bounces [(2070)/total entrances (2424)] *100 = 85.40%
2. The bounce rate of the home page ( / ) = [total bounces (171)/total entrances (416)] *100 = 41.11%

Bounce rate of a website = total number of bounces across all the pages on the website (in a given time period) / total number of entrances across all the pages on the website (in the same time period). For example in the chart above:
The bounce rate of the website = [total bounces (4039)/total entrances (5400)] *100 = 74.80%

Note: As you can see from the calculations above, bounce rate of a web page/website has nothing to do with ‘Time spent on a web page/website‘ (a common misconception about marketers and webmasters).

What are Bounces?

In Google analytics, bounces are number of single page visits resulting from a page and in each visit only one GIF request is sent to the Google Analytics Server.

What are Entrances?

In Google analytics, entrances are number of times visitors entered your site on the page.

GIF Request and Bounce Rate

Each time a page is loaded into a web browser, the Google Analytics tracking code (GATC) make a request for an invisible file called _utm.gif so that it can send the page view data to Google Analytics Server via this file.
The E-Commerce tracking code (ETC) can also make request for this file so that it can send the e-commerce data to Google Analytics server. In addition to GATC and ETC, the Event tracking code, Virtual Pageviews and social interaction analytics tracking code can also make request for this file.

The GIF request is quite long. Following is an example of a GIF Request:

http://www.google-analytics.com/__utm.gif?utmwv=4&utmn=769876874&utmhn=example.com&utmcs=ISO-8859-1&utmsr=1280×1024&utmsc=32-bit&utmul=en-us&utmje=1&utmfl=9.0%20%20r115&utmcn=1&utmdt=GATC012%20setting%20variables&utmhid=2059107202&utmr=0&utmp=/auto/GATC012.html?utm_source=www.gatc012.org&utm_campaign=campaign+gatc012&utm_term=keywords+gatc012&utm_content=content+gatc012&utm_medium=medium+gatc012&utmac=UA-30138-1&utmcc=__utma%3D97315849.1774621898.1207701397.1207701397.1207701397.1%3B…  

If you are a super geek and wish to understand the various parameters passed via GIF request then head straight to the official Google Analytics documentation on GIF request. In short, the _utm.gif file can send following type of data to the Google Analytics server:

1. Page view data (like visits, visitors, avg. time on site etc)
2. E-Commerce data (transaction ID, Item code, item value etc)
3. Social Interaction data (like facebook likes, tweets etc)
4. Details of the tracked events (like click on the video play button, click on an external link etc)

When a single page visit is not treated as a Bounce?

In order to truly understand bounce rate optimization it is very important that you are absolutely clear about what is counted as bounce and what is not by Google. In any scenario in which more than one GIF request is made in a web session (also called visit), the visit will not be treated as bounce by Google Analytics even if the visit is a single page visit.

In following scenarios, Google may not count a single page visit as a bounce:
 1. Event Tracking – A visitor lands on your website, triggers an event which is being tracked via e-commerce tracking code and then leaves the website from the landing page. For example a visitor landed on a web page of your site, clicked on the video ‘play’ button (which you are tracking via event tracking code) and then left the website from the landing page without browsing any further.
The reason why Google will not treat this single page visit as a bounce is because two GIF request were made during the web session. One GIF request was made by the Google Analytics tracking code (to send the pageview data) and second GIF request was made by the event tracking code (to send the details of the tracked event like number of clicks on the video ‘play’ button).
Needless to say, if you have implemented event tracking code on web pages, it can dramatically reduce bounce rate of your web pages and even your whole website. So you need to keep this in mind when you are analyzing the bounce rate of a web page.

2. Social Interactions Tracking – A visitor lands on your website, triggers a social event which is being tracked via social interaction analytics tracking code and then leave the website from the landing page. For example a visitor landed on a web page of your site, read a blog post, shares it via and then left the website from the landing page without browsing any further.
The reason why Google will not treat this single page visit as a bounce is because two GIF request were made during the web session. One GIF request was made by the Google Analytics tracking code (to send the pageview data) and second GIF request was made by the social interaction analytics tracking code

3. E-commerce Tracking – If a web page contains e-commerce tracking code then the code can make a GIF request once for each visitor’s transaction and once for each unique item in the transaction. So if a person has bought 4 products in one transaction then the ecommerce tracking code will make 5 GIF requests. Since more than one GIF request has been made, the single page visit can’t be considered as bounce.

4, Auto execution of tracked events – In case, a tracked event is automatically executed each time a page is loaded by a web browser then the single page visit can’t be considered as bounce, as more than one GIF request has been made. For example if you visit a web page and the video embed on the page automatically starts playing and you are tracking the click on the play button via event tracking code then more than one GIF request will be made: one request will be made by the Google Analytics Tracking Code and one will be made by the event tracking code. So bounce rate of such web pages will always be 0%.

5. Multiple Google Analytics Tracking Code on a web page- If a web page contains more than once instance of Google Analytics tracking code (like one tracking code in the header and one in the footer) then at least two GIF requests will be made. Consequently the single page visit won’t be treated as bounce. So make sure you have only one Google analytics tracking code on your web pages.

When a single page visit is treated as bounce?

In following scenarios, Google may count a single page visit as a bounce (provided only single GIF request has been made during the visit):
1. More than 30 minutes of inactivity on a web page (as a web session generally expires after 30 minutes)
2. A visitor closed the browser window after viewing a single page of your website.
3. A visitor clicked on the browser ‘Back’ button after viewing a single page of your website.
4. A visitor entered a new URL in the browser navigation bar after viewing a single page of your website.
5. A visitor clicked on an external link (which is not tracked by event tracking code) which takes him to another website after viewing a single page of your website.
6. Each time a web session gets killed – If a visitor is navigating from one web page to another and the web session gets killed for some reason then in this scenario the single page visit can be treated as bounce. In following situations a web session can get killed:

1. A visitor navigates to a web page which contains different Google analytics tracking code (may be the tracking code of some other website).
2. A visitor navigates to a web page which does not contain Google analytics tracking code.
3.  A visitor navigates to a web page which contains Google analytics tracking code but the tracking code is not correct.

How to analyze and report Bounce Rates?

You analyze and report the bounce rate in the similar way you analyze and report the conversion rates by segmenting your bounce rate and reporting bounce rate for each traffic source. So the questions that you should be asking now are:
Q1. What is the bounce rate of the traffic from organic search campaigns?
Q2. What is the bounce rate of the traffic from PPC campaigns?
Q3. What is the bounce rate of the traffic from a particular referral?
Q4. What is the bounce rate of the traffic from email campaigns?

How to interpret Bounce Rate?

Bounce rate can horribly mislead you if you don’t know how to interpret it. A high bounce rate is not always bad and sometimes even very low bounce rate can be bad. For example it is common for Blogs to have a high bounce rate. As people read the blog post and then leave the website.
If the bounce rate of your website is very low may be like 10% than there may be some issue with your tracking code implementation or may be some other website issue in which more than one GIF request is made in a single page web session and hence Google is not considering such visits as bounce.

Whenever you interpret bounce rate of any traffic source, keep following things in mind:
1. User Intent/behavior – How people usually interact with your website. How your website should be used according to you? If your landing page satisfies a visitor’s query then he will leave the website (provided you don’t give him another reason to continue browsing) and hence high bounce rate. If your landing page doesn’t satisfy the visitor’s query then also he will leave the website and hence the high bounce rate.

2. Type of website – Different types of websites have different bounce rate.  For example if your website is a blog then it is common for your visitors to read and leave and hence high bounce rate.  If you have a single page website then bounce rate will always be 100%. If you run a website which is purely built in flash and you don’t track flash events through event tracking then also your bounce rate will be very high as in majority of cases people don’t need to browse another page of the website.

3. Type of landing page – If a visitor lands on the ‘contact us’ page then he is most probably looking for contact information and therefore it is highly unlikely he will continue browsing. So bounce rate is going to be high.

4. Quality of the landing page – If you landing page is not visually appealing, full of ads, cluttered with text, looks spammy, doesn’t have clear ‘call to action’  then bounce rate is going to be high.

5. Type of content- If you have hard to consume content on your landing page then a visitor may bookmark the page and return to the website later to read it in his spare time.

6. Type of Industry- Bounce rate varies from industry to industry. In some industries high bounce rate is considered to be normal.

7. Type of Traffic – If you are getting wrong type of traffic on your website like traffic which is not your target audience then the bounce rate is going to be high.

8. Type of Marketing channel – Different marketing channels send traffic which tends to have different bounce rate. For example bounce rate of the traffic coming via social media sites is generally high. Same is the case with email campaigns.

9. Visitor Type- It is common for new visitors to bounce more than the returned visitors as they are not familiar with your brand.

10. Device Type – Bounce rate can vary from device to device. For example if your website is not mobile friendly then the mobile traffic to your website is going to have high bounce rate.