True Conversion Rate For Content Value

The real value of a client’s site taxonomy and webpage content is not truly available from Google Analytics when viewing the provided conversion rate. The conversion rates in the Goals Overview data cubes, and built-in tables do not reflect the User Experience of your target market. This raises three major concerns for the analysis of advertising value, budgets, and page performance.
  1. Those conversion rate percentages are calculated using sessions as the denominator.
  2. Those conversion rate percentage are calculated using bounced and non-bounced sessions in the denominator.
  3. Effective and actionable analysis requires a true conversion rate.
Sessions are not the best denominator to use for goals especially when the stakeholders are evaluating advertising budgets based on goal completions by channel, sources and mediums. When your digital advertising team is investing a lot of valuable efforts identifying key demographics and programmatic media buys based on user interests groups and user performance there is even more critical reason to stay away from the Google Analytics built-in reports and metrics. The solution is to use Calculated Metrics. Using a calculated metric available in the Admin section of Google Analytics, you’ll need to define the conversion rate based on Entrances, and based on Non-bounced Users. While the Entrances metric is still not a one-to-one metric of individuals who are visiting the website, conversion rates based on Entrances are typically higher than conversion rates based on sessions or users. Why entrances and not users or sessions is best defined in an article from the google analytics support page on bounce rate. In that article they define a bounce as a visitor who exits the entrance page without visiting any other page of the site. Even if the visitor bookmarks the landing page and returns 10 times but does not engage with the conversion or whatever the call-to-action may be, each return is a bounce.

The Non-Bounced Users metric provides a view of the conversion rate based on visitors who are engaged with the client’s website/content. I call this metric a True Conversion Rate (TCR). The onus for increasing the number of these engaged visitors is on the advertising team. By developing the TCR you are providing the stakeholders and the advertising team with analysis which provides evidence of the landing page and the websites ability to convert when the right target audience clicks through from the advertising. When you combine the TCR with audience segments, behavior segments, and drill down by source/medium in your analysis, many key actionable insights unfold.

  1. Does the landing page convert when visited by the target audience?
  2. Is the call-to-action communicating effectively?
  3. Is the landing page the right message for this audience?
  4. Are you targeting the right audience?
  5. Which programmatic logic is working, which isn’t?
  6. How much different is the conversion rate: > 300%, 500%, etc.?
  7. What can organic engineering learn from the paid audience landers?
There are dozens more insight probing questions that could be added to the list, and depending on the client vertical and offers you can always find significant impact using TCR. Here’s the how-to guide.

Log in to the View level of the client’s Google Analytics Admin tab. From here click on the calculated metric opportunity. 
Calculated metrics for true conversion rate

The View Level of Admin is where to find calculated metrics


Of course we’ll need to click the New Calculated Metric button.

create-metric





  1. Name the metric
  2. This is a system completed naming convention.
  3. There are five formats to set. In this case we are creating a percentage.
  4. Write the formula.
Four steps to create the metric

Four steps to create the metric


Make absolutely certain to set the formatting to be a percentage. The data management system will add the variables as you begin to type in the formula box. Use the goal completions in the numerator and make sure to use parenthesis to surround the denominator. Remember the rule of operators, PEMDAS?


As shown in the image above I’ve set the denominator for the true conversion rate to subtract Bounces from the total number of Entrances.

Now that you have the TCR defined you will need to create a custom report to use it in analysis. I typically create a single custom report and add a new tab for each goal that I have a TCR for. If you’ve never created a custom chart before… shame! But, you’ll see that it is fairly simple process and far more powerful for discovering insights.

Here’s my system for creating a True Conversion Rate report.

The first step is to navigate over to the Customization section in the client’s Google Analytics Admin. And, of course, create a new custom report.
Creating a custom report for true conversion rate analysis.

Creating a custom report for true conversion rate analysis.


Then you’ll need to build the report to include the metrics, dimensions, and any filters you require.

  1. Name the report, True Conversion Rate
  2. Add the Tabs, one for each calculated TCR
  3. Set the Metric. First metric is the TCR and the second metric is the conversion rate for the same goal. This gives you a side-by-side comparison of the two conversion rates for the same goal.
  4. The dimensions are a drill down function where the first position is the default and each dimension below it provides you with a deeper view. In my case I like to see the TCR by source. When I click on the source I want to next see the breakdown by medium. Drilling down again I’ll click a medium to see the landing page. Finally I can drill down on a landing page to discover the city the user was in when they completed the conversion engagement.
Here’s an example of the custom report.

true-conversion-rate
  1. Select the tab you want to analyse the TCR for.
  2. Compare the standard Google Analytics CR to the calculated metric for TCR
In this case the goal 9 conversion rate as reported in the built is Google reports is 1.26%. When the bounces are removed from the Entrances the True Conversion Rate is 5.27%. That’s a full 418% higher conversion rate. From here, when using a custom report, you can add custom segments just like you can in all GA Reports, and you can drill down to each dimension that was set when you created this custom report.

One last idea on the dimensions to drill down on is to add a Device Category option. There you can see what device is used more frequently for conversions.

tcr-device

In this case from the image above, I’m looking at phone calls to a call center from a website. The custom report identified there are more conversions from desktop devices then from mobile devices.

Interesting… and true conversion rate is 312% higher.

While Google still provides the analyst with no metrics that provide the actual number of visitors to the website or the webpage, we have to innovate and define as closely as possible. Entrances are a far better means to calculating conversion rate than sessions, but clearly we cannot truly provide the client with 100% data integrity. Using the entrances in this calculation of true conversion rate is a giant step closer to mastering optimization. 

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How Data Integrity Saves Your Business Thousands of Dollars

Businesses are using Google Analytics to track and record website performance data more than any other analytics tracking program. Not only are businesses using it more than any other program, but year after year Google Analytics is growing in market dominance. With nearly 65% of Fortune 500 companies adopting Google Analytics and Google Tag Manger[1] it is clearly the powerhouse for web analysis. According to a report from KissMetircs[2], the majority of Google Analytics installations are incomplete or not setup correctly.
google analytics typically installed inaccurately

Google search results for Google Analytics Inaccurate














Poor data Integrity is costing U.S. businesses billions of dollars a year.
The Data Warehousing Institute (TDWI) estimates that poor quality customer data costs U.S. businesses a staggering $611 billion a year…  [3]
According to a survey from ISAS (May 2016). [4It isn’t just small and medium sized business who may not have a dedicated Data Integrity process but it is a problem that affects even large businesses. A recent release of bad data news announced from the Wall Street Journal story, the impact of poor data integrity at Facebook on the advertisers meant thousands of paying customers were not getting accurate information regarding the impact of their advertising. Those companies were making businesses decisions for over a year based on statistical analysis built from data that is inaccurate, incomplete, and filled with errors.

A lack of DATA Integrity can result in many costly mistakes:
  • Increasing advertising budgets to channels and mediums where the conversion rates are incorrectly indicating high performance results.
  • Decreasing advertising budgets to channels and mediums where the conversion rates are incorrectly indicating poor results.
  • Changing content and navigation on the website based on incorrect, incomplete, or data that is missing key elements from user results and user engagement.
  • Financial impacts, such as increased operating costs, decreased revenues, missed opportunities, reduction or delays in cash flow, or increased penalties, fines, or other charges.[5]
  • Confidence and Satisfaction-based impacts, such as customer, employee, or supplier satisfaction, as well as decreased organizational trust, low confidence in forecasting, inconsistent operational and management reporting, and delayed or improper decisions.[5]
  • Productivity impacts such as increased workloads, decreased throughput, increased processing time, or decreased end-product quality.[5]
  • Risk and Compliance impacts associated with credit assessment, investment risks, competitive risk, capital investment and/or development, fraud, and leakage, and compliance with government regulations, industry expectations, or self-imposed policies (such as privacy policies).[5]
In my experience I understand it takes a combined effort of an experienced Google Analytics integration professional, plus the key stakeholders of the business, and a website development team to ensure the data integrity is intact. In today’s always online business the change in technology, methodology, and needs of the business and its customers are a constant. In my role as senior data science and analytics management I’ve developed the necessary methods to accurately complete the installation of Google Analytics, Google Tag Manager, Search Console, and more. If my client already has installed any or all of these, the process works to identify where data integrity is valuable and where it is at risk. Find out if the data your Google Analytics account is capturing is providing your business with accurate business intelligence.

  1. Data Integrity Scorecard: A 21-point checkup of the client’s Google Analytics data. The Score ranges from 1 to 100 with 100 being perfect. Any score below 50 we cannot, nor should the client use the GA data for reports, tracking, performance, budgets, etc.
  2. Site Tracking Assessment Guide (STAG): This is a comprehensive review of the client’s web property where we identify and document all of the tracking opportunities for developing goals, funnels, custom dimensions and metrics, custom reports, key demographic segments. and the initial design for a custom attribution model.


[1] Google Analytics and Google Tag Manager Dominate Fortune 500

[2] Common Google Analytics Data Errors

[3] Data Quality and The Bottom Line

[4] Business Impact from Bad Data

[5] Knowledge Integrity Inc. Report

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Analytical Insights for Virtual Page Views

The more I use a Tag Management System (TMS) for tracking and defining analytical insights from digital advertising results the more I value the application. This growing love affair is enhanced even more for me when combined with the use of my data management tools. Google analytics and Site Catalyst can take you a long way in simple website analysis, but when you want to drill down to discover how to make more from what your digital advertising is doing, or to discover what you’re missing, you need better data management tools. In this case study I have a local real estate client with a website that provides users with information about select neighborhoods in the nations 11th largest city. The website developer used virtual pages for each information article in each neighborhood. There are five virtual pages included in each neighborhood, each of them have the same trigger/name. That makes analytical insights a little easier for tracking events, but I cannot rely on page views in Google Analytics (GA) or from Site Catalyst as the KPI. Instead I’ll have to write a custom javascript that calculates the depth of a page and then tracks the scrolling depth to trigger the virtual page views.

Analytical Insights for Virtual Page Views

After creating the script and installing all of the tracking through the tag management system, I can use Google Analytics and the Real Time menu option to view the events. This view provides at-a-glance analytical insights to what users are currently up-to on the site.
Real time event trackin

I’m trying to develop insights for virtual page views to help sales convince the advertisers to want their ads placed on this real estate website. A key to the insights of the website is in the Neighborhoods section. I want advertisers to place their ads at the top of these pages for a premium rate, mid-page for a little less of a premium charge and at the bottom for the lowest advertising cost. Site visitors scroll the neighborhood pages to read relevant information about the specific neighborhood they are interested in. If I drill down on the GA Real Time events I can see exactly what information (virtual page articles) the user’s are reading over the last 30 minutes.

Virtual pages with real time tracking

The event labels tell the story about the user’s scrolling and that translates to how far down the page they scroll. As you may be able to surmise from looking at the table and graph above, the further down the page an article is, the fewer views it received.

For deeper analytical insights I want to discover more than just the obvious, “what virtual pages were viewed; how far did the user scroll down the page.” Selling advertisers on the value of their ad position should be easy enough with just simple scroll tracking, but with this custom scroll tracking script I can discover more than simple virtual-page-view metrics.

What we can know, and learn from the user’s scrolling behavior:

  • Does scroll depth correlate to conversion rate?
  • How much time was spent scrolling from section to section?
  • If a user clicks to the neighborhood landing page what percentage of the page did they view?
  • What percentage of users click the call-to-action at the bottom of the page?
  • What testing can be done to increase scrolling depth?

Using my data management tools (anlyticsAndDataScience.com) I can build a custom analysis table for discovering insights to each of these questions. Once I build the custom analysis data with the kpi collectors in the columns, it’s a simple matter of filtering the landing page for ‘/neighborhoods’ so the view data is precisely at the granular level I’m analyzing.

Custom analysis scroll tracking table

Developing the virtual page view tracking.

Within the script I have the opportunity to define the scroll depth by percentages. For this example there are five segments to the page (options.percentage ) so I’m tracking by quintile: 20%, 40%, 60%, 80%, and 100%. In the script I will set the page depth to identify the first virtual page read at 20%. Here’s what I have for tracking triggers:

Any landing page in the ‘/neighborhoods/’ file of the website will fire the scroll-tracking-listener. The list of virtual page names in the neighborhoods are:

Housing = Fires at 20% page view

The Market = Fires at 40% page view

Living Here = Fires at 60% page view

Things to Do = Fires at 80% page view

Stats and Facts = Fires at 100% page view

To build these tracking events into the TMS I need to define four custom variables as shown below.

User defined custom variablesEach of these four variables are a Data Layer Variables and you will follow these five steps to create each one.

  1. Name the Variable (eventAction, eventCategory, eventLable, and eventValue)
  2. Select the Data Layer as the variable type.
  3. Define the Data Layer Variable Name (eventAction, eventCategory, eventLable, and eventValue)
  4. Select Version 2 for the version.
  5. Save the variable

Creating custom variablesOnce the custom variables have been created it’s time to set the triggers for the scroll tracking. For this real estate case study I only want to track page depth so I’m going to create two triggers. First I’ll set the Scroll tracker to fire on any page in the ‘/neighborhoods’ folder of the website. Second I will exclude the pixel depth tracking that is defined in the custom script that I’ll get to in just a few minutes.

Create a Page View event:

  1. Name the trigger, Scroll Tracker
  2. Set the trigger type to ‘Page View.’
  3. Define the trigger to fire on a Page URL that contains the web site folder.
  4. Save the trigger

Create the pixel depth filter:

  1. Name the trigger, “Scroll Distance.”
  2. Set this to a ‘Custom Event’ trigger
  3. Fire on the ScrollDistance event name
  4. Set the eventAction to not contain Pixel Depth
  5. Save the trigger

Filtering the events

The only thing left to do is the creation of the tracking Tags. I want to track these events in Google Analytics (GA) so I will create one Tag to send the custom variable data to GA. I will set the calculations and data layer information in a custom HTML tag with a java script.


Setting the GA Scroll Depth tracking:

  1. Name the GA Tag “Scroll Depth”
  2. Choose Universal Analytics as the Tag Type
  3. Select track type to ‘Event’
  4. Set the category, Action, Label, and Value to the custom variables created earlier.
  5. Set the Fire On to the “Scroll Distance” trigger created earlier
  6. Save the TagSend the data layer to Google Analytics



All that’s needed now is the Tag containing the custom java.

You can get the scroll tracking script here.

Create the TAG for a custom HTML and paste the script.paste the custom script to an html tag













  1. Name the Tag “Scroll Tracker”
  2. Select the Custom Html product
  3. Paste the scroll tracker script into the html
  4. Select the Scroll Tracker trigger created earlier
  5. Save the TAG

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