/ Growth Tactics

Understand and Improve Your Conversion Rates Via Google Analytics, Split Testing and User Personalization

Conversion Rate - The Unknown Species

You might have recognized there is lot of confusion around the conversion rate topic. In this post I would like to shed some light on it and clear the mist.

You will learn how Google Analytics calculates different conversion rates and why you might want to change the way you look at these numbers to make them become more relevant to your business.

Second, I would like to show how to improve the conversion rate using the model we discussed before.

Please note: This post requires some basic understanding of Google Analytics. However, I have linked further information so you can easily look up these topics.

Ready? Let us dive in…

Conversion Rate Basics

Like any other KPI, conversion rate is nothing else but a metric.

A metric is a calculation of several measures (e.g. number of sessions, users or goal completions). Any metric or even a measure may become a KPI as soon as you define it as such making relevant for your business.

The main reason for the confusion around the conversion rate definition is that the measures used for calculating this metric vary from case to case. Let me give you an example.

If you look up conversion rate in Wikipedia, you are redirected to a conversion rate definition for conversion marketing. Why? Likely because one may apply this metric to many channels and it is hard to define a single definition.

As an example, Google Ads defines a conversion rate for their own channel as follows:

Conversion rate = Number of goal achievements / Number of total ad clicks

So this definition is completely bound to Google’s ad service.

But even when we look at the formula presented in the above article about conversion marketing (focussing on conversion rate optimization (CRO) and on-site measures), it gets confusing:

Conversion rate = Number of goal achievements / Number of visitors

What’s wrong with this formula?

An on-site conversion rate doesn’t necessarily has to be based on the number of visitors. In fact, widespread Google Analytics uses the number of sessions (visits) instead of users (unique visitors) when calculating goal or ecommerce conversion rates. Minor difference, major impact - we will get to this a little later.

Same for the goal achievements: Do you want to count a goal achievement only once or how often it has been reached during a session or by a user?

The most basic definition of a conversion rate could be:

Conversion rate = Number of goal achievements per entity / Number of potential goal achieving entities

This isn’t academic talk. The reason why many people struggle with defining and interpreting a meaningful conversion rate for their business is because they don’t question the measures their conversion rate metric is based on:

  • What do I define as a (conversion) goal?
  • What entity do I want to look at that may potentially reach this goal?

Let us take a look at Google Analytics using Google’s terminology and then discuss the potential pitfalls afterwards.

Goal Conversion Rate in Google Analytics

Most CRO owners usually use Google Analytics’ goal conversion rates to measure their marketing performance.

Goal Conversion Rate Googl Analytics

Google Analytics calculates the goal conversion rate as follows:

Goal conversion rate = Number of unique goal achievements per session / Number of sessions

Number of Unique Goal Achievements

In most cases marketers have set up URI goals, meaning a goal is completed once a certain URI is reached during a session (visit). This URI usually is a checkout or thank you page.

Hint: If you are not familiar with how to set up a goal in Google Analytics, check out my post on process step optimization.

If a goal is reached multiple times during a session (visit), it still is counted only once. Let me illustrate this:

  • User A
    • Session A: Page A > Page B > Goal > Page C > Page D
    • Session B: Page A > Page B > Goal > Page C > Goal

Two goal completions are registered for both sessions, even though in session B the goal was reached two times.

The goal conversion rate in the above example would be:

Number of unique goal achievements per session: 2 / Number of sessions: 2 = 100%.

Be careful: If you use a URI path as a goal, the number of unique pageviews for this page might differ from the number of goal completions. Why?

The reason is if you set up your goal URI using head match or regular expression match, you might include more than one page in your goal definition, e.g.:

/thankyou
/thankyou/confirmation

could be counted as one goal, depending on your goal setup. So please make sure your goal is set up properly according to your requirements.

Number of Sessions (Visits)

As mentioned earlier, Google Analytics doesn’t use users (unique visitors) to calculate the goal conversion rate but the number of sessions during which a goal was completed.

As a reminder, a session is closed after 30 minutes of inactivity or at midnight (I am not covering any additional exceptions here).

That said, be careful when looking at the goal conversion rate in Google Analytics. Let me illustrate this:

  • User A
    • Session A: Page A > Page B > Goal > Page C > Page D
    • Session B: Page A > Page B > Goal > Page C > Goal
  • User B
    • Session D: Page A > Page B > Page A > Page C > Page D
    • Session E: Page A > Page B > Page D > Page C > Page D
    • Session F: Page A > Page B > Goal > Page C > Page D
  • User C
    • Session G: Page A > Page B > Page D > Page C > Page D
    • Session H: Page A > Page B > Page D > Page C > Page D

How many goal completions are tracked by Google Analytics in this case? Correct: three.

  • In total the goal has been reached four times, but session B is counted as one goal completion even though the goal was reached two times during this session
  • The goal has been reached by two users, but it is counted three times because User A reached the goal twice during two separate sessions.

The goal conversion rate in the above example would be:

Number of unique goal achievements per session: 3 / Number of sessions: 7 = 43%.

As you can see it can get tricky when relying on Google’s way of interpreting measures when calculating its goal conversion rate. We will discuss a little later when Google Analytics’ default conversion rate might match your business and when not.

Funnel Conversion Rate in Google Analytics

Hint: If you are not familiar with it, check out my post on process step optimization.

Funnel Conversion Rate Google Analytics

Consequently, Google Analytics uses the same formula for its funnel conversion rate:

Funnel conversion rate = Number of unique goal achievements per session / Number of funnel step 1 sessions

The only difference is that you have funnel steps included and the number of sessions is taken from the first funnel step instead of the whole page to calculate the funnel conversion rate.

eCommerce Conversion Rate in Google Analytics

If you are running a website where visitors purchase products or items, you likely would want to look at the ecommerce conversion rate instead of the goal conversion rate in Google Analytics.

If you are not familiar with it, check out Google’s help page for enhanced ecommerce data in Google Analytics to set it up - it is easy to set up.

Ecommerce Conversion Rate Google Analytics

Let us look at the formula Google uses for ecommerce:

eCommerce Conversion rate = Number of goal achievements per session / Number of sessions

In Google Analytics, goal achievements for ecommerce are called transactions. You might have recognized it: This time the goal achievements are missing the term ‘unique’.

In contrast to the conversion rate metrics we discussed before, this time multiple goal completions (transactions) can be counted within one session.

Let us have a look:

  • User A
    • Session A: Page A > Page B > Transaction > Page C > Page D
    • Session B: Page A > Page B > Transaction > Page C > Transaction
  • User B
    • Session D: Page A > Page B > Page A > Page C > Page D
    • Session E: Page A > Page B > Page D > Page C > Page D
    • Session F: Page A > Page B > Transaction > Page C > Page D
  • User C
    • Session G: Page A > Page B > Page D > Page C > Page D
    • Session H: Page A > Page B > Page D > Page C > Page D

How many transactions are tracked by Google Analytics in this case? Correct: four. Every transaction is counted, regardless if it happened multiple times during a session (visit) or just once.

The ecommerce conversion rate in the above example would be:

Number of goal achievements per session: 4 / Number of sessions: 7 = 57%.

Be careful: Because transactions are counted every time they happen, unintended counts might occur:

  • A user refreshes the confirmation page
  • A user bookmarks the confirmation page and opens it later
  • A user closes the browser, opens it later and the confirmation page gets reloaded

Unfortunately, you can not prevent Google Analytics from tracking these “false” transactions.

Instead, you would need to either:

  • Prevent the confirmation page from reloading or
  • Prevent the ecommerce Google Analytics script from firing more than one time

Segmented Conversion Rates in Google Analytics

You may easily create a segment in Google Analytics to recalculate the conversion rates outlined above based on the sessions segment you would like to look at.

If you want to only look at the ecommerce conversion rate for US users, you may create a segment filtering out users from other regions.

Segments Google Analytics

There is one exception though: You may unfortunately not apply segments to a conversion funnel visualization. If you want to look at the funnel conversion rate for a specific segment (e.g. a specific traffic source), you would need to create a filtered view from where you can call the funnel visualization.

Do Google Analytics’ Conversion Rates Really Help You To Understand Your Business?

As outlined, there are many ways to look at the measures that are used to calculate conversion rates.

eCommerce aside, Google Analytics calculates the metric as follows:

Conversion rate = Number of unique goal achievements per session / Number of sessions

For some cases this might be fine, but in many cases it isn’t helpful. Why? Let me use the example above once again:

  • User A
    • Session A: Page A > Page B > Goal > Page C > Page D
    • Session B: Page A > Page B > Goal > Page C > Goal
  • User B
    • Session D: Page A > Page B > Page A > Page C > Page D
    • Session E: Page A > Page B > Page D > Page C > Page D
    • Session F: Page A > Page B > Goal > Page C > Page D
  • User C
    • Session G: Page A > Page B > Page D > Page C > Page D
    • Session H: Page A > Page B > Page D > Page C > Page D

Let us iterate through some possible conversion rates...

Goal Conversion Rate 1 (Session Goal / Sessions - Google Analytics Default)

Google’s goal conversion rate in the above example would be:

Number of unique goal achievements per session: 3 / Number of sessions: 7 = 43%.

Goal Conversion Rate 2 (User Goal / Users)

While this is correct, you might rather want to look at the percentage of users (unique visitors) achieving a certain goal in total (per user):

Number of unique goal achievements per user: 2 / Number of users: 3 = 67%.

Choose Wisely When Calculating Your Conversion Rate

43% vs 67% goal conversion rate - holy moly! Let us look at some use cases to better understand this correlation...

Use Case: SaaS Website

If

  • it takes many sessions for users to sign up on a SaaS website
  • but finally almost every user signs up

then

  • Google Analytics’ default goal conversion rate will be very low
  • whereas the user focussed conversion rate will be very high
Use Case II: Ecommerce Website

If

  • it takes only a few sessions for users to purchase a product on an ecommerce website
  • but hardly any user purchases the product

then

  • Google Analytics’ default goal conversion rate will be very low
  • and the user focused conversion rate will be equally low

Quo Vadis Conversion Rate?

As you could see, in some cases session and user based conversion rates match, in others they don’t.

You might say: “This isn’t very convincing, show me some realistic scenario!”. Right so. Let us do quick calculation. Let us say we have an online services business with one time subscriptions set as a goal (per month, on average):

  • 10000 users
  • 3 sessions per user
  • 2% of all users reach the goal at least once
  • 10% of all sessions reach the goal at least once

Google Analytics’ goal conversion rate in this case would be:

Number of unique goal achievements per sessions: 3000 / Number of sessions: 30000 = 10%

Interpretation: 10% of all sessions lead to a subscribe. Is this relevant in this case? Somewhat. It tells you that some users have subscribed more than one time. You might want to investigate why. Perhaps there is some error in the subscribe funnel?

A user oriented goal conversion rate instead would be:

Number of unique goal achievements per user: 200 / Number of users: 10000 = 2%

Interpretation: Every fiftieth user subscribed. This is very likely what you would be more interested in in this case. You would want to optimize your website so more users reaching the website subscribe.

You might ask: “What should I do?” The unsatisfying question is: it depends. You might want to ask yourself:

  • Is the goal something I want users (visitors) to do every time they visit?
  • Is the goal something I want many users (visitors) to do?

If you want to focus on the former, choose session goals and sessions (visits) as a measure, otherwise user goals and users (unique visitors).

Goals suitable for a session (visit) oriented view:

  • Services Usage
  • Logins
  • All ecommerce purchases

Goals suitable for a user (unique visitor) oriented view:

  • App downloads
  • Lead generation
  • Sign-Ups
  • First time ecommerce purchases (customer count)
  • A/B testing

Also keep in mind many analytics and optimization tools such as Heap, Optimizely and also Intempt use users as a base measure, not sessions. If you want to sync with these tools using Google Analytics, you might want to focus on users instead of sessions, depending on the context.

How To Create a User View In Google Analytics?

If you want to calculate user related data instead of looking at sessions in Google Analytics, it gets a bit tricky. First let us go to “Audience Overview” where you get to see sessions and users (I am using a real account here from one of our clients, so I’ve blurred data):

Audience Overview Google Analytics

Next, you would need to create a segment, based on your goal. If it is non ecommerce, you simply can create an advanced segment filtering out users who have completed the goal at least once:

Advanced Segment Goal Completion Per User Google Analytics

For ecommerce, you may alternatively use the buit-in segment “Sessions with Transactions”:

Built In Segment Sessions With Transactions Google Analytics

After you have enabled this filter, you may calculate the user based goal or transaction conversion rate:

Audience Overview Google Analytics With Applied Filter

What would the conversion rate be in this case? Let us use again the formula discussed above:

Number of unique goal achievements per user: 370 / Number of users: 31584 = 1.17%

Let us compare: In this case

  • The user focused conversion rate is 1.17%,
  • Google Analytics’ goal conversion rate is 0.97%
  • Google Analytics’ ecommerce conversion rate is 0.92%

So the user conversion is way better than it might appear at first glance.

How to Improve Your Conversion Rate?

After we discussed the conversion rate metric or KPI in detail, it is time to look at measures and technologies that help you to improve this metric and leverage your business.

Whether you are new to conversion rate optimization or a pro already, I bet you (at least sometimes) struggle with finding the right tools to do the job...this isn’t 2000 where only a few and very basic technologies were available to drive conversions.

In 2018 it is...complicated (to say the least):

marketing technology landscape 2018

Source

Marketing Strategies - the Crux of CRO?

Many marketers get overwhelmed when asked to pick the right tools for their business. So let us step back for a second and look at common strategies used for conversion rate optimization:

  • Split Testing
  • Recommendations
  • Abandoned Cart Notifications
  • Ratings and Reviews
  • Email Personalization
  • Chat / Click-to-Call
  • Automated Guides
  • Re-Targeting

No matter if you sell consumer services or products, there is certainly always room to improve your website / app so users are more likely convert.

Conversion Rate Optimization - Strategize First

Because conversion rate optimization is complex, it often helps me to systematically strategize first. I simply split the user flow into:

Positive aspects Negative aspects
Engage your visitors, e.g. create tempting call-to-actions Remove design hurdles and solve or overcome usability issues

...and think about strategies that could fit for my website. Let us sort the strategies outlined above accordingly:

Positive aspects Negative aspects
Split Testing Split Testing
Recommendations Abandoned Cart Notifications
Ratings and Reviews Chat / Click-to-Call
Email Personalization Automated Guides
Automated Guides Re-Targeting

If we look at the table closely, we may find some strategies match with both aspects, which is why they are more versatile when getting hands on the conversion rate optimization.

My general recommendation is to focus on these strategies instead of cosmetic changes or at least start incorporating them at an early stage.

While e.g. abandoned cart solutions might initially boost conversions and be easier to set up, they don’t help creating sustainable and long lasting assets that withstand the test of time (e.g. when your user base changes).

One sustainable conversion rate optimization strategy is to run split tests.

Your Swiss Army Knife For Conversion Rate Optimization: Split Testing?

Split testing is on the market for long. In fact, Google did their first A/B testing in 2000 aiming at finding out the optimum number of results to display on a page.

In case you are not familiar with the concept: A/B testing compares two variants of a single variable (e.g. “Does call-to-action A or B engage more people to convert?”). The testing helps you to adapt and redesign your website based on user preferences and variant performance.

Multivariate testing simply is an enhancement of this idea, allowing you to test more than two variants at the same time. Both A/B and multivariate testing are labelled “split testing” describing the general method behind this technology.

Benefits of Split Testing

There are numerous advantages split testing has over other marketing strategies and their related tools:

  • Flexibility: You may work on all aspects of your website: design, content or structural changes
  • Control: You may exactly control the testing and changes
  • Lift: You may create great conversion rate lifts through split testing
  • Insights: You may get valuable insights in how your visitor base behaves
  • Versatility: You may work on CRO positive and negative aspects for all kinds of businesses

Drawbacks of Split Testing

While I generally recommend to use split testing for any kind of business, there are some drawbacks:

  • Sample Size: You might not be able to reach statistical significance in case of low traffic.
  • Work Intensity: Tests may require involvement of other departments (Design,R&D) slowing down the workflow while increasing costs heavily.
  • Saturation Point: You may initially see a reasonable conversion lift when testing drastic variants. Minor changes however may not show statistical significance.
  • Missing Segmentation: Testing against your whole audience regardless of its user segments leads to broad results. Applied changes miss out user segments that would have converted better with other variants.
  • Missing ROI: As you progress, lower lifts and increased design work question the ROI.
  • Constant Testing: Tested data only applies to one test, you cannot reuse it. Test rounds must be planned thoroughly if the goal is to measure interactions between isolated elements.

Want To Go Beyond Split Testing?

Split testing helps you to get a broad direction on your market and your message. However, you are still optimizing with an ideal audience in mind instead of individual user flows.

What does that mean?

Because conversion rate optimization is complex, many marketers focus on the whole traffic and tend to forget about the big picture.

Optimize For Individual Users, Not For an Audience

User personalization means to put marketing back on its feet.

What matters most is giving the right response to a specific user at the right time. Not the audience you optimize for nor the tools you use should restrict this response, but rather where your user is at during the individual decision making process.

Let me explain this...

Who Are My Users?

The above question can be answered in a simple and a sophisticated way.

The usual perspective is to look at a generic website audience, meaning: “Who are my users - so I can deliver the best possible website to all of them?”

However, smart marketers are thinking differently: “Who are my users today - what do they need right now, in this moment?”

Segment Your Users Via a Personalization System

The central idea of a personalization system such as Intempt is to

  • Segment your users based on
    • Tracked website behaviour and
    • Third party data
  • Change your website individually in real time
  • Grow by increasing your conversion rate

The user data may come in from multiple sources:

  • CMS
  • CRM
  • Search engines
  • Email
  • Social
  • Retargeting

This system is equally flexible. You may address positive and negative CRO aspects:

  • Deliver engaging call-to-actions only to the right users
  • Deliver helpful messages if users struggle and are about to drop off
  • Change your website whenever a specific user shows up

Let me outline the advantages of a personalization system over a split testing system:

  • Sample Size: Even with low traffic you may create powerful user segmented campaigns.
  • Work Intensity: If you use on-site messages (see below) the required involvement of other team members is minimal.
  • Saturation Point: Precisely create as many behavioral campaigns as you like.
  • Segmented Users: You may precisely target specific user segments instead of your whole website audience.
  • Retrospective Database: You may always go back in time to understand your visitor behavior and create new campaigns from this database.
  • Predicted Campaigns: You may also predict your user’s next steps and take action using collected data from previous users (see below).

Let me show you how using a client use case.

User Personalization Use Cases: Kukun

Kukun Home Remodeling

One of our clients, Kukun, is an online services provider helping house owners to estimate their home remodeling projects, research best loan options, find professionals and much more.

Each of these services result in a separate conversion funnel, and almost every user has a specific objective:

  • Estimating the cost of a project
  • Seeking inspiration around home remodeling projects
  • Applying for a loan
  • Finding professionals in the neighborhood
  • Joining Kukun as a professional and get listed on the website
  • Contacting Kukun for a business cooperation

The Kukun website requires to guide users carefully. We do this by segmenting them based on intents they show via their behavior.

Kukun Behavioral Split Content Campaign

Kukun’s project estimator is a multi form tool that displays an estimate after users have entered all information on their project.

When users get to see their results, they are asked to calculate their project recoup:

Kukun Default Estimate Result

We aimed at displaying a different version of this page to users who previously showed intent in applying for a loan to drive conversions for this funnel.

These users - and only these users - should get to see a block element engaging them to apply for a loan:

Kukun Treated Behavioral Estimate Result

Intempt can dynamically override any existing page content. Except from the tracker installation no further IT involvement is required.

How did we get there?

Installing The Intempt Tracker

Before creating the campaign, we installed the Intempt tracker on Kukun’s website. The tracker is a code snippet similar to Google Analytics collecting each visitor’s behaviour.

Create a Behavioral Segment

We first defined a behavioral segment in Intempt matching our campaign goal:

  • The user reached the end of the estimator and
  • Browsed at least one loan related page before

Intempt Campaign Segment

Setting The Campaign Up

We copied the page element’s code from Kukun’s website and adapted it matching users interested in loans. This code then was added to the campaign.

Kukun Split Campaign View

Whenever all campaign conditions are met and a user is segmented, the Intempt server sends the adapted element to Kukun’s website.

Kukun Predictive Behavioral Campaign

For this campaign we aimed at displaying an engaging message to users who are predicted to not finish an estimate based on:

  • The actual user behaviour
  • All previously collected user behaviour data

to drive additional conversions for this funnel:

Predictive Campaign Intempt Kukun Message

How did we get there?

Create a Predictive Segment

We first defined a predictive segment in Intempt matching our campaign goal:

  • The user will very likely not begin an estimate

Kukun Intempt Predictive Segment

Setting The Campaign Up

We then created three variant texts to split test them:

Kukun Intempt Predictive Campaign View

These variants can be investigated later using Intempt’s campaign analytics:

Kukun Intempt Predictive Campaign Analytics

Optimize Conversion Rates Via User Personalization

Target visitors based on their behaviour across channels while you still retain full control over your campaign.

If you are struggling with long customer journeys and fragmented visitor segments, this approach can be your tool to drive conversions. Just be personal, in a smart way.

Want To Get Your Conversions Boosted?