One might find it odd to talk about not doing conversion rate optimization (CRO) when CRO is one of the most popular ways of increasing conversions for a web-based business. But as odd as it may sound:
CRO has always been the sub optimal way of optimizing your business performance.
Many analysts are familiar with the limitations of CRO and never really say or do CRO. But by and large, CRO is still considered the most effective way to increase the sales/revenue of a website.
In the next few minutes, I will convince you why CRO is a sub-optimal way of optimizing your business bottomline and why you should focus on Conversion Volume Optimization instead of Conversion Rate Optimization.
Note: Throughout this article, whenever I talk about the conversion rate, I am talking about the ecommerce conversion rate. But my suggestions are also equally valid for goal conversion rate.
The conversion rate is not that powerful.
Contrary to popular belief:
Conversion rate has weak positive correlation with revenue and zero correlation with cost and revenue is all that matters at the end of the day.
The conversion rate has little impact on optimizing revenue and absolutely no impact on optimizing cost.
The two metrics that actually drive revenue are: ‘average order value’ and the ‘number of transactions’.
The conversion rate, on the other hand, has a secondary impact on revenue because it doesn’t take into account ‘average order value’ in its calculation, and it is a ratio metric in which the increase in traffic (visits) always tends to lower the value of the conversion rate.
It is quite possible and common that…
Increase in conversion rate results in decrease in revenue
Decrease in conversion rate results in increase in revenue
Increase in conversion rate actually results in decrease in gross profit
Case 1: Negative Correlation between Conversion Rate and Average Order Value
Consider the following scenario:
From the table above, we can see that the revenue has decreased by 33% in the last month, even when the conversion rate has improved by 66% in the same period.
This happened because the average order value went down by 66%.
So increase in conversion rate did not result in an increase in revenue, and at the end of the day, all that really matters is revenue, esp. for a marketer.
Now look at the alternative scenario:
Here conversion rate has decreased by 40% in the last month, but the revenue has increased by 50%.
This happened because the average order value increased by 200%.
So decrease in conversion rate resulted in an increase in revenue.
Case 2: Negative Correlation between Conversion Rate and Transactions
Consider the following scenario:
We can see that the revenue went down by 30% in the last month even when the conversion rate improved by 16% in the same time period.
This happened because the number of transactions went down by 30%. So increase in conversion rate did not result in an increase in revenue.
Now look at the alternative scenario:
Here conversion rate decreased by 23% in the last month, but the revenue improved by 14% in the same time period.
This happened because the number of transactions increased by 14%. So decrease in conversion rate did not result in an increase in revenue.
Case 3: Positive Correlation between Conversion Rate and Acquisition Cost
Consider the following scenario:
Here the increase in conversion rate resulted in an increase in revenue by 16% in the last month.
But the cost of acquiring traffic also increased by 250%, eventually resulting in a decline in Gross profit by 19%.
This usually happens when we focus more on acquiring average/low-value customers than best customers.
All of the above case studies suggested that focusing on conversion rate is not the best way to optimize business and marketing performance.
We should rather focus on improving revenue and decreasing the cost per acquisition.
Other than these case studies, there are some other very strong reasons not to optimize for conversion rates:
#1 It is not very practical to optimize conversion rate as it is a ratio metric and you can’t set achievable numerical targets for it like improve the conversion rate of the website by 10% in the next 4 months.
You will always get some traffic which won’t convert, no matter what you do to improve user experience.
#3 Conversion rate calculations are horribly prone to errors and do not reflect effect size (i.e. signal) more accurately than conversion volumes. I have explained these issues in great detail in the article: What Matters more: Conversion Volume or Conversion Rate – Case Study.
Because of the secondary impact of the conversion rate on revenue and zero impact on the cost, it is no more important than a metric like bounce rate. Ok, a little bit more important than the bounce rate.
But just like you won’t measure the success or failure of your marketing efforts only on the basis of bounce rate, you won’t measure the success or failure of your marketing efforts only on the basis of conversion rate.
In order to truly optimize revenue, you need to focus on increasing average order value and number of transactions for each of your market segments, product categories, and other portfolios of outcomes.
So next time you conduct a test to optimize your business performance, focus on how the change impacts the average order value, transaction volume, and acquisition cost.
Don’t be fooled by the misleading conversion rate metric.
When you say you do CRO, you imply that all of your marketing efforts are conversion rate centric. You imply that all you care about is increasing the conversion rate.
In order to get optimum results from your marketing efforts, you need to focus on the metrics that really matter, i.e. revenue and cost.
And when you change your focus from conversion rate to more useful metrics like revenue and cost, you are no longer doing CRO as your marketing efforts are no longer conversion rate centric.
You can’t really optimize the conversion rate.
As odd as it may sound, you can’t really optimize the conversion rate. Yet millions of blog posts are out there teaching you CRO every breathing minute.
The following are two simple reasons:
1. Web analytics tools like Google Analytics puts each and every visit to your website in the conversion funnel while computing conversion rates.
Not every visit leads to conversion, yet the formula for calculating the conversion rate is: the number of transactions/total visits.
Now the question that arises is, can you really optimize each and every visit on your website for conversion?
The answer is: you can’t.
You will always get some traffic which won’t convert no matter what.
2. Now, let us assume that you calculate the conversion rate differently.
Instead of taking visits into account, you take visitors into account.
So your formula for calculating the conversion rateis now: number of transactions/total visitors.
Now the question that arises is, can you really optimize each and every visitor of your website for conversion?
The answer is: you can’t.
You will always get some visitors who won’t convert, no matter what.
These visitors can be people like job seekers, competitors, link builders or people who are just on your website for a reason other than completing a goal conversion or placing an order.
Other than these two simple reasons:
The conversion rate metric is innately prone to errors simply because it is a ratio metric.
The ever-increasing traffic on your website will always tend to lower the conversion rate.
Since conversion rate is a ratio metric, you can’t set achievable targets for it with any ease, like increasing the conversion rate by 5% in the next 6 months.
Conversion rates are horribly prone to misinterpretation.
You don’t get what you see in the case of conversion rate.
Conversion volume optimization (CVO) is a web analytics term coined by yours truly in 2012 which focuses on optimizing conversion volumes of a marketing channel rather than the conversion rates.
While the rest of the world is busy optimizing conversion rates (which you can’t optimize anyways), I am more focused on optimizing conversion volumes and suggest you do the same.
280% Improvement in Conversion Rate
Does that sound familiar?
Q1. Do you have any idea how this 280% increase in conversion rate impacted the business bottomline? Is the company that experienced such an uplift now a multi-billion dollar enterprise, or are they still struggling to pay their utility bills?
Q2. Is this a Goal conversion rate or an ecommerce conversion rate?
Q3. Is this conversion rate in aggregated form or segmented?
Q4. How was this conversion rate calculated? Using sessions, unique visitors, by spending 280% more on marketing campaigns….
Q5. When was this conversion rate calculated? peak session, off-peak season, during the aggressive sales campaign, during a rapid decline in traffic…..
With so many questions to answer, it is hard to measure the performance of service providers who advertise their success in the form of conversion rate improvement.
Issues with Conversion Rate Optimization (CRO)
I have discovered the following issues with the traditional CRO approach:
Data Collection Issues
Data Interpretation Issues
Data Reporting Issues
Data Optimization Issues
#1 Data Collection Issues.
The manner in which web analytics tools like Google Analytics collects conversion rate data is misleading and downright wrong.
For example, as mentioned earlier:
#1 Google Analytics add the Goal conversion rate of each individual Goal and then report the sum as the overall Goal conversion rate of the website.
So if you have set up 5 goals for your website and the conversion rate of each goal turned out to be 20%, then Google Analytics will report a 100% conversion rate for your website.
#2 Google Analytics puts every visit to your site in the conversion funnel while computing goal and ecommerce conversion rates.
But this is never really the case. Not every visit leads to conversion.
So following traditional definitions of conversion rates are downright misleading and incorrect:
Goal Conversion Rate = Total Goal Completions/Total visits to the website
E-Commerce Conversion Rate = Total e-commerce transactions/total visits to the website
#3 There are many ways of calculating conversion rate metrics.
You can calculate it by using: total website sessions, website sessions only from the target market, unique sessions, users or unique users as denominators.
Consequently, you can come up with different conversion rate values for the same website goal.
#4 When (i.e. period or event) the conversion rate was calculated can also greatly impact its value.
For example value of the conversion rate varies when calculated in the peak season, off-peak season, during aggressive sales campaigns, during major news about the business, and during rapid decline or increase in website traffic.
Consequently, you can have different conversion rate values for the same website goal.
There are ways (data segmentation) to get around these issues, but it is still a pain in the butt.
On the other hand, conversion volume has no such data collection issues.
You get what you see.
If Google has reported 455 conversions through Google organic search, then you have really got that many conversions through organic search.
Get my best selling books on Attribution Modelling
Learn to implement attribution modelling in your organisation
Understand the customer purchase journey across devices
Determine the most effective marketing channels for investment
Click book covers to find out more
#2 Data Interpretation Issues
Since conversion rates calculated by analytics tools like Google Analytics do not represent the true conversion rate of a marketing channel, it is very easy to misinterpret them (unless you are a data segmentation junkie).
Another factor which contributes towards the misinterpretation of conversion rate data is its ‘ratio metrics’ nature.
Ratio metrics are the metrics which are computed as ratios.
For example, Bounce Rate is a ratio metric as it is computed as the number of bounces/number of entrances.
So what is the issue with ratio metrics?
Ratio metrics provide muddy analytical insight and can, therefore, horribly mislead you.
For example, consider the following scenario:
Your transaction volume has increased by more than 7800% in the last 5 months, but since the focus is on e-commerce conversion rate, there is virtually no improvement (flat 0.5% conversion rate as reported by Google Analytics, unless off course, you bother to segment the data).
Consider another scenario:
Your transaction volume has increased by more than 19,900% in the last 8th months, but since the focus is optimizing on e-commerce conversion rate, there has been a sharp decline.
Since conversion volume is a ‘number metric’, you can never misinterpret it. 300 conversions mean 300 conversions.
It is as simple as that.
#3 Data Reporting Issues
When you report conversion rates in aggregate forms, like 0.5%, your client has no idea what does that means.
Is it 5 conversions out of 1000 visits or 50 conversions out of 10000 visits?
Whether we are making any progress, and how can this progress be translated into monetary form?
Since ratio metrics like conversion rate provide a muddy analytical insight, they can’t effectively communicate your marketing efforts to senior management/clients.
Businesses understand numbers more than ratios.
This is because numbers mean money ££££ and if you can’t show them the money, you will have a hard time getting anything done in SEO, PPC or any form of marketing.
Your client will be happier if you tell him that number of orders on the website has doubled in the last 3 months than reporting to him something like, your site e-commerce conversion rate has improved by 0.431% in the last 3 months.
Even if you report the ratio, your client still needs to know the impact on the bottomline in the form of the ‘number of orders’.
Conversion volume is a number, and it communicates really well.
Any person, regardless of his background, can easily understand that when his website got 300 orders in the first month and 410 orders in the second month, his online business is making progress.
#4 Data Optimization Issues
It is not very practical to optimize conversion rate since it is a ratio metrics.
You can’t set achievable targets for conversion rate, like improving the e-commerce conversion rate of the website by 1% in the next 6 months.
This is because:
1. You can’t lead every visit and/or visitor to your website to convert, no matter what you do.
2. You will always get some/lot of traffic which won’t convert, no matter what you do.
3. Your website traffic will always increase (ideally, it should) and it won’t always increase in proportion to conversion volume.
4. Any person working in the marketing field long enough knows what one 1% increase in the conversion rate can do to your business bottomline, esp. at the enterprise level. It can be a difference between making £1 million and £10 million.
Conversion volume, on the other hand, has no such data optimization issues.
Since conversion volume is a number, you can easily set numerical targets for it.
For example, we aim to get at least 500 orders in the next 6 months.
We aim to generate at least £50k a month in revenue in the next 6 months.
“Conversion Volume is the total number of conversions or total monetary value of conversions in a given time period.
A conversion can be a macro conversion like transactions, revenue, leads etc. and/or it can be a micro conversion like the number of newsletter signups, file downloads etc.”
In Google Analytics, conversion volume is called ‘Goal Completions’.
In Google Analytics standard reports, you won’t see the conversion volume as you would like for each traffic source.
So you need to create a custom report which lists conversion volume (aka Goal Completions) for each traffic source:
Here I have created a custom report and then view the data in the pivot table.
No. I am not saying to discard the conversion rate metrics.
Conversion rate is a good indicator of the quality of traffic to your website and determines website issues.
If you really want to use this metric, use, report and analyze conversion rates in analytics nerd style, in segmented form and with conversion volume, not as a standalone metric.
So the smart questions to ask now are:
1. How many orders have I got through Google organic search in the last month, and how much conversion rate conversion volume has improved?
2. How many leads have I gotten through email campaigns in the last month, and how much has conversion volume improved?
3. How many orders should we aim for in the next 6 months?
In the end, conversion volume matters the most to a business because it speaks the universal language (the language of money) loud and clear.
Other articles on Maths and Stats in Web Analytics
"How to use Digital Analytics to generate floods of new Sales and Customers without spending years figuring everything out on your own."
Here’s what we’re going to cover in this training…
#1 Why digital analytics is the key to online business success.
#2 The number 1 reason why most marketers are not able to scale their advertising and maximize sales.
#3 Why Google and Facebook ads don’t work for most businesses & how to make them work.
#4 Why you won’t get any competitive advantage in the marketplace just by knowing Google Analytics.
#5 The number 1 reason why conversion optimization is not working for your business.
#6 How to advertise on any marketing platform for FREE with an unlimited budget.
#7 How to learn and master digital analytics and conversion optimization in record time.
My best selling books on Digital Analytics and Conversion Optimization
Maths and Stats for Web Analytics and Conversion Optimization
This expert guide will teach you how to leverage the knowledge of maths and statistics in order to accurately interpret data and take actions, which can quickly improve the bottom-line of your online business.
Master the Essentials of Email Marketing Analytics
This book focuses solely on the ‘analytics’ that power your email marketing optimization program and will help you dramatically reduce your cost per acquisition and increase marketing ROI by tracking the performance of the various KPIs and metrics used for email marketing.
Attribution Modelling in Google Analytics and BeyondSECOND EDITION OUT NOW!
Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.
Attribution Modelling in Google Ads and Facebook
This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.
About the Author
Himanshu Sharma
Founder, OptimizeSmart.com
Over 15 years of experience in digital analytics and marketing
Author of four best-selling books on digital analytics and conversion optimization
Nominated for Digital Analytics Association Awards for Excellence
Runs one of the most popular blogs in the world on digital analytics
Consultant to countless small and big businesses over the decade
Get My Step-By-Step Blueprint For Finding The Best KPIs (32 pages ebook)
We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of all the cookies.
This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
Cookie
Duration
Description
cookielawinfo-checkbox-analytics
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional
11 months
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance
11 months
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy
11 months
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.