How to Start Conversion Optimization like a Pro

There is a famous quote from Chinese philosopher Laozi: “A journey of a thousand miles begins with a single step”. 

But what if your first few steps take you in the wrong direction?

Well in that case, you may end up thousand of miles away from your desired destination.

So right beginning is as important as the journey itself.

In case of conversion optimization, we take the first few right steps by following a process (which act as a roadmap).

The process you follow must be well defined and it must have a clear start and a clear end.

Without a well defined process in place, you will end up doing what I call ‘Random Optimization’.

Let us first start with industry experts and learn, how do they start the conversion optimization process.

Q. How do you start conversion optimization? What processes and framework do you follow?

Tim Ash (author of the bestselling book Landing Page Optimization, CEO of SiteTuners and & Chair of Conversion Conference):

” You have to start with a deep understanding of your audience. As online marketers we are often focused on the internal needs and goals of our business. But from the outside-in, the perspective is a lot more messy and complicated.

You have to understand the confusion, lack of knowledge and irrational nature of how your audience behaves. From this starting point you can design appropriate web experiences and properly motivate them to act.”

Stephen Pavlovich is the CEO at

At we take a strategic approach to conversion optimization. First, we need to understand the goals we’re looking to achieve and the KPIs that track them. Second, we need to gather and analyse data and insight – specifically, we’re looking to identify the motivations, abilities and triggers that drive them (using BJ Fogg’s behaivour model).

Third, we develop the strategy – and this will depend on the capacity for testing. eg for a company with high resources and a high traffic website, we’ll use a more exploratory approach to testing, whereas with a low traffic website, we’ll need to be more selective in the tests we run. Finally, we run and analyse the tests.

Csaba Zajdó CEO at OptiMonk

We use a variaton of the so-called “Bullseye Framework” for our optimization campaigns.

First we spend sime time checking and reviewing our data and our metrics, then we brainstorm ideas about potential optimization targets.

Q How do you decide what to test first and when?

Tim Ash: 

Prioritizing testing depends on the importance of the pages being optimized (the traffic sources, number of conversions, and the economic value), the availability of enough steady traffic, the difficulty of creating and implementing the test, as well as political considerations and the support needed inside of the company.

Stephen Pavlovich: 

Good question! A simple approach is to rank tests by impact and ease, meaning you can run the high-impact high-ease tests first. The problem with this, of course, that you don’t know which tests are going to be high impact – and certainly not at the start of a project. Instead, we look to see which customer objections are the most prominent – at its simplest, what is stopping visitors from converting? Then we look to see the most impactful way of fixing that objection. This is normally the most impactful place to start – but the right creative may take a few iterations to get right.

Csaba Zajdó: 

We rank these ideas according to their “ROI-potential”: we rate the potential win on a scale of 1 to 10, then we make a rough estimation about the execution costs (again a scale of 1 to 10, 10 being the easiest, less than one hour type of tasks, 1 being the most difficult, several month projects). We add these two values, and rank the ideas accordingly. We choose the top 3, with the highest estimated ROI-potential.

Q How do you validate your A/B test results?

Tim Ash: 

The test is the validation. In other words, if you run it properly you should be very sure that you have found something that performs better.

After that it is simply a matter of continuing to run with the winning version that you have uncovered. Some companies also keep the original version running continuously and show it to a small percentage of the visitors. This is a sort of insurance policy to ensure that the winning version continues to outperform the original over time.

Stephen Pavlovich:

At Conversion, we use a proprietary model for statistical analysis. You can, of course, use a system like Optimizely’s Stats Engine, or an approach that uses a combination of statistical significance, test duration and number of conversions.

Csaba Zajdó:  

We use Optimizely and Google Analytics for our tests, depending on the type of test we want to accomplish. We evaluate the results every two weeks for the smaller tests, or every second day for the larger ones.


Now some tips from yours truly:

#1 Avoid ‘Random optimization’

Random optimization occurs when you optimize a website without any clear objective.

You identify problems (based on some industry best practices) and then you rush to fix them in a hope that it will somehow improve the business bottomline.

Random optimization also occur when every second or third day you ask yourself this question “What should I do next?”.

For example, starting your analysis by looking at the ‘All Pages’ report or ‘Landing Pages’ report is random optimization.

Let us wait and see what will happen if we somehow reduce the bounce rate of top landing pages.

If a web page has got bounce rate higher than website average than surely it must be repulsive to users and need fixing.

Bounce rate is a tricky metric.

It can suggest many things:

1) Your web page does not satisfy users’ query hence people bounce from the landing page.

2) Your web page fully satisfy users’ query and there is no reason to browse the website any further.

3) You are not getting the right users to your landing pages. There is nothing wrong with your landing pages, the traffic that is coming is not relevant.

So is high bounce rate good or bad?

There is no single right or wrong answer.

It depends upon how you interpret the data.


But no matter what bounce rate suggest, there is no direct correlation between bounce rate and sales i.e. increasing or decreasing the bounce rate does not directly result in corresponding increase or decrease in sales.

So there is no guarantee that optimizing the bounce rate is going to improve the business bottomline.

The chances of improvement are as good as flipping a coin and expecting ‘head’.

Much of the conversion optimization that exist today and that is taught is old school, is about evaluating page designs (via series of A/B Tests, multi variate tests, heatmaps etc) to improve business bottomline.

I would have loved to tell you that A/B test is the miracle cure to all of your conversion problems.

But the reality is that, it is not.

You need to do lot more than evaluate page design to improve the business bottomline.

I have nothing against A/B test or conversion rate as such.

But I am not obsessed about them either.

For me, as an analyst, A/B test is just another tool.

It has its own place and is helpful in certain situations.

But if you are starting your optimization journey by evaluating page designs and running series of A/B test then you won’t get optimal results and may even end up wasting your time and resources.

The websites I handle are usually high traffic websites (millions of monthly sessions) and they have got tens of thousands of web pages.

There are hundreds of web pages which get thousand of sessions each and near identical traffic volume.

So if I start my optimization process by optimizing the performance of top pages (in terms of traffic), I will forever be optimising them.

Now I am not saying that you can never get results through random optimization.

You can esp. if you are optimizing a low traffic website with clear winners (clear top 10 pages).


  • Will you get results?
  • When you will see your results?
  • What kind and magnitude of results you will see?
  • How long it will take to get results?

The answers to all of these questions will remain as random as the ‘random optimization’ itself, if you choose not to follow a formalized process.

#2 Determine what the business is prioritizing

You get the answer to this question through the people who actually run the business and not from Google Analytics reports or the website itself.

Consequently when you are starting out, you need to interview your client.

Ask questions, tons of questions related to:

  • business objectives
  • current marketing activities
  • Pain points (like satisfaction with the current website, marketing campaigns etc)
  • Products
  • Target Audience
  • Competitors
  • SWOT (Strength, Weaknesses, Opportunities, Threats)

Document all the important information provided to you.

Documentation is very important.

If you won’t document the information, you are most likely to forget half of the key information sooner or later esp. if you are handling many projects.

You can ask questions through Skype, Phone, email or one to one meetings.

The important thing here is that you ask questions and not just once but throughout the duration of the project.

I can guarantee that you will learn much more and much faster by asking questions than trying to figure out everything on your own via Google Analytics.

It is only by asking questions that you can truly embrace Agile Analytics methodologies.

#3 Determine what is being prioritized on the website and via campaigns

We often start our optimization process by visiting the client’s website under the assumption that the website accurately reflects business needs and wants or what the business is prioritizing.

But this not always the case.

So for example if a business wants to grow blog subscribers but the blog link is not even in the top navigation menu of their website, it tells you of a gap between what the business is prioritizing and what is being prioritized on the website.

Similarly if the business is keen to improve website sales but majority of marketing campaigns are traffic driven instead of conversion driven, it tells you of a gap between what the business is prioritizing and what is being prioritized via campaigns.

In order to do such GAP Analysis, you first need to know what the business is prioritizing.

If you start your analysis by visiting the website straighaway, you would not be able to leverage the benefits of GAP analysis (which to be honest is a secret weapon of the analytics pros).

#4 Determine what the target market is prioritizing

We often do market research under the assumption that what business is prioritizing, is being prioritized by their target audience.

What business is selling is exactly what the target market wants.

But this is not always the case.

For example, a business may be keen to sell Product X, but its target market may not be interested in buying it.

In such situations when large amount of money is spent on pushing the sales of Product X, it results in high cost per acquisition.

If there is no alignment between what the business want and what the market needs, then there will be little to no sales.

Whenever there is such conflict of interest, you should always prioritize the needs of the target market.

What that means is, you sell what is selling, what is in demand and not waste your time and resources to try to sell something which has no demand or try to create a market where the market doesn’t exist.

Off course if you have got only one product/service to offer than you have got no choice.

But for vast majority of online retailers this is not the case.

You have got the opportunity to focus, only on selling the top revenue generating products.

Improving the sales of all of the products should never be your top priority.

You can do target market research through Google Analytics, Omniture, Surveys, Feedback etc.

#5 Do GAP Analysis

GAP Analysis is carried out to find gaps between what the business is prioritizing, what is being prioritized on the website and what the customers are prioritizing.

The output of GAP analysis is what we call “Conversion Issues“.

For example if your customers wants to know shipping cost upfront to make an informed buying decision and the shipping cost is not disclosed on the website until the checkout then this is the gap you need to identify and close to improve the business bottomline.

Similarly, if you advertised throughout the UK but majority of buyers come only from London, then there is a gap between where you are spending your money and where the money should actually being spent.

You need to identify and close such gaps.

Following is the process I follow to do GAP Analysis in Google Analytics:

#1 Find Top Selling Locations – drill down to city level
#2 Find Top Selling Product Categories
#3 Find Top Selling Products
#4 Find Top Traffic Sources
#5 Find the Top Landing Pages for conversion funnel analysis
#6 Find the Top performing keywords (optional)

I have explained all of these data drill downs in great detail in the article: 6 data drill downs for improving Ecommerce Products Sales.

So instead of just repeating everything all over again, I would suggest to read this article.

Other article you will find useful: Using Cohort Analysis & Enhanced ecommerce to understand users behavior


Do you know the difference between Web Analytics and Google Analytics?

99.99% of course creators themselves don’t know the difference between Web analytics, Google Analytics (GA) and Google Tag Manager (GTM).

So they are teaching GA and GTM in the name of teaching Web analytics.

They just copy each other. Monkey see, monkey do.

But Web analytics is not about GA, GTM.

It is about analyzing and interpreting data, setting up goals, strategies and KPIs.

It’s about creating strategic roadmap for your business.

Web Analytics is the core skill. Google Analytics is just a tool used to implement ‘Web Analytics’.

You can also implement ‘Web analytics’ via other tools like ‘adobe analytics’, ‘kissmetrics’ etc.

Using Google Analytics without the good understanding of ‘Web analytics’ is like driving around in a car, in a big city without understanding the traffic rules and road signs.

You are either likely to end up somewhere other than your destination or you get involved in an accident.

You learn data analysis and interpretation from Web analytics and not from Google Analytics.

The direction in which your analysis will move, will determine the direction in which your marketing campaigns and eventually your company will move to get the highest possible return on investment.

You get that direction from ‘Web analytics’ and not from ‘Google Analytics’.

You learn to set up KPIs, strategies and measurement framework for your business from ‘Web analytics’ and not from ‘Google Analytics’.

So if you are taking a course only on 'Google Analytics’, you are learning to use one of the tools of ‘Web analytics’. You are not learning the ‘Web analytics’ itself.

Since any person can learn to use Google Analytics in couple of weeks, you do no get any competitive advantage in the marketplace just by knowing GA.

You need to know lot more than GA in order to work in Web analytics and marketing field.

So what I have done, if you are interested, is I have put together a completely free training that will teach you exactly how I have been able to leverage web/digital analytics to generate floods of news sales and customers and how you can literally copy what I have done to get similar results.

Here what You'll Learn On This FREE Web Class!

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 Beyond
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.

Himanshu Sharma

Digital Marketing Consultant and Founder of

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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