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Last Updated: September 5, 2023

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 thousands of miles away from your desired destination. So the right beginning is as important as the journey itself.

In the case of conversion optimization, we take the first few right steps by following a process (which acts 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 Conversion.com

At Conversion.com 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 behavior 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 variation of the so-called “Bullseye Framework” for our optimization campaigns.

First, we spend some 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 occurs 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 a bounce rate higher than the 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 satisfies 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 suggests, there is no direct correlation between bounce rate and sales i.e. increasing or decreasing the bounce rate does not directly result in a 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 exists today and that is taught is old school, is about evaluating page designs (via series of A/B Tests, multivariate tests, heatmaps, etc) to improve business bottomline.

I would have loved to tell you that the 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 a 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 with 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 that 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 optimizing them.

Now I am not saying that you can never get results through random optimization. You can, especially if you are optimizing a low traffic website with clear winners (clear top 10 pages).

But…

• 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 don’t document the information, you will most likely forget half of the key information sooner or later, especially 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.

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#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. 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 the 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 a GAP analysis, you first need to know what the business is prioritizing.

If you start your analysis by visiting the website straight away, you are not 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 the 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 a 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 wants 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.

Of course, if you have got only one product/service to offer then you have got no choice. But for the 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 want to know the 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 the 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 be 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 reading this article.

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