Optimize your conversion rate: an achievable goal!

You know what's unfortunate?

Only one fifth of companies are happy with their conversion rate.

A fifth!

That's why even the most savvy businesses are turning to incorporating conversion rate optimization (CRO) into their digital marketing strategy.

However, conversion rate optimization can sometimes be misleading.

"Converting" doesn't just mean making a sale. Having a good conversion rate can mean all sorts of measurables. Unless you clearly define what you expect as "conversion", you will not achieve your goal.

Here's the bottom line: if you want to have a better conversion rate, you need to learn how to better articulate your customer experience to get people to take the desired action.

In order to succeed as a digital marketer, you need to be able to optimize your marketing throughout your evolution, making small changes that improve returns by 1% to 10% or more.

In this article, we will help you to achieve it. We will discuss the optimization methodology, a procedure you can repeat to improve the results on your website. We will also talk about the jargon you need to know as an optimizer, the statistical data you need to take as well as the roles within your organization in order to identify who is responsible.

Let's start with some basics...

The main goal of optimization is to improve conversion rates based on the traffic you already have and generally with the assets at your disposal.

We are not going to deal with the topic "how to gain website traffic", but rather how to optimize your current traffic.

It is also important to know that optimization is a dedicated operation that you can reproduce. It is not a one-time activity. You will work through the process and then do it again. Because you can always improve your results, no matter how much you improve, you can keep going.

This is why we describe the CRO process as a cycle:

You will start by setting your objectives. You will collect the relevant data, then analyze it to come up with a hypothesis. You will design the variants, implement the technology and test your hypothesis. Then you will analyze the results, so that you can come up with new designs and ideas for new tests.

After that, the process just starts all over again. With optimization and testing, this cycle repeats itself permanently. At least if you do it right.

Now let's discuss what you will do at each stage of the cycle.

A clearly defined goal is the beginning of the operation. You need to remember that you can't optimize anything without clear goals. You must be able to understand what you want to achieve.

Let's assume that you are going to try to optimize your homepage. We will take the Digital Marketer homepage as an example.

Keep in mind, however, that optimizing landing pages is far from easy because of the many tasks that need to be done and the fact that everyone wants to emphasize their own goals. The sales team is doing everything they can to find new prospects. On the other hand, the acquisition team is studying the best strategy to convert traffic into emails.

You get the idea. Everyone is working to get a little space on the home page.

So here's the goal: a homepage allows you to tell visitors "you are here". This interface allows them to provide feedback on the relevance of your business, and if so, they can specify where they are and where they should go.

A definition of one or more of the following three types of objectives is essential to optimize this operation:

• A short-term goal, such as a click or the execution of a form on a page.
• A campaign goal, such as leads generated or purchases.
• A long-term goal, such as your long-term cost impact, net income, average order cost or lead quality.

Once you have identified your goal, you need to set a baseline for your statistics. For each measure, enter your current data, your potential data (the numbers you are targeting) and your user data.

Once you have defined your goal, you need to provide a baseline for your statistics. For each, attach your current numbers, the numbers you covet (the ones you're aiming for) and your user data.

Consolidate this data before making any assumptions.

For optimizers, this is rule #1: leave all assumptions aside. You and your colleagues all have ideas about what works well and not so well, user expectations and more. But these ideas are still assumptions.

You should never make decisions based on assumptions. Examine your designs and let your users give you feedback on what doesn't work.

So where do you collect your data from?

• For the statistics of your site, go to Google Analytics.
• For statistics on user behavior, you can use a tool like TruConversion.
• For customer and email information, use the information provided by your email service like MailChimp.
• For payment information, take a look at your payment platform such as Stripe, Paypal, etc.

The secret to CRO success is using the right data (that you just collected) to launch relevant optimization campaigns.

Analyze your data and ask yourself questions like these:

• What is my conversion rate (and is it satisfactory?) Use analytics or CRM data to get answers.
• What is weakening my conversion rate? Use user behavior data to figure it out.
• How or why does this negatively impact my conversion rate? To answer this question, you will take the next step in the CRO process and develop a hypothesis.

This is the starting point for optimization.

Without any assumptions, you cannot optimize because you have no idea what you need to improve.

At this point in the process, you know all the things that can hurt your conversion rates. Now you need to make assumptions about the method you will use to solve the problem you have identified.

How will you establish a hypothesis?

It's a simple procedure, you just have to include these 3 elements:

• The innovation or approach you plan to test.
• Who do you intend to target with this innovation?
• Your expectation of results.

The format should look like this:
We imagine that doing [1 ] for [2 ] will make [3] happen.

Your hypothesis must relate to your intent. You need to be very methodical about the outcome you expect. You also need to make sure that it is a measurable result that you can improve in a particular way.

Your new hypothesis will be used alongside your data to obtain the variations you will test.

Remember that tests take time, both to create and to execute.

As the number of tests to run on a site is unlimited, but in case your site generates only a small amount of traffic, you should limit the number of tests you will run. The execution of a test as well as the obtaining of the results is longer if your site is small.

In this case, if you have a low-traffic site, make sure you don't run more than about 30 tests per year.

This implies that you need to choose the best tests to run. You will need to improve your identification skills in order to justify the page you intend to optimize.

If you have done a simple review and everything is working as it should, it will take between 9 and 11 days to go live. However, when an obstacle arises, you should be prepared for technical and other issues that may extend the time by a few days.

Let's move on to how this might play out in real-world cases.

This test is easy. It requires only a few minor changes, which means it can be set up quickly. It is not very revealing, however, and even less scalable. What you can learn from this test will not have a significant effect on the other tests.

Since this is a big change, it takes a lot longer to set up and start. However, this procedure teaches you more and your results can be used on other pages, so it is scalable.

Insider's tip: For a complex test like this, you'll need to build a mockup, then build it in a landing page builder. Once your variant has been tested and validated, you'll need to upgrade it for all equivalent offers so that the results of your test can be used on all associated pages. In this case, it will take about a month to complete.

As soon as you create your variant, you must add all the technology needed to make the changes you are testing.

You can't do this without the right technology. You need some tools like Visual Website Otpimizer, Google Analytics and Truconversion.

It is also important to determine the right time to do or not to do a test. To do this, you must qualify your test.

First, ask yourself: can you do the test?

Each test should be run until it reaches statistical significance. Otherwise, your test results will not be reliable. The time it takes to achieve statistical relevance depends on the amount of variants you test and the number of conversions you process daily.

What is "statistical significance"? It is the mathematical proof of the reliability of your results. If you stop your test early, your test will not generate enough information to test the reliability of your hypothesis. If you spent more time on your test, this case should not arise, as the numbers would have proven it.

It's harder to get statistical relevance if you don't have much traffic. Without traffic, you won't have enough data.

Once you have set up your test, if you notice any signs of an anomaly or failure, you can stop the test.

If, for example, you get results on the first day, there is a problem. Suspend the test and identify the problem. If on day 12, the numbers are still below 80%, the test is not working. You need a realistic approach to find the right measure.

As a CRO, your goal is to mitigate risk while testing innovative ideas. In this case, if a test has a malfunction and the traffic source is organic, you can still run it. If it is a paid traffic source, the longer the test, the more money you will lose. So you should think about ending it sooner.

Here are the questions you need to ask yourself to determine if you should be tested:

• Is it a functional problem with a clear solution? If it is simply a functional problem, you give up testing.
• Does this page have a direct impact on the long-term goal or campaign? If so, conduct the test.
• Are there other testing options that can have a greater impact? If so, turn to this option.
• Can these instructions be applied to other parts of the site? If not, proceed with caution. You will get more value from a test that has a real effect on several pages of your site than from a test that only gives you one thing.
• Can I run the test (or the option that works) over a reasonable period of time? Without any resources to run the test or add a working option, you'd better give up to avoid wasting time.

At the end of the test, you should move on to analyze the results. This allows you to answer the "why" and inform your next test.

During this step of the process, you will perform 5 important tasks:

• Sharing increases or losses
• Defining the "why
• Write a report
• Store your data
• Share results with stakeholders

In the report, you will need to insert the test title, timeline, statistics, options and analyze the long numbers. Then move on to what you learned about the test and what decisions you need to make as a result.

During your analysis, you should ask yourself:

• Did you have a profit, loss or zero result?
• If the results are the opposite of your hypothesis, why?
• Is it necessary to retest? Is there any possibility of unusual facts about the test that may make the results questionable?
• How can you leverage the data in other experiments?

Now, use these results to determine your new goals and start the process again.

As mentioned above, testing and optimization is supposed to be a routine procedure for your marketing plan. Each test should lead you to another, and each small change will bring you considerable growth.

You need to know these terms in order to talk about conversion rate optimization in a meaningful way.

Conversion
The visitor's action that you intend to improve with the campaign (e.g., signing up for a webinar, adding a product to the cart, etc.) You need to determine your conversion actions. Clearly define what you are testing, your target and the most important statistic in evaluating your results.

Control
The page in the test that is not part of the test. In conversion tests, the control is the page that is currently converting better. Each new variation is tested against the control.

So in an A/B test, A is the control. The version of your test, or variation (see above) is therefore B.

Variation
The target page on which you performed the test. For example, the variation page should be more advanced compared to the control page.

Insider's tip: name your variants in the test to make it easier to identify each key element.

Here's what it should look like:

• Control - full form
• Variant 1 - shortened form
• Variant 2 - email only
• Variant 3 - form + analysis

Quantitative data
This is data that can be quantified numerically. The "objects of calculation", such as :

• Unique visits
• Registration
• Purchasing
• Amount of the order

Qualitative data
This is descriptive data. People's opinions" are difficult to study, but most of the time lead to a circumstance that allows you to obtain quantitative data. This includes:

• Activity Mapping
• Session recording
• Analysis forms

To evaluate
The life of an optimizer is all about numbers. So what are the most important numbers when you are doing a test?

Conversion rate
The conversion rate is calculated by dividing the number of conversions (without choice exceptions) by the total number of visitors on your test page.

Percentage increase
The rate of change between two variants (it is not the difference between two numbers). To calculate the percentage increase, here is the formula to use: In this case, if the difference is 1%, the rate of increase is 10%.

Confidence rate
Technically, it refers to: "The percentage of instances in which a set of identically established tests will capture the concrete (accurate) mean of the system under test within a stated range of values around the accurate value measure of each test."

Simply put, you are trying to prevent false positives. Therefore, the confidence percentage shows how confident you can be that your test is accurate.

For example, let's say your confidence percentage is 95%. This proves that if you were to run your campaign 100 times, the 95 tests you ran would result in decisive variations.

It is a common mistake to interpret this as a "chance" when you get the same results. As if the 95% confidence level means that you have a 95% chance of getting the same results with another test.

Here, there is no room for chance. We calculate the accuracy. You may notice small dissimilarities in each test. The percentage confidence means that you can see the difference, but not the degree of difference.

Conversion interval

"Conversion rate" is a misnomer. It gives you the impression that your tests are giving you an exact number that you can call a "conversion rate".

In practical terms, be prepared to get conversions in a range that is not at all accurate. For a range of 30.86% to 36.38%, you will get an average of 33.59%.

Be aware that the two tests overlap slightly. Your goal is to break the overlap so that you get a decisive variant.

Here are the 3 roles that are generally entrusted with the mission of optimization and testing.

Acquisition
The person dealing with the acquisition of new leads and customers should find the best way for optimization to get more conversions.
Despite the fact that this role does not directly deal with optimization, they should be able to define if the expected results are lower than expected or if there are problems on the page.

Marketing
A marketing professional must be able to see the strategy behind conversion rate optimization at every stage of the process.

He must know the sources of the optimization (at least) in order to be able to determine the origin of possible problems, whether they are related to the optimization, the acquisition or the qualification.

IT/Web Developer or Designer
Most of the time, conversion rate optimization includes technical elements that require assistance from the technical team members in charge of creating the web pages.

You need to make sure that these people are aware of your testing. There will be times when the designer will not share your opinions on the solutions you wanted to provide, and this helps them understand what they are creating and why.

Also, if you use optimization tools that allow you to make the changes yourself, notify everyone involved in your test. Otherwise, they will realize the changes on the website and wonder why the "validated" language or design was changed.

If you don't want to be one of the marketers who are disappointed with their conversion rates, you need to find another method of approaching digital marketing.

You don't have to just improvise and wait for results.

The only way to improve your conversion rates is to run the test and optimize.

This is not a one-time activity. It must be integrated into your company's culture if you are serious about growing your business.