Using A/B testing to evaluate the effectiveness of web pages

Creating any Internet resource involves preparing such landing pages that would show the highest practical effectiveness, attract the attention of the user audience and ensure high conversion rates. This is what will guarantee the profitability of your project, its relevance, stability of work and long-term demand in the market. In order to avoid making rash decisions, to minimize errors and the need to correct them in the future, today in practice such a technology as A/B testing is actively used.

In this case, we are talking about comparing several versions of the same page in order to determine the most suitable solution. One that will cause the most positive response from the user audience. Real users are involved in A/B testing. That is, the same people are shown different versions, and then the results are summed up. The version that shows the highest result as a result of such testing is sent to work. Basically, delivery is done to those pages where the conversion (conversion tracking) will be higher.

As part of today's review, we will dwell in more detail on what A/B testing is, why it is worth conducting and what parameters can be tested with its help. We will show how this technique works and what stages need to be implemented during its implementation. We will provide a number of additional recommendations that will improve the quality of the work performed, and also tell you about the services that will allow you to complete the upcoming work as quickly and easily as possible. We will highlight a number of the most common mistakes that occur in practice when conducting A/B testing. The information provided will allow you to get the most detailed understanding of this issue and complete all the work quickly and easily.

Why is it important to use A/B testing

If you want your site to work, to attract an audience, to sell your products and services, then you will have to work with it, regularly and comprehensively. The fact that you will prepare the material and post it on the site is far from the best strategy. It is important to understand how your readers will perceive it. If you think about this in advance, you can identify weaknesses and eliminate them, thereby obtaining the highest possible result in practice./p>

A/B testing is what will save you from guesswork, minimizes the likelihood of making subsequent adjustments and changes. That is, thanks to it, you will initially publish material that the user audience will perceive as positively as possible. This is what will increase engagement rates, have a positive impact on conversion rates, sales, and business revenue.

In practice, this method looks like this. Let's say you are launching a project dedicated to online English courses. You have checked that the landing page conversion rate today is only 4%. This figure does not suit you, and you want to get higher figures, say 10%. What will you do in this situation? Start looking for ways to increase this figure. That is, you will start formulating assumptions - hypotheses.

Alternatively, you can assume that a good result can be achieved by simplifying the application form, removing a number of optional items from it. Or think about displaying basic information about each course and its cost on the main page, which will allow people to immediately choose the appropriate training format for themselves without additional transitions. There are many options here, but your task in this case will be to check which of your hypotheses will give the maximum result in practice and allow you to get closer to the desired 10% conversion. Identifying it is the main task that will be assigned to A/B testing.

If we are talking about a small project, for example, a startup, then such events are not necessary. But you need to understand that as traffic grows, the cost of mistakes will also increase. What will happen to your idea if you invest in project promotion, but the number of clients of your online school does not increase? Or in the case when the number of visitors to the site increases, but does not bring conversion? You will still have to review your entire strategy, identify the mistakes made and correct them. But in this case, time, effort, money will already have been spent. This is despite the fact that your more successful competitors will already take a fairly large part of the target audience.

It will be much more reliable and effective to perform A/B testing in order to identify in advance the most correct and working strategies that will obviously work in practice. When forming hypotheses, it is important to evaluate them not only from the point of view of achieving the desired results, for example, increasing conversion, but also taking into account the costs of development. That is, this way you will be able to set priorities as correctly as possible and get accurate results.

That is, the practical use of A/B testing is what will allow you to:

• find out how individual elements of your page affect user behavioral factors;
• eliminate subjective opinion during decision-making, minimize all possible risks;
• improve user action conversion rates, as well as such economic indicators as income level, average check size, etc.;
• direct all labor and financial resources to the implementation of those ideas that will obviously give maximum results in practice.

Yes, you will spend a certain amount of time and effort on A/B testing, but you will be able to minimize various problems that prevent your Internet project from fully developing. The main thing is perform the upcoming work as correctly as possible.

What elements can be tested using A/B testing

If you really want to, you can test absolutely all the components that in your case have a direct impact on the transformation of a site visitor into a client. But in practice, such large-scale work is carried out very rarely. Most often, one main parameter is selected for testing. But in practice today, multivariate testing is also encountered, which involves checking several elements. In particular, these can be:

1. Advertising materials. You must understand that uninformative, unconvincing text is what can ruin any paid advertising. All you can achieve in this case is a waste of budget. Here you need to prepare materials that would appeal to your audience, would arouse their interest, which would ultimately lead to a purchase.
2. A separate page of the site. This is relevant not only for landing pages, but also for many other pages that your customers will visit. It's not just about the content itself, but also about the background color, how harmoniously and consistently the blocks will be placed. This way, you can understand which elements your users liked, and which, on the contrary, they reject and want to just take and close the page.
3. Call to perform a target action. Here, it is important to make sure that your audience actively and voluntarily makes contact, happily subscribes to your newsletters, leaves comments, and reposts. A/B testing will help you choose the most appropriate tone of communication, place buttons so that people find them convenient to work with. In this case, you can develop several options, and then test them all to see which option will be the most effective and convenient for you.
4. Working with letters for newsletters. With the help of A/B testing, you can check the relevance of topics, content, test layouts and other elements of letters, identify those options that give the greatest result in practice. That is, what the audience responds to most actively.
5. Subscription forms. Here it is necessary to check as much as possible. Practice shows that the user audience is influenced not only by the text, but even by the color of the buttons. Correct development is a guarantee that the time to think about the purchase will be minimized, and the percentage of a positive decision will be higher.

That is, you can test headings and subheadings of texts, as well as the content itself, including advertising materials, product descriptions in the product catalog, graphic blocks, the amount of material on a particular page. Also, using this technology, you can evaluate the appearance of a separate page and the entire site as a whole, the placement and text of CTA buttons, check user reviews, the correctness of registration forms. A/B testing is often used to initially evaluate the future design and layout of the page, to understand how presentable and harmonious everything will look. Business representatives should definitely start checking promotions, prices, delivery conditions and other business components even before offering all this to the consumer market.

Nuances of A/B testing

The A/B testing mechanism itself is quite simple. In the course of performing these works, it is necessary to divide all visitors of the resource into 2 or more groups, and then direct each of them to separate versions of the pages of your site. It does not matter here whether you will adhere to the division into equal groups by the number of participants or divide the traffic 60% and 40%, 30% and 70%. You manage all these parameters yourself. The main thing is that you get a clear picture at the output and can draw the appropriate conclusions.

It is also imperative to exclude situations when different versions of pages are displayed to the same person. If this is allowed, then you will not get statistically significant results, which means the reliability of your A/B testing will be in great question. In order to perform the appropriate division and “assign” a certain user to one audience, special parameters are used. They are written directly into the browser cookie files.

Also, in order to get the most reliable data in the testing results, it is important to take into account all the channels from which your traffic will come. We are talking about the social component, organic, advertising traffic, email newsletters etc. It is also important to take measurements at the same time. That is, you need to create the most equal conditions for all participants, as well as minimize external factors, including the actions of call center service operators, moderators and any other personnel. Only if all these conditions are met can we confidently say that the accuracy of the A/B testing will be as high as possible and will ultimately benefit your business.

Doing A/B testing of websites correctly

Conducting A/B testing — This is a rather boring and monotonous process, which involves the step-by-step implementation of a number of key stages. We would like to draw your attention to the fact that experience and intuition are good, but you still cannot do without systematically implementing the stages prescribed in the methodology of this process. Otherwise, all your time and effort will be wasted - you will not get an accurate result.

A/B testing itself will be quite simple to implement. This means that even a novice marketer will be able to perform the upcoming work. A much more complex process is to develop several versions of the same page that will be launched for testing. This is something that will require certain knowledge, skills, and otherwise - just follow our instructions and perform the work in the following sequence:

1. Determine what goal you set for yourself. That is, you need to clearly understand why all the changes on the site are being made. Alternatively, you want to increase the number of orders, improve the user experience. Perhaps you have noticed that your bounce rate has increased, that users often leave items in the cart without completing the purchase. That is, it is important to understand what exactly you want to get as a result, and then take measures to improve it. This is what will ultimately allow you to select key parameters for A/B testing.
2. Select the indicator based on which you will evaluate the results of the work performed. We have already mentioned above that most A/B testing involves the use of one parameter, but a comprehensive approach is also possible. Alternatively, you can focus on increasing the number of user requests that will come to your store from the target audience, increasing the clickability of buttons, activating requests to store managers, increasing the number of people registering on the site, etc. That is, you yourself determine which parameter will currently play a key role in the development of your business. Practice shows that the most popular metric when performing A/B testing among most managers will be an increase in revenue from website sales. And this is quite reasonable, since increasing revenue is a priority for any business.
3. Draw up several hypotheses that, in your opinion, should ensure the fulfillment of the task. In this case, we are talking about the fact that you are selecting several options that will contribute to achieving the goal. Perhaps you believe that the low level of income is due to the fact that the structure of your catalog is inconvenient for users, that it lacks navigation, does not provide a filter system, or lacks some important criteria. That is, it is important for you to formulate all the ideas correctly, write them down and then launch each one for testing. The main thing at this stage is to clearly separate all the hypotheses. Do not try to combine all your assumptions into one dimension. This way, you will not be able to see which parameter has a negative impact on sales indicators and understand which of your assumptions worked and which did not. Perhaps even without this, you will be able to eliminate the existing problem, but you will not be able to use the experience gained in subsequent work. That is, the fewer changes are tested in each case, the more efficiently you will be able to evaluate the effectiveness.
4. Determine the group of visitors who will participate in A/B testing. Sample size is one of the key indicators in the process of performing this work. Otherwise, you will not be able to understand that the results obtained have a sufficiently serious statistical significance, and not just a coincidence. Today, there are already special A/B testing calculators, using which you can determine the optimal number of people who should view a certain version of the page. Only if you collect a sufficient number of people, you can talk about the reliability of the results obtained. Otherwise, all your actions and numbers will not have statistical significance. It is also important to understand which users, in your opinion, should be included in the contact group. These can be regular visitors to your site or new ones. In the first case, these are people who have already contacted your site. Those who know its features and have adapted to them. New users will always be more critical - this is not your loyal audience. But it is imperative to exclude company employees from testing, regardless of their level of involvement. Alternatively, you can immediately enter into the system those IP addresses, the connection from which will not be taken into account by the analytics system, i.e. will not affect the testing results.
5. Set a time frame for testing. On average, this work takes up to 2 weeks. This is quite enough to gather the required number of testers and evaluate user reactions. For maximum visibility and increased detail, it is important to cover all days of the week and different times of the day in testing. If you drag out your A/B testing for a month or longer, you can completely lose important information. The fact is that there is always a risk that people will simply clear the cookies on their devices. This means that their subsequent visits to your site will be counted by the system as a new connection of a new person. As a result, the testing results are distorted and you do not achieve your goal.
6. Work on improving external factors. This means collecting the most homogeneous audience for A/B testing, as well as distributing traffic evenly between different versions of pages. The results should be analyzed separately for each of the traffic channels. To perform the work, select the time interval that is standard for your business. Alternatively, you should not launch the work during seasonal sales. This way, you will not understand whether your transformations worked or whether demand in the market simply increased. The same will be true for the period of stagnation. That is, you will not understand whether your transformations worsened the user experience or whether this is just a coincidence. That is, choose a standard period for your sales.
7. Run the testing itself. This work can be done using built-in tools, which is implemented in a number of specialized systems. In this case, the program itself will distribute the traffic between all ad options or companies and calculate the results. Manual A/B testing can also be performed. This option is suitable for any use cases, but it is still quite labor-intensive, since the configuration of the display of objects will have to be performed by specialists independently. Testing can also be done using programming. In practice, this method is used very rarely, since it is quite labor-intensive and requires special knowledge, skills, and serious preparation. But it will be highly effective when performing complex testing. When it is necessary to simultaneously study different metrics, focus on different segments of the user audience. Another testing option is the use of special services. Suitable for various types of sites, online applications, email newsletters. It involves adding a special code to the site. After that, the service itself will be able to distribute traffic and calculate the results. This option has found wide application in practice, and we will consider the most suitable services for performing this work below.
8. Analysis of the results obtained. This is a very important stage of any A/B testing, since it allows you to evaluate the static significance and select the page that, as a result of the work performed, showed itself to be the best. Then it remains only to implement the appropriate changes to the site. But monitoring the results does not end there. You must make sure that you have managed to achieve your goal. And this means that after a certain period of time you will have to perform a series of checks again.

Practice shows that properly conducted testing taking into account all the basic requirements, as well as the most correct interpretation of the results - this is what will allow you to get the maximum result in practice.

Important points during A/B testing

Described above A/B testing, we have repeatedly talked about such concepts as the statistical significance of the text, statistically significant user sample. Despite the fact that they sound quite complicated, their principle is quite simple. In particular, the static significance of the test is a variable that will indicate the reliability of the study. It is calculated mathematically. It is believed that if the final indicator is above 93-95%, then you have done all the work as correctly as possible and the result can be considered successful. That is, you can rely on it and make appropriate adjustments to the site, being confident that its efficiency will improve. This indicator is determined through the same A/B testing calculators that we talked about above. Also, the basic capabilities of Google Analytics, end-to-end analytics, which will be extracted from CRM systems, can be used here.

In turn, a statistically significant sample involves defining a group of visitors who will take part in testing. That is, this is not your entire target audience, but a certain part of it. Alternatively, this could be the first 100, 1000 visitors. Their required number can also be calculated using a calculator based on the specifics of the site itself and the characteristics of the business as a whole. The main thing here is to get the most reliable results, and then they can be scaled to absolutely the entire audience. Let's say you saw that the first 1000 visitors on one or another version of the page performed 150 target actions. This means that the conversion rate will be 15%. And it does not matter whether 100 or 10,000 people visit your site next time, the target actions will still be within 15%. But all this will only apply to "ideal" conditions. In reality, the results can be influenced by a huge number of external factors, ranging from the level of awareness of your business to advertising campaigns and the actions of your competitors. That is, you should always understand that A/B testing will have an error and take it into account when performing work.

What services can be used to conduct A/B testing

We have already mentioned above that one of the simplest, most convenient ways to conduct A/B testing of sites will be the use of specialized services. In order not to spend a long time looking for the most suitable option for yourself, you can use one of these solutions:

• Google Analytics. The service offers to perform upcoming work directly from your account absolutely free of charge. The functionality here will be quite limited, but, nevertheless, they will be quite enough for you to conduct simple experiments. But here you definitely need to have some knowledge of HTML code, since the visual component is not provided.
• Vwo.com. A service developed specifically for testing both desktop and mobile versions of Internet resources. It already has a visual editor, as well as fairly advanced targeting, a library of ideas for launching such testing. Conveniently, it also provides the ability to integrate with many platforms and tools that marketers use in their daily work. Among other things, you can set up joint work with the same Google Analytics.
• Google Optimize. A free service from a well-known developer, which you can very easily and quickly synchronize with your main account in Google Analytics in order to view reports with the results of the testing. Conveniently, using this service you can check various changes on the pages, including images, headings, fonts, design, buttons, color palette, etc.
• Changeagain.me. There is a pretty good visual editor, there is targeting by devices and regions. The service is suitable for working with desktop and mobile versions. Direct integration with a personal Google Analytics account is also implemented.
• Optimizely. We would like to draw your attention to the fact that this tool will be paid, but with its help you will be able to conduct not only A/B testing, but also multivariate, multichannel tests, split tests. Due to the fact that there is a visual interface, you do not need to have certain knowledge in the field of HTML code. It is convenient that there is an opportunity to segment the results obtained, perform diverse integration. Quite advanced targeting tools are provided.
• Convert.com. With the help of this service, you can perform A/B testing for several income metrics at once, launch diverse targeting. There is a visual editor and quite wide opportunities for integration with other services.

Regardless of which service you decide to use for A/B testing, the principle of the work itself will be quite similar. And above we have already described in detail the sequence in which the work should be performed in order to obtain the maximum result in practice.

The most common mistakes during A/B testing

If we analyze all the mistakes that are encountered today in practice during A/B testing, we can highlight a number of key points:

1. Launching different changes at the same time. We have already said that using several changes within the same test is not the best option. If you change several elements at the same time, you will not be able to understand which of them had a positive effect on the results, and which, on the contrary, turned out to be a failure. Therefore, it is better to always use only one change. It will be much more effective to simply run several such checks.
2. Completing the test before stable results are obtained. We have already said that on average, such testing will take up to 2 weeks. If you do not use these recommendations, you will not be able to get the required sample size, which will have a negative impact on the overall testing results. And you should not delay it too much, because this is fraught with reconnection of users.
3. Using other people's hypotheses in practice. You must understand that solutions that have proven themselves well in one project will be completely irrelevant for another. Here you should take into account the specifics and features of each site, focus on the interests and profile of the target audience. If you borrow other solutions, then you should do it wisely, having previously adapted them to the specifics of your site. Take the time to analyze your own situation and put forward the hypothesis that will be most effective in your case.
4. The audience distribution was not uniform. If this is allowed, the page options will be displayed to the audience unevenly, which will ultimately lead to one segment of the audience seeing both options, while others will not have access to the modified version at all. To avoid such a problem, it is optimal to use the services we talked about above. In this case, the traffic will be distributed evenly and such problems will not occur.
5. Incorrect choice of metrics. We are talking about using those metrics that do not have a direct impact on commercial indicators. Therefore, it is optimal to focus on those solutions that are related to the level of income. The most universal solution in this case will be the conversion rate.
6. The resulting sample has nothing in common with the general population of users. A similar problem is also associated with incorrect traffic distribution, so it is still better to perform this work through specialized services.
7. Ignoring external factors. We have already said that a huge number of external factors have a significant impact on the accuracy of testing. And if you neglect them, you will not be able to get the most detailed picture during testing. Therefore, it is important to take into account sales periods, seasonality, time of day. The optimal solution is to carry out work during periods neutral for business. This way you can count on the most accurate results.

Now that you know about the main mistakes, you can avoid them, thereby increasing the quality and effectiveness of your testing.

Let's summarize

As you can see, A/B testing is This is an extremely popular and useful tool for testing various hypotheses designed to improve the quality of website pages and their convenience for the user audience. This is what will allow you to initially launch the highest quality websites that will be positively received by the user audience and will be as easy to use as possible.

If we briefly summarize everything we talked about in today's review, it is worth highlighting several points:

• A/B testing is a research method during which several versions of website pages are tested in order to determine the best solution from the point of view of the user audience. Your task is to identify the option that will provide the best results in practice.
• To launch such testing, you need to initially put forward several hypotheses, determine key metrics, calculate the audience sample, launch testing through specialized services and analyze the results.
• In order for the test results to be as close to reliable as possible, it is important to exclude the most common errors. It is also important to take a comprehensive approach to evaluating the results.

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