Buyer's Guide: A/B Testing
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users value the ease of use of Statsig, making experiments quick and intuitive to implement and manage.
Users praise the ease of running experiments, facilitating quick decisions and enhancing understanding of user behavior.
Users value the real-time insights from Statsig, enabling easy experimentation and clear performance tracking.
Users find the learning curve steep due to complex setup and overwhelming UI, but support helps ease the process.
Users experience a steep learning curve due to complex features and initial setup challenges, impacting usability.
Users note the missing features in Statsig, including ad hoc analysis, real-time syncing, and complex conditions.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of VWO Testing, making A/B testing simple even for non-technical users.
Users appreciate the incredible customer support from VWO Testing, which understands their needs and offers quick assistance.
Users appreciate the intuitive interface of VWO Testing, facilitating effortless A/B testing for all skill levels.
Users find missing features a drawback, noting instability in the variant editor and high pricing for advanced functionalities.
Users find VWO's limited features restrictive, especially lacking in complex changes and product recommendations.
Users are concerned about session count limitations and integration difficulties with VWO, affecting the overall user experience.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use of AB Tasty, facilitating quick implementation of tests and personalizations.
Users appreciate the excellent customer support of AB Tasty, highlighting quick responses and helpful assistance.
Users value the excellent customer support and helpful tools that enhance their experience with AB Tasty.
Users face testing difficulties due to QA bugs and issues running tests, causing time loss and complications.
Users find the difficult learning curve challenging, particularly for complex experiments and advanced targeting options.
Users find the limitations of the visual editor and targeting options hinder effective analysis and experimentation.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users find LaunchDarkly incredibly easy to use, with intuitive features that simplify management and integration for teams.
Users value the flexibility of feature flags in LaunchDarkly, enhancing development processes and user experience significantly.
Users love the flexible feature management of LaunchDarkly, enhancing development efficiency and improving user experience.
Users face feature flags issues, with complexity and reliability concerns disrupting workflows and causing confusion.
Users find complexity and small UI bugs in LaunchDarkly challenging, especially when managing numerous feature flags across environments.
Users find missing features in LaunchDarkly frustrating, particularly regarding rules and analytics for feature performance.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users find Bloomreach easy to implement and use, making daily tasks and campaign management seamless and efficient.
Users value the centralized zero party data in Bloomreach, simplifying reports, audience building, and CRM integration.
Users appreciate the outstanding support from Bloomreach, highlighting responsiveness and professionalism for a seamless experience.
Users find the learning curve steep, needing time to acclimate to navigation and features of Bloomreach.
Users find Bloomreach's setup too complex for basic tasks, making it challenging for new users to navigate.
Users find some missing features in Bloomreach, feeling advanced options are limited and cumbersome to use.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use in designing omnichannel journeys with Netcore's intuitive drag-and-drop builder.
Users value the excellent customer support from Netcore, enhancing their engagement experience significantly.
Users commend the exceptional customer support from Netcore, noting their responsiveness and dedication to user success.
Users face missing features like error notifications during campaign uploads, leading to a frustrating experience with file management.
Users often experience slow performance with the platform, especially during heavy data uploads and template uploads.
Users find the learning curve steep, particularly in setup, segmentation, and journey creation processes.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use in Webflow, allowing quick website creation through intuitive drag-and-drop functionality.
Users value the design flexibility of Webflow, enabling rapid website creation with visual precision and advanced functionality.
Users love Webflow's lightning-fast publishing and intuitive CMS, enhancing collaboration and creative freedom for swift site development.
Users feel the learning curve is steep, making it challenging for newcomers to adapt to Webflow's complexities.
Users express frustration with Webflow's limited features, particularly around CMS nesting and e-commerce functionality.
Users note the missing features in Webflow, including nested collections and various file upload limitations.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users praise the ease of use of MoEngage, enabling effective engagement and retention across multiple channels.
Users love the multiple features of MoEngage for effective engagement, retention, and insightful analytics.
Users value MoEngage for its helpful support team that is responsive and readily available for assistance.
Users find missing features in MoEngage, such as limited product personalization and unclear event setup, impacting overall usability.
Users find the learning curve steep, particularly with event setup and navigating the feature-rich but complex UI.
Users find limited campaign settings hinder MoEngage's effectiveness, impacting customization and overall user experience.
This description is provided by the seller.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the ease of use in PostHog, finding it straightforward and user-friendly for analytics.
Users love the easy setup of PostHog, appreciating its simplicity and powerful analytics tools available immediately.
Users appreciate the user-friendly analytics of PostHog, enjoying its easy setup and intuitive interface.
Users face a steep learning curve with PostHog, finding it difficult to understand features and data effectively.
Users face a steep learning curve with PostHog, finding it challenging to grasp its features and functionalities.
Users find the initial setup complexity of PostHog challenging, particularly in configuring advanced features and self-hosting.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users praise the ease of use of AppMetrica, enjoying straightforward setup and intuitive navigation for insights.
Users appreciate the easy integrations of AppMetrica, making data analysis straightforward and effective for mobile applications.
Users value the user-friendly analytics of AppMetrica, enabling clear insights and effortless tracking for informed decision-making.
Users express frustration over missing features in AppMetrica, deeming it difficult and lacking useful capabilities.
Users face reporting issues with limited customization and slow performance when handling larger datasets in AppMetrica.
Users find inadequate reporting in AppMetrica, lacking essential features like detailed UTM and ad performance analysis.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users praise Kameleoon for its excellent customer support, providing expert guidance and ensuring optimal platform usage.
Users find Kameleoon to be easy to use, featuring a fun graphic editor and simple implementation.
Users find Kameleoon's A/B testing capabilities easy and effective, enhanced by excellent support and user-friendly design.
Users express concern over their dependency on developers, which can lead to delays and added costs in A/B testing.
Users find the difficult learning curve of Kameleoon frustrating, particularly with its complex features and widgets.
Users find the learning curve steep for Kameleoon, noting navigation and terminology can be unintuitive.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users appreciate the intuitive interface of Optimizely Web Experimentation, making experimentation simple and accessible for everyone.
Users highlight the agile experimentation capabilities of Optimizely, rapidly delivering content updates and optimizing user experiences.
Users appreciate the flexibility and ease of use in Optimizely Web Experimentation, enhancing testing and optimization processes.
Users find the steep learning curve challenging, especially without prior experience or dedicated resources for experimentation.
Users find the difficult learning curve of Optimizely Web Experimentation challenging, especially for those without prior experience.
Users find the difficulty of use in Optimizely Web Experimentation frustrating, especially for those without coding experience.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users commend the responsive customer support of Omniconvert, appreciating their quick assistance with any issues.
Users appreciate the fast and responsive customer support of Omniconvert, enhancing their overall experience.
Users find Omniconvert's platform incredibly easy to use, complemented by outstanding customer support that enhances the experience.
Users find the steep learning curve challenging, particularly for advanced features and initial setup, though benefits emerge later.
Users often face poor customer support due to limited help documentation, necessitating frequent contact for assistance.
Users express concern over the need for developer assistance for complex tasks, highlighting potential barriers for marketing teams.
This description is provided by the seller.
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Users find the ease of use of Harness Platform invaluable, facilitating quick setup and streamlined project implementation.
Users value the ease of integration with Harness Platform, highlighting its simple implementation and support for various SDKs.
Users find the ease of use of Harness's Feature Flags invaluable for seamless and confident feature releases.
Users seek missing feature flags to better target specific companies, hindering development and integration experiences.
Users report clunky UI and manual user management issues that hinder usability and integration efforts.
Users express frustration over limited features, particularly the absence of browser devtools and response character limits.
A/B testing tools measure how customers interact with a brand’s digital creative content. Through conducting tests on customer interaction, companies can extract real data and metrics to optimize products.
A/B testing tools allow marketers, advertisers, and web developers to test different versions of digital content to find the customer-preferred digital experience and personalization for various personas. Website visitors subconsciously react to every element on a web page—such as the color and aggressiveness of a live chat pop-up, the phrasing of a call-to-action (CTA) button, or the positioning of the search bar. A/B testing solutions give web content creators the tools to deploy the tests, determine the target audience, and analyze the experiment results. These tools are used to improve conversion rate and bounce rates, as well as the overall success of a website.
The main way that digital creativity is tested is through a rotating A/B test. This is done by using two iterations of a design and seeing which one gets the highest click-through rate. A company can conduct a test with version A for 500 users from the target audience and then another test on version B for 500 users with a completely different variant. The company can then see which one gets the highest click-through rate and, ultimately, determine which variant should be used.
A/B testing can offer the following use cases to improve a company’s performance:
Proprietary A/B testing
Proprietary solutions will require time and resources but will adapt to very specific case studies and customizations. Proprietary products also provide customer support and streamline the process of setting up, tracking, and analyzing tests.
Open-source A/B testing
Open-source solutions come with a very small price tag (if any at all). While open-source software doesn’t offer the same kinds of reports and finetuned features as proprietary solutions, it gives access to an entire community of programmers and developers with bountiful testing experience.
A/B/n testing: This type of split testing takes A/B testing to the next level by analyzing multiple versions of a creative product, one variable at a time. This allows a company to determine the best variation across a multitude of tests that measure KPIs on several iterations. The analytics tools used for a simple A/B test will also measure the same KPIs for the multiple variations.
Multivariate testing: Multivariate testing uses the same methods as A/B testing, but instead of testing only two variables, it tests a higher number. This is essentially like having two tests combined into one. This is a way to conduct test combinations. For example, one multivariate test can test whether the combination of a blue header and white text works better than a red header with grey text. Then, it can test what happens when the combination is flipped—whether a blue header would work better with grey text or a red header would work better with white text. A successfully performed multivariate test would then show which combination had the highest click-through rate. The major benefit of multivariate testing is saving time and ensuring that the best combination with the highest conversion rate is being presented on the website.
Multipage funnel testing: Multipage funnel testing is a way to test variations of several consecutive website pages. This is a great way to see if customers are finding what they’re looking for in the quickest way possible. The use case of multipage funnel testing can be easily applicable to retail, e-commerce, and any other website where the company is selling a product. This can test how quickly a user went through the buyer funnel from initial interest all the way to the final goal of purchasing the product. A multipage funnel test can help test the most effective way to convert customer interest into a customer purchase.
Audience targeting: Audience targeting provides the ability to choose where the test will run and for whom. A/B test can be conducted to see which visitor conditions to show the experiment to and which specific URLs the experiment should run on the site. To increase engagement from mobile users who are using Google Chrome, audience targeting can conduct the A/B test on these specific users. This helps increase engagement with a particular audience.
Funnel analysis: Funnel analysis allows companies to analyze the data in the buyer's journey and make necessary changes to facilitate conversion rate optimization. A/B test with funnel analysis helps understand if things such as registration pages or website subscription options are driving more people to convert or if they’re turning customers away. This allows the tester to see if they need to make adjustments to certain stages to increase engagement.
Heat maps: Heat maps are a very effective tool for visualizing which links users click on when they visit a website. Heat maps applied to an A/B test will show certain links on a webpage in either blue, yellow, or red to indicate how often those links are clicked. This way, testers can analyze how to effectively set up a page and ensure that the most important links are in spots that are being clicked on the most.
Surveys: A valuable feature in A/B testing software is surveys. This enables companies to directly ask users which type of variant they prefer through a variety of different questions. The data from the survey can then be translated into graphs or charts, which makes it easier for the tester to visualize the results. This can help companies target which specific variants are working well and which variants are failing. It also may give companies more detail on where to head in order to improve their designs by asking questions that make users explain in detail rather than asking simple yes or no questions.
Statistical relevance analysis: Statistical relevance analysis helps confirm if an A/B test has a large enough sample size. Users can track their data in real time and see if the test needs more time or if there’s enough traffic to confirm that one variant performed better than another. This helps users stop the test and not use more time on it than needed. Achieving the right sample size ensures the statistical significance of test results is achieved during the testing process.
Test scheduling: A/B testing platforms allow users to schedule tests in advance to ensure that they are conducted during a time when the website is expected to get a lot of traffic.
A/B testing software is an essential tool for optimization and growth. The best way to improve a product's performance is by continuously conducting new trials to see what works and what doesn't. The following are reasons why vendors benefit from using these tools.
Higher conversion rates: Companies can conduct a test to see what will produce the best conversion rate. Rotating A/B tests can give content creators an accurate representation of how quickly users can find what they’re looking for on a website. This can lead to customers purchasing more quickly or subscribing to newsletters more frequently, leading to greater conversions and higher revenue for the company.
Real-time testing: A/B testing can save companies plenty of time by testing variations in real time. Instead of having to pull people aside to conduct trials, rotating tests are conducted on users who are currently visiting the website.
Genuine testing: Another major benefit of A/B testing is genuine testing. Tests are conducted on actual visitors who are coming to the website, which means that the results are not skewed by incentives or preconceived knowledge within a trial. Since the testing is done on completely random visitors, the company will get the most accurate picture of how customers are behaving in real time.
Reduced bounce rate: One of the main goals of A/B testing tools is to test ways to keep people on a website for as long as possible. This can be done by incorporating different page layouts, links that lead back to the website, and CTA buttons. High bounce rates are the main reason for low conversion rates, so testing ways to reduce the bounce rate of a landing page is a critical way to keep customers engaged.
While A/B testing tools and personalization software generally integrate with systems that work on both the front end and back end of websites, the software isn’t just for technical website developers who specialize in coding. Users with varying skill sets can use the software to enhance their currently existing websites. Appropriately, A/B testing software vendors clearly advertise either their ease of use (embedding just one line of code) or the flexibility with which their tests can be conducted (conducting split-level experiments). Here are some ways various team members can use these tools to enhance performance:
Digital marketing teams: Digital marketing teams can utilize A/B testing software in a variety of ways. They can measure the efficacy of CTAs, headlines, images, and copy to see which variations will have higher click-through rates with users. In addition, they can measure the frequency of cart abandonment to test how likely a customer is to convert into a sale.
Design teams: Perfecting the design of a website is an ongoing process. Design teams can utilize A/B testing to optimize a website’s performance and quality of the user experience by making sure visitors are staying on for an ample amount of time. They can do this by testing how quickly people find what they’re looking for, where to place links on a page to get the most clicks, and other web layout adjustments in order to increase customer engagement.
Research and development teams: Research teams that focus on optimizing website performance can use surveys within A/B testing tools to see which variants appeal to more users. They can ask about customer desires, demographics, and any other details that they can extract to improve their product and website.
A/B testing can be supplemented with a wide variety of other software that also test for conversion rates and lead generation:
Email marketing software: Email marketing software includes A/B testing features, which can be used to test which of two email campaign options will be more successful. During this process, two variations of an email campaign are sent out to two different pools of recipients. Whichever pool has the higher click rate on the email campaign will indicate which one will be more successful. The results can indicate the open rate, click-through rate, and the number of subscribers that were influenced by the email campaign. This is a great tool to guarantee that the marketing campaign is effective and that it will generate more revenue and happier customers.
Web content management software: Web content management (WCM) systems allow users to create, edit, and publish digital content such as text, embedded audio and video files, and interactive graphics for websites. WCM tools offer an assortment of templated web pages, from which site administrators can browse and choose. Since the main goal of web content management is to maximize customer engagement, it is a great software to integrate with A/B testing. A/B tests can be conducted on certain web content and provide higher conversion rates.
Digital analytics software: Digital analytics software tracks website visitors and measures web traffic. Marketers, web developers, and analysts use digital analytics suites to report on the effectiveness and popularity of web experiences and to determine how visitors are finding and interacting with their sites. Digital analytics supplement A/B testing by showing companies which areas need improvement on their website. This can indicate what areas need help from a test to determine what will improve customer engagement.
Heatmap tools: Marketers and web developers use heat maps and in-page analytics to visualize where on a web page visitors click, hover, and scroll. Heat maps can be integrated with A/B testing software to effectively set up a page and ensure that the most important links are in spots that are being clicked on the most.
Ensuring random testing: It is difficult to ensure that a test is truly random. For example, if a company wanted to conduct an A/B test on page traffic on any random day, it might be difficult to assess whether visitors were less likely to come on that day. If the weather was nice or it was too close to the holidays, people might be less likely to be on their computers, which can skew the test's results.
Testing too many variables: Product teams are constantly trying to reimagine product pages with new designs to increase sales. However, overtesting can be a problem, especially when users are more familiar with one design over another. This can lead product teams to be overfocused on certain website designs that will most likely not have an effect on the user. The best way to avoid this issue is to focus on major design changes, such as page layouts, rather than the font size of certain words.
Small sample sizes: Often, A/B tests are conducted on too small a sample. This means that there is not enough data to confidently say that a variation is more successful than another variation because not enough people were tested. The best way to avoid this issue is to conduct a test that is concluded when the test reaches 95% confidence. While this may take some time, it can ensure that it was conducted effectively.
When searching for the right A/B testing tool, it’s important to create a long list based on products that contain some of the most necessary features for an effective experiment. After the available pool has been segmented based on crucial features, one can then sort based on nice-to-haves, bells and whistles, and industry-specific software requirements.
Create a long list
In order to create a long list, buyers must ensure the products being considered meet these core criteria:
Create a short list
Once a long list based on core features is created, a short list should be further narrowed based on nice-to-haves and bells and whistles:
Conduct demos
Buyers must schedule calls with the vendors on the short list to ensure their product is the right fit. The most foolproof way to make the right decision is to actually test out the software. It is important to ask vendors about how their product addresses the business’ most pressing needs.
Choose a selection team
The selection team should include the CEO and other executives from finance, marketing, and IT. The CEO will be there to represent the whole company and its business objectives. Finance will be able to represent the company and IT will determine if the product fits well into existing tech stacks and company technology. Most importantly, representatives from marketing will be able to speak fluently on the goals of A/B testing and company needs with software, since the marketing team will be the end user for these tools.
Negotiation
A/B testing software vendors will be bringing their strongest team to seal the deal with a potential client. Therefore, it’s important to come to the negotiation process with questions on certain key features one needs. These include (but are not limited to) multivariate testing and WYSIWYG capabilities, how much coding experience is needed to use the interface, and AI or machine learning. Buyers must ask questions about the total costs and fees associated with purchasing, implementing, and using the product. In order to prevent surprises later, it is crucial to ensure the terms and conditions are read in full and discussed.
Final decision
It could be useful to create a scoring template that measures the various features mentioned in the long and short list, as well as notes from calls between the client and vendor.
Calls-to-action (CTA): CTAs have become the most popular test to conduct within A/B testing. Calls to action are phrases that try to induce urgency in the buyer, like a certain offering will expire soon or must be purchased immediately. More companies are using CTA links, as they help with end-of-funnel marketing and can lead to a sale in the quickest way possible. Common A/B tests to run on a CTA button include bigger text size, brighter button colors, and any other adjustments to make the button more visually appealing or engaging.
Mobile A/B testing: These tests are seeing a huge spike in growth as more users are shifting away from desktops and onto their phones. Mobile A/B testing trends can help companies analyze how their mobile app’s layout is performing and how to make mobile purchases for consumers as simple as possible. Since the screen size is so drastic from the desktop to the mobile screen, it’s important to make necessary changes so users can see product offerings on a smaller screen.
Website personalization: A/B tests enable users to run tests based on customers’ personal information. Companies can utilize big data to offer tailored content (based on assumptions about the way a visitor will behave) to invoke the feeling of a personalized shopping or browsing experience. Testers can run A/B tests to examine if the tailored content leads to more conversions or engagement.