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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 find VWO Testing's easy-to-use interface and responsive support team enhance their testing experience significantly.
Users praise the responsive customer support of VWO Testing, enhancing their overall experience and troubleshooting capabilities.
Users appreciate the powerful and user-friendly A/B testing features of VWO, enabling effective analysis and decision-making.
Users note the missing features like scrollmaps and more templates, hindering usability for non-technical users.
Users find VWO Testing has limited features, often needing developer help for more complex experiments and customizations.
Users find the limitations in segmentation and pricing structure restricts their testing capabilities in VWO.
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, highlighting its intuitive interface and flexible features.
Users appreciate the excellent customer support from AB Tasty, helping them effectively leverage the platform's features.
Users value the exceptional customer support from AB Tasty, enhancing their overall experience and problem-solving capabilities.
Users face testing difficulties due to QA bugs and challenges in identifying optimal versions, which hinder testing efficiency.
Users find feature explanations unclear and face challenges with data integration for multiple accounts in AB Tasty.
Users experience difficult learning curves due to technical complexities and the need for extensive development knowledge.
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, simplifying quick experiments and clear results interpretation for decisions.
Users love the speed and ease of experimentation, enabling quick AB tests for confident decision making.
Users value the ease of running experiments and customizing metrics, enhancing their ability to analyze performance effectively.
Users find the learning curve on advanced analytics steep, requiring additional time and effort to master.
Users face a steep learning curve with Statsig's advanced analytics, requiring additional resources to master its features.
Users find missing features and occasional documentation lag impact their overall experience with Statsig.
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 love the ease of use with Netcore, enabling effortless campaign creation and real-time customer engagement.
Users value the responsive support and customer service of Netcore, which greatly enhances their overall experience.
Users commend the exceptional customer support of Netcore, ensuring effective integration and ongoing assistance.
Users find the missing features in Netcore's platform limit usability and complicate the user experience.
Users often experience slow performance with Netcore, especially during segmentation and email delivery peaks.
Users find the learning curve challenging, which can make initial use and setup somewhat overwhelming for new users.
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 to have a user-friendly interface, making it straightforward to implement and utilize daily.
Users commend Bloomreach's exceptional customer support, highlighting responsive and professional assistance that enhances their experience.
Users praise the exceptional support from Bloomreach, highlighting quick responses and helpful assistance for seamless experiences.
Users find the learning curve challenging, but appreciate the eventual rewards and support available during the process.
Users find the limited features in Bloomreach restrictive, impacting their ability to fully customize campaigns.
Users find the learning difficulty of Bloomreach challenging, needing significant time and training to navigate effectively.
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's ease of use and intuitive navigation enhances their overall experience and productivity.
Users value the ease of managing feature flags in LaunchDarkly, enhancing release processes without code redeployment.
Users value the intuitive feature management of LaunchDarkly, enabling seamless updates and safe experimentation without downtime.
Users struggle with cumbersome feature flag management, finding the individual enabling process tedious and inefficient across environments.
Users face inconsistencies in feature flag management, impacting user targeting and random distribution for tests.
Users desire missing features, including multi-environment editing, better GitHub integration, and improved flag visibility.
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 Webflow, enjoying its intuitive interface and fast publishing capabilities.
Users value the design flexibility of Webflow, enabling quick site creation and advanced customizations with ease.
Users appreciate the quick build speed of Webflow, enabling rapid page creation and client empowerment.
Users find the learning curve steep, requiring guidance and familiarity due to Webflow's complexity.
Users find Webflow's limited features frustrating, especially for complex content management and e-commerce capabilities.
Users perceive missing features in Webflow, including limitations on CMS nesting and file uploads affecting usability.
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 love the ease of use of EngageBay, appreciating its intuitive interface and seamless marketing automation tools.
Users praise the ease of workflows and robust features, highlighting responsive support and effective email marketing tools.
Users appreciate the excellent customer support of EngageBay, always ready to assist and enhance their experience.
Users find the missing advanced features frustrating, as many integrations and analytics are lacking in EngageBay.
Users find the limited features of EngageBay lacking, especially in analytics and modern design elements.
Users find the reporting issues in EngageBay limit advanced analytics, affecting overall functionality for in-depth needs.
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 love the ease of use of PostHog, finding its interface intuitive and quick to set up.
Users appreciate the easy setup of PostHog, allowing for quick implementation and a smooth onboarding experience.
Users find PostHog's user-friendly analytics setup and clean interface ideal for tracking early traffic effectively.
Users find the learning curve steep, as the data and features can be confusing for non-technical users.
Users experience a steep learning curve with PostHog, finding it challenging to navigate its complex features effectively.
Users find the missing features in PostHog, such as real-time session replay, limiting for effective 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 appreciate the ease of use of AppMetrica, finding it simple to integrate and manage their analytics effectively.
Users praise the easy integrations of AppMetrica, enhancing workflow with seamless setup and real-time data access.
Users value the user-friendly interface and comprehensive analytics of AppMetrica, enhancing their app performance insights.
Users report missing features like essential reports and ad tracking customization in AppMetrica, affecting usability.
Users struggle with limited reporting features and a non-intuitive UX, hindering effective data analysis.
Users find the inadequate reporting on ROAS and ad spend to be a significant limitation in AppMetrica.
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 highlight the ease of use of MoEngage, praising its user-friendly interface and seamless integration capabilities.
Users value the robust automation and analytics features of MoEngage, enhancing user engagement and campaign effectiveness.
Users value the helpful support team of MoEngage, ensuring quick resolutions and exceptional user experience.
Users note the missing features in MoEngage, including AI tools and customization options for campaigns and notifications.
Users find the learning curve challenging, especially for newcomers, despite helpful documentation for mastering the product.
Users find the pricing structure complicated and expensive, especially with extra costs for advanced features.
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 responsive customer support of Kameleoon, highlighting helpful teams and quick assistance via Slack.
Users find Kameleoon to be a user-friendly platform that simplifies launching experiments and personalizations effectively.
Users value the ease of use and flexibility of Kameleoon for running and analyzing A/B tests.
Users find that developer dependency complicates A/B test setups, often requiring additional support and technical skills.
Users find it challenging to navigate difficult learning curves due to the platform's technical complexities and dependencies.
Users find the learning curve steep due to complex widgets and a WYSIWYG platform that isn’t intuitive.
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 Optimizely Web Experimentation, simplifying experiment management and user insights effectively.
Users appreciate the ease of experimentation with Optimizely, enabling straightforward live testing and clear result tracking.
Users value the customizable personalized UX and superior analytics of Optimizely Web Experimentation, enhancing user understanding and performance.
Users find the learning curve steep for Optimizely Web Experimentation, necessitating prior experience for effective use.
Users find Optimizely Web Experimentation has a difficult learning curve, requiring prior experience for effective use.
Users find the platform to be difficult to use, especially for newcomers lacking prior experience with similar systems.
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 in the Harness Platform facilitates quick implementation and efficient project management.
Users value the scalable architecture of Harness Platform, ensuring consistent results with beneficial features tailored to their needs.
Users appreciate the easy control over features with Harness Platform's feature flags, enhancing testing and rollout processes.
Users note a lack of features in Harness Platform, particularly regarding API management and UI flexibility.
Users experience configuration challenges with customer flags and face limitations in data control and access permissions.
Users find the limited features of Harness Platform challenging, as it lacks essential filtering options and has pending requests.
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.