Emotions drive conversions — and in this episode of Intended Consequences, Brian Massey sits down with Joe Putnam, founder of Conversion Engine, to explore how top-performing ecommerce brands are using AI CRO strategies to scale faster, test better, and connect more deeply with their customers.
You’ll hear how Joe’s team analyzes customer reviews at scale to uncover emotional triggers, how they test ad angles that competitors often miss, and why a “boots that hurt” campaign might not be the golden angle you think it is.
Why Emotions Still Win in Marketing (Even for Practical Products)
“People buy with emotion and justify with logic,” Joe explains — and it’s not just for luxury brands like BMW.
From cowboy boots to baby products, emotional triggers like trust, belonging, pride, and joy show up in customer language all the time. Even in seemingly utilitarian products like closet storage or bathroom scales, people make decisions based on how they feel about the product, not just what it does.
The key is knowing which emotional buttons to push, and that’s where AI CRO strategies come into play.
Finding Emotional Patterns
Sentiment analysis is the process of identifying the emotions behind the words people use — especially in product reviews, support tickets, and social comments.
Traditionally, marketers had to manually scan hundreds of reviews to pick up on these emotional patterns. Today, Joe’s team uses ChatGPT and other AI tools to streamline this process:
“We copy and paste hundreds of reviews into ChatGPT and ask it to do an emotional sentiment analysis,” Joe says. “What problems are being solved? What are people feeling? What language are they using?”
AI CRO strategies like this quickly surface pain points, unique selling propositions, and emotional value statements that can power ad copy, email campaigns, and landing pages.
Building an Emotional Connection
Once the team has pulled emotional themes from the reviews, they organize them into distinct messaging angles — each one reflecting a different emotional trigger. These angles might include:
Trust & security: “I know these will last. Worth every penny.”
Belonging: “I feel like I’m part of a community.”
Confidence: “I walk taller when I wear these boots.”
Joy & reward: “I bought these for myself as a gift. It felt amazing.”
Instead of just running ads that say, “Tired of boots that hurt?” over and over, Joe’s team builds multiple ads targeting different emotional angles. Then, they let the data reveal which message resonates most with the brand’s audience.
Takeaway: You’re probably underutilizing your customer reviews. With the right prompt, AI can uncover 3–5 powerful emotional angles you may have never tested.
Does AI-led Sentiment Analysis Work for All Products?
Yes, even for “boring” or utilitarian products. Joe explains:
“Whether you’re selling cowboy boots or closet storage, you’re always trying to tap into emotion. It might be fear, trust, anxiety, or satisfaction. But emotion is there. And when you find the right one, your results improve.”
Some products might lean into pride or aspiration. Others might connect through relief or peace of mind. In every case, the emotional experience is as important as the feature set.
Why AI Doesn’t Replace the Marketer
Let’s be clear: AI isn’t doing the job for you — it’s helping you do your job better.
Joe emphasizes that AI CRO strategies are a shortcut to better ideas, not a replacement for judgment:
“You still need human intelligence to decide which angles are worth testing, which copy resonates, and which ideas are off-brand. AI gives us more clay to mold — but we still have to be the sculptor.”
AI may generate seven ad angles. But maybe only two of them are good. With a trained marketing team, you can spot the winners, test them faster, and scale what works.
The best ads in the world can fail if the landing page doesn’t match the emotional promise.
One mistake Joe often sees: sending all ad traffic to the same product listing or category page, regardless of the ad’s message.
Instead, he recommends:
Creating custom landing pages for different ad angles.
Reinforcing the same emotional message from ad to landing page.
Using customer language throughout the copy and CTA.
“If the ad is about personal pride or reward, make sure the landing page reflects that. That emotional consistency is what drives higher conversions.”
Mistakes to Avoid with AI and CRO
While AI can be powerful, it’s not infallible. Joe warns of a few key pitfalls:
❌ Mistake 1: Believing Every Insight is Gold
Not every insight generated by AI deserves to be tested. Use your experience and brand knowledge to filter the noise.
❌ Mistake 2: Ignoring the Landing Page
Even strong ads will underperform if the landing page doesn’t deliver on the emotional promise of the creative.
❌ Mistake 3: Over-engineering Prompts
You don’t need “prompt engineering” skills to make this work. Start simple:
“Conduct emotional sentiment analysis on these reviews.”
Let the AI do the heavy lifting — then dig deeper based on what it returns.
Quickstart Guide: How to Use AI in Your Ecommerce Ad Strategy
If you want to try this for your brand, here’s a simple way to get started:
Collect Reviews – Grab 100–200 reviews from your product pages or Amazon listings.
Drop into ChatGPT (or your AI of choice) – Use a prompt like, “Analyze these for emotional sentiment. What feelings are customers expressing? What problems are they solving? What language repeats?”
Extract Emotional Angles – Look for clusters: trust, pride, satisfaction, relief, identity, etc.
Translate into Messaging Pillars – Create 3–5 core messaging angles that represent your product’s emotional impact.
Test in Ads and Landing Pages – Build multiple creatives — each aligned with a different pillar — and track which one drives the most engagement and conversions.
Final Thoughts: Emotions Scale. AI Speeds It Up.
The secret to ecommerce success isn’t just in your product specs. It’s in the emotional response you trigger. And now, thanks to AI, you can discover those responses faster than ever.
As Joe Putnam puts it:
“AI doesn’t give you the final product. But it gets you 80% of the way there — and helps you uncover ideas you wouldn’t find on your own.”
In this episode of Intended Consequences, Brian Massey sits down with Deborah O’Malley, founder of GuessTheTest.com, to explore the fast-changing world of AI in experimentation — from A/B testing myths to the ways AI is already changing how digital marketers approach conversion optimization.
And yes, they really do debate whether AI will kill our creativity.
Deborah pulls no punches: “People are still testing button colors and headlines when they should be testing concepts.”
That’s one of the many interesting misconceptions about experimentation. But as she explains, the most valuable insights come from big, bold tests — especially ones that challenge your brand’s assumptions. And with the arrival of generative AI, we now have the ability to scale those tests like never before.
How AI in Experimentation Is Changing the Game
AI isn’t just writing headlines — it’s redesigning the entire optimization process. Deborah and Brian explore a few critical shifts:
1. Faster Hypothesis Generation
AI can instantly produce dozens of test ideas based on your existing content, analytics, or competitor sites. This helps marketers and CRO pros move from analysis paralysis to active testing — fast.
“You can use AI to brainstorm variations you’d never think of on your own,” Deborah explains. “That means more creative testing… not less.”
2. Pattern Recognition at Scale
While most human optimizers rely on gut instinct or anecdotal evidence, AI can spot trends in user behavior across massive datasets. That means smarter test prioritization, better personalization, and tighter feedback loops.
3. Test Ideas From Outside Your Echo Chamber
AI doesn’t share your brand biases — and that’s a good thing. By using tools like ChatGPT to simulate how different personas react to your copy or design, you can explore radically new angles without waiting for an actual test to finish.
From “Interesting” to “Impactful”
One of Deborah’s boldest claims: We should stop chasing ‘interesting’ test results.
Why? Because what’s interesting isn’t always what moves the needle.
“You want tests that are valid, repeatable, and drive real business results. That’s where AI can help — it brings a level of objectivity and scale that humans alone can’t match.”
In other words, AI in experimentation isn’t replacing us — it’s upgrading us.
Want to Test Better? Start Here.
Whether you’re a CRO veteran or just getting started with testing, this episode is packed with practical insights:
✅ Which A/B tests are still worth running ✅ How to think beyond copy tweaks and start testing experiences ✅ Why generative AI might be your best brainstorming partner ✅ And how to avoid common pitfalls that make test results meaningless
And don’t worry — it’s not all tech talk. Deborah and Brian also cover the human side of experimentation, from internal politics to the fear of failure.
Final Thoughts: Embrace AI in Your Testing Workflow
This episode challenges us to move past the superficial and start building testing programs that matter. Whether you’re optimizing landing pages, ecommerce funnels, or entire customer journeys, AI in experimentation is the lever that can help you scale faster and learn deeper — without sacrificing creativity.
“When used well, AI becomes the co-pilot of every test you run,” Brian says. “It accelerates creativity, supports analysis, and helps you ask better questions — the real key to CRO.”
Here are the 20 top CRO-worthy AB testing software you must consider to help you increase your conversion rates in 2024.
There are a ton of AB testing tools on the market right now, and that number is only going to increase. When evaluating these tools for use in your own business, it can be difficult to wade through the marketing rhetoric and identify exactly which tools are a good fit. That’s why we reached out to our network of CRO specialists in order to bring you a comprehensive look at the best AB testing tools on the market.
Our goal here isn’t necessarily to give you a complete review of each tool, but rather, to show you which split testing tools are preferred by full-time CRO experts — people whose businesses depend completely on the results they are able to deliver to their clients.
At the end of the day, the “right” tool is going to vary depending on the business. As Paul Rouke, former Founder and Director of Customer-Centricity at CX agency PRWD, explains:
We see it time and time again: companies sign up to multi-year contracts for feature rich, enterprise level tools which have a fantastic looking client list, and it ends up burning through their entire CRO budget. Companies invest without considering the need for resource and skills, or they are simply sold on the tool’s ‘ease of use’.
Many companies don’t have the internal skills in place yet to actually utilize this tool, and so the all-singing, all-dancing tool hardly gets used. Also, people using the tool don’t understand the need for or cost of customer research, data, psychology, design, UX principles, etc., meaning they’re ultimately testing the wrong things.
The tools that in my experience deliver the most long-term value are those which are reasonably priced, allowing companies to spend more of their budget on making sure they are testing intelligently and developing an effective testing process.
No tool on this list will be the right fit for every business. That said, without breaking up our list into tiers, we would like to note 4 tools that came up very consistently from the experts we queried.
The two most popular AB testing tools by a wide margin were Optimizely and VWO. These are the most common AB testing tools used by Conversion Sciences clients, and virtually every single expert we chatted with is using both of these tools on a regular basis.
Another two tools that came up on our original poll (in about a third of responses), were Convert Experiences and UsabilityHub. Both of these tools received consistently strong reviews from the experts who used them and fill key needs in the CRO space, which we’ll discuss in their respective entries.
Without further ado, let’s talk a look at our list of recommended AB testing tools.
What We Use at Conversion Sciences
Our use of AB testing tools allows us to do post-test analysis of different segments.
So important is this stack to us that we’ve created a Google Sheets add-on for Google Analytics 4 (GA4).
Most Recommended AB Testing Tools
Now, let’s look at our experts’ recommended options for running AB tests. We’ve listed these in order of frequency with which they were mentioned by our experts. This is not to be confused with a quality ranking.
Optimizely is basically the big kid on campus. It’s our experts’ go-to choice for working with enterprise level clients, and despite the significant price increases over the years, it remains the king.
It’s also reasonably user friendly for such a complex tool, as Shanelle Mullin summarizes:
Optimizely is the leading A/B testing tool by a fairly large margin. It’s easy to use – you don’t need to be technical to launch small tests – and the Stats Engine makes testing easier for beginners.
Here at Conversion Sciences, we use this tool every single day, so I asked them to give me a few thoughts on what they like and dislike about it.
According to the team, Optimizely offers some of the following benefits.
Easy editing access through the dashboard
Retroactive filtering (e.g., IP addresses)
Intuitive data display and goal comparison
Saved Audiences (not available in VWO)
Great integration with 3rd-party tools
AB testing software Optimizely dashboard with AB Test Experiments highlighted and Edit highlighted.
On the flip side, Optimizely is a bit lacking in these ways:
Test setup is not as intuitive compared to other tools
Slow updates for saved changes to the CDN
Doesn’t carry through query params/cookies within a certain test
Targeting is more difficult
Optimizely’s multivariate testing setup is simple and intuitive, and it’s the leading split testing tool for a reason. For businesses with the budget and team to utilize Optimizely to its fullest potential, it is clearly a must-own.
2. VWO
AB Testing Tool VWO Dashboard.
Coming in just behind Optimizely in the AB testing pantheon is Visual Website Optimizer (VWO). VWO is incredibly popular in the marketing space, and in addition to serving as a top choice for businesses with smaller budgets, it is also frequently used in conjunction with Optimizely by businesses who run complex testing campaigns.
Our Conversion Scientists® feel VWO offers some of the following benefits as compared to Optimizely:
More intuitive interface with color coding
Faster updates
Easier goal setup
Easier to download data
Better customer support
On the flip side, VWO is lacking in the following areas:
Can’t view goal reports all at once, which makes them harder to compare
No saved targeting, so you must start fresh with each test unless you clone
No cumulative CR graph if you have low traffic (or what VWO considers low traffic). Instead it gives CR ranges. You must export the data to get any usable information.
This perspective is mostly shared by the ConversionXL team as well, as explained by Shanelle Mullin:
VWO is very easy to use, especially with its WYSIWYG editor. They have something similar to Optimizely’s Stats Engine called Smart Stats, which is based on Bayesian decisions. VWO also offers heatmaps, clickmaps, personalization tools and on-page surveys.
Overall, VWO is in intriguing solo option for smaller to midsized businesses and also works very well in conjunction with Optimizely for enterprise clients.
3. Convert Experiences
AB testing tool Convert Experiences.
While Optimizely and VWO were the tools most commonly mentioned, Convert Experiences received some of the most effusive praise from those who had worked with it.
It seems to have hit a sweet spot for SME/SMBs, combining an exceptional power-to-price ratio with an intuitive interface and highly regarded customer support.
We are platform agnostic, so if our client already has a tool in use, then we try to use that. But in cases where the client has never done any testing before, we typically look first to use Convert (convert.com). I like Convert for a number of reasons. From the very beginning, it has been one of the easiest tools to integrate with Google Analytics. Also, for tricky variations, I’ve had better luck with Convert than others (Optimizely) at getting the variation to display just the way we want. And the support at Convert has always been excellent—again, better than most of their competitors.
We focus on small to medium size clients, and Convert is excellent for that segment with flexible pricing. It’s a great solution for small businesses doing in-house conversion optimization, but it can also work very well for agencies.
– Tom Bowen, Web Site Optimizers
Convert Experiences also stood out as the type of tool that catches new fans wherever it’s discovered, leading me to believe that it will continue to grow and pick up market share.
We have come across convert.com more and more in recent months working on client campaigns. If you are a true marketer and want actionable data then they are a good choice. The user interface is actually pretty good and you can actually understand the data they give you on experiments. They run on the typical drag and drop style experiment setup engine that most others do and can be manipulated even if you aren’t a technical wizard.
The price isn’t too bad either as they fall somewhere in the middle of Optimizely and VWO. I would recommend them to someone who has a bit of budget constraints but wants a bit more testing power. We have used them on multi million dollar per month campaigns with much success.
Convert Experiences is known for having some of the most robust multivariate testing options in it’s class. At the same time, it is also one of the few tools in its class to not offer any sort of email split testing capabilities.
Overall, it’s a highly recommended AB testing tool that is worth trying out.
Convert has great customer support (via live chat) and is easy to use. We’d recommend it to the same people who are considering using Optimizely and VWO.
SiteSpect initially distinguished itself as one of the first server-side testing solutions on the market, and it has remained a top choice for more technically sophisticated users and security-conscious clients.
For a long period, SiteSpect was one of the few platforms offering a server-side solution. This has given them a huge advantage by allowing more complex testing, by adapting to newer JavaScript technologies, and by accommodating security-conscious clients. – Stephen Pavlovich, Conversion
SiteSpect has the advantage that it works in a different way. It’s tag-free. SiteSpect edits the HTML before it even leaves the server, rather than after it has hit the user’s browser. It tends to be popular with companies that want to self-host and are technically sophisticated. – Karl Blanks, Conversion Rate Experts
As a server-side testing solution, SiteSpect avoids many of the issues that can arise with the more typical browser-based testing platforms that utilize javascript tags.
Tag-based solutions typically charge by the number of tag calls you make, even if those tags don’t end up being used.
Tag-based solutions often require third-party cookies, which certain browsers or browser settings might not support, causing you to lose the ability to test a large percentage of traffic.
Tag-based solutions can have imprecise reporting because the javascript doesn’t always fire.
While this value proposition won’t be the deciding factor for many businesses, for those requiring a server-side solution, SiteSpect is one of the best options on the market.
5. AB Tasty
AB testing software ABTasty reports screen capture
AB Tasty is a solution for testing, re-engagement of users, and content personalisation, designed for marketing teams. Paul Rouke had a good bit to say here, so I’ll let him take it away.
The tools that in my experience deliver the most long-term value are those which are reasonably priced, allowing companies to spend more of their budget on making sure they are testing intelligently and developing an effective testing process. I talk about this in-depth in my article The Great Divide Between BS and Intelligent Optimization.
On this note, my favorite tool would be something like AB Tasty, which is priced sensibly, yet has a powerful platform that facilitates a wide range of testing, from simple iterative tests through to innovative tests, along with strategic tests which can help evolve a business proposition and market positioning.
I would recommend AB Tasty (and similarly Convert.com) to the following types of companies:
(1) Companies just starting to invest in conversion optimisation – they won’t break the bank, they won’t overwhelm you with add-ons you will never use as you’re starting out, but they have the capability to match your progress as you scale up your testing output
(2) Companies who have been investing in conversion optimisation but who want to start using a higher portion of their budget (75% or more) on people, skills, process and methodology in order to deliver a greater impact and ROI
(3) Companies frustrated at investing significant amounts of money in enterprise testing platforms, which aren’t being used anywhere near their potential and are taking away from the budget for investing in people, skills and developing an intelligent process for strategic optimisation.
6. Evolv AI
AB testing software Ascend uses machine learning.
Evolv brings advanced machine learning algorithms to the CRO space, helping you identy exactly why your customers aren’t converting, how to fix it, and the potential revenue impact. It was one of the first conversion optimization apps to leverage AI, and it’s becoming exponentially more precise over time.
This is important because it speeds up multivariate testing. Evolutionary, or genetic algorithms do a better job of finding optimum combinations, isolating the richest local maximum for a solution set.
Our team of scientists love being able to assemble our highest rated hypotheses and throw them in the mix to have the machine sort them for us. This really is the future of conversion optimization.
7. Kameleoon
Kameleoon is a web experimentation tool that offers some of the most well-thought-out reporting of any tool we’ve used. They offer features for websites and apps with a dash of AI to identify segments and predict conversions.
Kameleoon makes it easy for our product managers and marketing teams to build experiments. It fits into our tech stack and our existing product release process. Developers get feature flagging and we get to experiment without taking up all their time.
Alexandre Suon, Head of Experimentation, Accor Group
8. Qubit
Testing Platform Qubit Example Screen Capture
Qubit is a testing platform focused primarily on personalization. Accordingly, it has some of the strongest segmentation capabilities of any tool on this list.
Qubit has a strong focus on granular segmentation – and the suite covering analytics through to testing gives it an advantage. They’ve now broken out of their traditional retail focus to become a strong personalisation platform across sectors.
If advanced segmentation or personalization are a priority for your business or clients, Qubit is a tool worth checking out.
9. Adobe Target
AB testing software Adobe Target
Long known for being the most expensive AB testing tool on the market, we’ve found that Adobe Target works best with sites that already use Adobe Analytics.
If your business is already paying for Adobe Analytics, adding Adobe Target is virtually a no-brainer. If your business is not using Adobe Analytics, ignoring Adobe Target is virtually a no-brainer.
I like Adobe Target. The integration of Adobe Analytics and Target is strong – especially being able to push data two-ways. And the fact that Target is normally an inexpensive upsell for Analytics customers is a bonus.
2 Marketing Software Tools With Built-In AB Testing
In addition to dedicated AB testing tools, there are some great marketing software out there that include built-in split testing capabilities. This is fairly common with tools like landing page builders, email service providers, or lead capture solutions.
As Justin Christianson explains, there are some positives and negatives to relying on these built-in tools:
Most page builders out there such as LeadPages and Instapage have split testing capabilities built into their platforms. The problem is you don’t have much control over the goals measured and the adaptability to test more complex elements. The good thing is they are extremely easy to setup and use for those quick and dirty type tests. I recommend the use of this to just get some tests up and running, as constantly testing is extremely important. If you are currently using a platform with these native testing capabilities then this is a good place to start.
1. Unbounce
One particular tool that was highlighted by several of our experts was Unbounce, one of the web’s more popular landing page builders.
I also like Unbounce, and not just because I like Oli Gardner. It seems most everyone there lives and breathes landing pages, so the expertise that comes with the tool is virtually unmatched. Their support is also excellent. Unbounce works really well when we’re creating a new landing page from scratch and want to try different variations, since it’s so easy to create brand new pages using the tool.
Unbounce is an excellent tool for A/B testing your landing pages. While many landing page tools also offer A/B testing, I think Unbounce has the best and most flexible page editor when creating variations of your pages to be tested, and their landing page templates have the most CRO best practices included already.
Unbounce is outstanding for online marketing teams that want the most flexibility when creating and A/B testing their landing pages – many other landing page tools are limited to a fixed grid system which makes it much harder to make changes.
Another popular tool was OptinMonster, which began as a popular popup tool and has evolved into a more fully featured lead generation software.
Optin Monster is an outstanding tool that lets you easily A/B test visitor opt-in incentives to see which converts best – not only headlines, images and CTAs, but also which types perform best (like a discount versus a free guide). In particular it offers great customization options and many popup styles, and exit intent popups.
Optin Monster is particularly useful for the many website marketers who don’t have enough traffic to do formal A/B testing (using tools like Optimizely or VWO) but still want to get a better idea of their best performing content variations. It has great pricing options suitable for online businesses on a low budget.
– Rich Page
12 Tools For Gathering Data
As every good split tester knows, your AB tests are only as good as the hypotheses you are testing. The following tools represent our experts’ favorite choices for collecting data to fuel effective AB tests.
UsabilityHub was by far the most frequently mentioned analytics tool by our group of CRO experts. UsabilityHub is a collection of 5 usability tests that can be administered to visitors in order to collect key insights.
UsabilityHub is great for clarity testing and getting quick indications of potential improvements. It is also great for uncovering personal biases in the creation of page variations. I would recommend it to anyone doing conversion optimization or even basic usability testing.
While many of the tools on this list deal primarily with quantitative data, UsabilityHub offers uniquely efficient ways to collect valuable qualitative data.
Once I’ve identified underperforming pags, the next step is to figure out what’s wrong with those pages by gathering qualitative data. For top landing pages, including the homepage, I like to run one of UsabilityHub’s “5 Second Tests” to gauge whether people understand the product or service offered. The first question I always ask is “what do you think this company sells?”. I’ve gotten some surprisingly bad results, where large numbers of respondents gave the wrong answer. In these cases, running a simple A/B test on a headline and/or hero shot to clarify what the company does is an easy win.
It also can be a cost-effective alternative if your website doesn’t get enough traffic to facilitate use of an actual split testing tool.
UsabilityHub is essential if you want to do A/B testing but your website doesn’t have enough traffic to do so. Instead it enables you to show your proposed page improvements to testers (including your visitors) to get their quick feedback, particularly using the highly useful ‘Question Test’ and ‘Preference Test’ features.
UsabilityHub can be particularly useful for the many website marketers who don’t have enough traffic to do formal A/B testing (using tools like Optimizely or VWO) but still want to get a better idea of their best performing content variations.
– Rich Page
2. Google Analytics
Analytics platform Google Analytics Screen Capture
To the surprise of exactly no one, Google Analytics was high up on the list of recommended analytics tools. Yet despite its popularity, very few marketers or business owners are using this free tool to its full potential.
Theresa Baiocco makes the follow recommendations for getting started:
There’s so much data in Google Analytics that it’s easy to suffer from paralysis by analysis. It helps to have a few reports you use regularly and know what you’re looking for before jumping in. The obvious reports for finding the most problematic pages in your funnel are the funnel visualization and goal flow reports. But I also like to look at top landing pages, and using the “comparison” view, I see which of them have higher bounce rates than average for the site. Those 3 reports together are a good starting point for identifying which pages to work on first.
When it comes to applying Google Analytics to your AB testing efforts, John Ekman of Conversionista offers some advice:
Most of the AB testing tools provide an easy integration with Google Analytics. Do not miss this opportunity in your AB testing setup!
When you integrate your testing tool with GA it means that you will be able to break down your test results and look at A vs. B in all dimensions available in GA. You will be able to see behavior segmented by device, returning vs new visitors, geography etc.
For example: if you are using Enhanced Ecommerce setup for GA you will be able to compare your E-commerce funnel for the A version vs. the B version. Maybe the A version gets more add to carts, but then that effect withers off and the result in the checkout is the same?!
Example of Google Analytics ecommerce report for AB test variation.
Word of warning: as soon as you start segmenting your data you might lose statistical significance in the underlying segments. Even if your AB test results are statistically significant on the overall level that does not mean that the deviations you see in smaller segments of your test data are significant. The smaller the data sample size, the harder it is to reach significance. What you think is a strong signal is just some data noise.
User intelligence tool Crazy Egg confetti report screen capture.
Crazy Egg is one of the more popular heatmap and click-tracking tools online, thanks to an attractive interface, an affordable price point, and a deceptively powerful feature set.
Our Conversion Scientists not only use Crazy Egg, we highly recommend it. Here’s what they says about it:
Crazy Egg offers tools to help you visually identify the most popular areas of your page, help you see which parts of your pages are working and which ones are not, and give you greater insight as to what your users are doing on your pages via both mobile and desktop sites.
4. UserTesting.com
User testing platform UserTesting.com
UserTesting.com is a unique service that provides videos of real users in your target market experiencing your site and talking through what they’re thinking.
This service is recommended by Craig Andrews, who had the following to say:
UserTesting.com is great for hypothesis generation and uncovering personal biases. It is an absolutely fantastic tool for persuading clients on the reality and importance of certain site issues, and I would recommend it to anyone doing conversion optimization or even basic usability testing
5. UserZoom (formerly Validately)
UserZoom user testing video.
UserZoom provides a complete online user testing service.
For a somewhat less expensive alternative to UserTesting.com we have found UserZoom to be an effective solution. The quality of the panel members is good, and their panel is large enough that user tests are completed quickly.
6. ClickTale
Heatmapping and session recording tool ClickTale dashboard
Clicktale is a cloud-based analytic system that allows you to visualize your customer’s experience on your website from their perspective. It’s an enterprise-level tool that combines session recording with click and scroll tracking, and while it comes with an enterprise price tag, it’s made some significant quality strides over the last few years.
There has been a huge improvement in Clicktale over the past three years, in tracking, reporting and accuracy. If you want “any old session recording JS”, boxed-product application out there, there are a variety of options. If you want accurate rendering that is linked to your existing analytics and a company that will help you tune as your own website evolves, then Clicktale is a good choice. It’s the one I’ve chosen as I wouldn’t want to risk the privacy of my customers or risk degrading the performance of my website. Clicktale also gives me a representative sample that is accurate by resolution and responsive design.
7. Hotjar
Hotjar offers heatmap reports, session recordings, polls, surveys and more.
HotJar is a jack of all trades type tool: an all-in-one tool that does heatmaps, scroll tracking, recordings, funnel tracking, form analysis, feedback polls, surveys, and more.
And from what a few of our Conversion Scientists have seen so far, it does all of those things about as well as you would expect from a jack of all trades.
On the plus side, Hotjar has prioritized creating an exceptional user experience, so if you are a solo blogger wanting a feature-rich, easy-to-use toolkit in one place with a reasonable price tag, Hotjar might be the perfect choice for you.
Stephen Esketzis had the following to say about his experience with the tool:
So overall, HotJar really is a great tool with a lot of value to offer any online business (or website in general at that). There’s not many businesses that work online I wouldn’t recommend this tool to.
With a no-brainer price point (and even a free plan) it’s pretty hard to go wrong.
8. Mouseflow
Mouseflow is another Swiss army knife of user intelligence. The service bundles screen recording, heatmap reports, on-site surveys, funnel tracking and form analysis.
Mouseflow user behavior analytics tool.
We like it because it provides advanced segmentation. Filters include traffic source, platform, location, and more. It also supports segmentation by custom variables.
On the Intended Consequences podcast, Evan Hill said of the power of data:
“So I would I think that’s one of the most exciting things for a marketer who finally grabs this tool installs it, because they’re about to get the data they need to have really really interesting meetings.”
9. Inspectlet
Session recording software Inspectlet.
Inspectlet is primarily a session recording tool with additional heatmaps as well. Here’s what Anders Toxboe had to say about it in a recent review:
Inspectlet is simple to use. It gets out of the way in order to let the user do what he or she needs. The simple funnel analysis and filtering options is a breeze to use and covered my basic needs.Inspectlet does what it does good with a few minor glitches. It doesn’t have the newer features that have started appearing lately such as watching live recordings, live chatting, surveys, and polls.
In other words, Inspectlet is an easy-to-use, budget-friendly session recording tool that might be right for you depending on your needs.
10. SessionCam
Session recording software SessionCam offers a Suffer Score.
SessionCam is a session recording tool that has also added heatmaps form analytics to its offering. It’s a classic example of a tool that combines better-than-average functionality with a more-difficult-than-average user interface.
SessionCam provides a lot of useful functionality, but its user interface isn’t the easiest to learn or use. Getting the most out of it requires a nontrivial investment of time.
And later:
UX designers have long known that, where there is internal resistance to change, showing stakeholders clear evidence of users experiencing problems can be a powerful tool in persuading them to recognize and address issues. SessionCam meets the need for a tool that provides this data in a much more dynamic, cost-effective way than using traditional observation techniques.
SessionCam [also] manages [to protect user data] effectively by masking the data that users enter into form fields, so you can put their concerns to rest.
If you are looking for a more robust session recording and form analytic tool that keeps user data safe, SessionCam is worth checking out.
11. Lucky Orange
Lucky Orange is kind of like Crazy Egg with a bit of UserTesting.com, a bit of The Godfather, and a bit of a hundred other things. It’s a surprisingly diverse package of conversion features that make you start to believe their claim as “the original all-in-one conversion optimization suite”, despite the incredibly low price point.
Despite the hundred new tools that have popped up since Lucky Orange hit the market, Theresa Baiocco still swears by the original:
No testing program is complete without analyzing how users behave on the site. Optimizers all have their favorite tools for gathering this data, and while the newest and hottest kid on the block is Hotjar, I still like using my old go-to: Lucky Orange. Starting at just $10/month, Lucky Orange gives you visitor recordings, conversion funnel reports, form analytics, polls, chat, and heat maps of clicks, scroll depth, and mouse movements – all in one place.
12. Adobe Analytics
Analytics platform Adobe Analytics site overview.
Adobe Analytics is a big data analysis tool that helps CMOs understand the performance of their businesses across all digital channels. It enables real time web, mobile and social analytics across online channels, and data integration with offline and third-party sources.
In other words, Adobe Analytics is a $100k+ per year, enterprise level analytics tool that has some serious firepower. Here’s what David Williams of ASOS.com had to say about it:
After a thorough review of the market, we chose Adobe Analytics to satisfy our current and future analytics and optimization needs. We needed a solution that could scale globally with our business, improve productivity, and offer out-of-the box integration with our key partners to deliver more value from our existing investments. Adobe’s constant pace of innovation continues to deliver value for our business, and live stream (the event firehose) is the latest capability that opens up exciting opportunities for how we engage with customers.
AB Testing Tools Conclusion
Well that’s that: 20 of the most recommended AB testing tools from a diverse collection of the web’s leading CRO experts.
Have you used any of these tools before? Do you have a favorite that wasn’t included? We’d love to hear your thoughts in the comments.
And if you are looking for a quick way to calculate how a conversion lift could increase your bottom line, be sure to check out our Optimization Calculator.
Discover how AI marketing tools truly work and find the answer to the question: Can they really increase your website’s conversion rates?
Do you know how machine learning is impacting conversion rate optimization for marketers? We all know what the acronym “AI” stands for: “As If”. Data scientists are telling us that by using AI, they’ll will be able to create a predictive model of the visitors to your website that will tell you exactly who is ready to buy.
I say, “As if.”
We may marvel that such things can be done, but we also recognize that these things require a great deal of data and the skills of some serious brainiacs to get a machine to tell us something we don’t already know.
The truth is, you are probably already using “AI”, or more accurately, machine learning in your marketing. It’s hiding in the tools we use, like monsters under our bed. Machine learning and the more sciencey-sounding AI will change the way you take products to market, but your human mind will still be needed and loved.
Things like AI-driven predictive models are exciting, because our job as marketers is to predict the future. We’re like that exotic fortune teller gazing into an empty tea cup or a crystal ball.
We say things like, “If you give me a budget, I’ll generate six times that amount in revenue.” This is is like saying, “If you put a chicken foot under your pillow, you will find true love.” As if.
But this is what we do, and the data on which we base our predictions is often no more valid than the layout of tea leaves at the bottom of a cup. Our brains are wired to find patterns in anything, even when a pattern isn’t really there.
If I came into your office and said, “The last three leads we generated were all visiting the website using a Firefox browser,” your brain would jump to the conclusion, “If I can get more Firefox users to visit our website, I’ll generate tons of leads.”
Do AI marketing tools impact your website conversion rates?
Purveyors of AI, or more accurately Machine Learning (ML), would tell us that the machine doesn’t make mistakes like this. Our 100% genuine intelligence just doesn’t stack up to their Artificial Intelligence.
The problem is that machines will make exactly the same mistake if we don’t give them lots of data.
Just as machines need data, we know that we need more data before we start an ad campaign targeting Firefox users. We’ll ask our analytics person to pull together all website visits for the last year, and calculate the conversion rate for each. This increases the size of our dataset from three to many.
If this analysis goes the way of most analyses, we’ll find that there’s not a meaningful difference in conversion rates among browsers. Most experiments end up being inconclusive. That’s just the way it is.
In this scenario, we “wasted” an hour of our data scientist’s time, an hour of our time, and another twenty minutes explaining to our boss why we were so unproductive today.
“What if,” the AI crowd says, “you could get a machine to sort through your data looking for clues and figuring out who’s more likely buy. You don’t have to waste your time. Let the machine do it.”
This is an exciting proposition. The machine wouldn’t just look at the browser. It would look at the time of day, day of week, and week of the year that visitors converted. It could consider the device being used, screen size and operating system. It could add in the source of the visit, the number of times a visitor has been to the website, and whether the visitor has bought before.
After crunching through all of your analytics data, the machine would give you a percentage chance that the next visitor to your website will convert. And here comes a person with a Safari browser on a Mac computer at 3:30pm EST on a warm Tuesday afternoon who’s never been to the site before.
The machine might spit out, “There is a 51% chance this person will complete the lead form.” Actually, the machine will just say, “0.51”. Machines are so boring.
It’s amazing that a machine can so accurately predict a human being’s behavior. This is incredible.
But, is 51% good? And if this is true, what should my website do differently to make this Safari visitor more likely to buy? Do I reduce the price by 49%? Do I flatter this visitor for being above average? Do I ignore them?
This is “the rub” with machine learning. The machine can’t tell us what to do with the data it gives us. There are systems that will tell us if a visitor is “at the top of the funnel” or “in the consideration phase.” Still, what do we do with that? A price-sensitive buyer may want to see a discount when “at the top” of their purchase process. A relational buyer may not care about discounts until they’re “at the bottom,” ready to buy.
The machine won’t tell us, “Target Internet Explorer visitors coming late at night on a Windows computer during the springtime months with a picture of a cat.” It spits out the probability for each visit: “0.51, 0.34, 0.71, 0.92”.
Wait! A 92% probability? Is that important!? Well, no. They’re probably going to buy no matter what we do. “As if.”
AI-Driven Results
Scoring customers in a customer relationship management (CRM) platform has required that marketers hand-code the algorithm. We decide which actions indicate that a prospect is moving closer to buying. We decide how to value each action. It can work, but it isn’t rocket science – or AI.
Alternatively, we can dump sales data into a machine learning algorithm and let it calculate the probability that each prospect will turn into a customer. The sales force can focus on those high-probability clients and disregard the low-scoring leads. It’s using past performance to predict the future, and should be more accurate than arbitrary assignment of values to actions.
This is how machine learning is entering your life as a marketer.
AI Conversion Rate Optimization: Can AI Marketing Tools Increase Your Website’s Conversion Rates?
Amazon famously introduced product suggestions to the eCommerce world. “People who bought this also bought that and that and that.”
It’s not an easy problem to solve. There are a lot of variables to crunch and it has to be done quickly. This is a prime area for AI.
Mailchimp launched a similar tool to add product suggestions to the emails of its eCommerce clients. Every time you send an email to someone, Mailchimp will include a few product suggestions at the bottom of the email. The machine learning algorithm will compute the probability that one or more products will appeal to a subscriber, based on the behavior of all email recipients. Those products with the highest probability get added to the email. This prompts the visitor to buy.
As if.
It’s hard to know how well the machine has learned what your visitors buy collectively. This is the limitation of AI. We can’t really see what is inside the box. All we get is a number.
If you implement a suggestion engine on your website, we recommend running an A/B test to measure its effectiveness. This is done by adding the “Also bought” suggestions for half the visitors and hiding it for the other half. This will give us some conclusive data about how the suggestion AI is performing. Is it increasing the order size on average, or reducing it?
