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• CRO Testing : The 6-Steps for Maximising Conversion Rates

  10 mars, par Erin

  It’s a nightmare every marketing manager faces. Traffic is soaring after you’ve launched new digital marketing campaigns, but conversions have barely moved.

  Sound familiar ?

  The good news is you’re not alone — loads of marketing managers struggle to get potential customers to purchase. The better news is that you can test dozens of strategies to turn around your site’s fortunes. 

  Conversion rate optimisation testing (CRO testing for short) is the name for this kind of experimentation — and it can send conversion rates and revenue soaring.

  In this article, we’ll explain CRO testing and how you can start doing it today using Matomo. 

  What is CRO Testing ? 

  CRO testing is optimising your site’s conversion funnel using a series of experiments designed to improve conversion rates.

  A CRO test can take several forms, but it usually involves changing one or more elements of your landing page. It looks something like this :

  1. You hypothesise what you expect to happen.
  2. You then run an A/B test using a dedicated CRO platform or tool.
  3. This tool will divide your site’s traffic, sending one segment to one variation and the other segment to another.
  4. The CRO tool will measure conversions, track statistical significance, and declare one variation the winner. 

  A CRO tool isn’t the only software you can use to gather data when running tests. There are several other valuable data sources, including :

  • A web analytics platform : to identify issues with your website
  • User surveys : to find out what your target audience thinks about your site
  • Heatmaps : to learn where users focus their attention
  • Session recordings : to discover how visitors browse your site

  Use as many of these features, tools, and methods as you can when brainstorming hypotheses and measuring results. After all, your CRO test is only as good as your data.

  On that note, we need to mention the importance of data accuracy when researching issues with your website and running CRO tests. If you trust a platform like Google Analytics that uses data sampling (where only a subset of data is analysed), then there’s a risk you make business decisions based on inaccurate reports.

  In practice, that could see you overestimate the effectiveness of a landing page, potentially wasting thousands in ad spend on poorly converting pages. 

  That’s why over a million websites rely on Matomo as their web analytics solution—it doesn’t sample data, providing 100% accurate website traffic insights you can trust to make informed decisions.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Types of CRO Testing 

  There are three core types of CRO tests :

  A/B testing

  A/B testing, or split testing, is when you test two versions of the same page against each other. Usually, the two pages have only one difference, such as a new headline or a different CTA. 

  

  In the test above, for example, we test what happens if we remove one of the affiliate links from a page. We hypothesise that conversions won’t change because these links aren’t effective.

  A/B/n testing

  A/B/n testing is when you test multiple variations of the same element on the same page. 

  Rather than just testing one headline against another, for example, you test multiple different headlines at once.

  

  In the test above in Matomo, we’re testing a website’s original header against a wider and smaller version. It turns out the wider header converts significantly better. 

  Multivariate testing

  In a multivariate CRO test, you test multiple different elements at the same time. That could mean testing combining a different headline, CTA button, and image. 

  Multivariate testing can save time because you test multiple elements at once and find the best combination of elements. But you’ll usually need a lot of traffic to find a statistically significant result.

  Why is CRO testing important ?

  Who doesn’t want more conversions, right ? Improving your conversion rate is the core benefit of running a CRO test, but there are a couple of other reasons you should do it, too :

  

  Improve conversion rates

  How well does your website convert visitors ? The average conversion rate of a typical website is 2.35%, but better-performing websites have significantly higher conversion rates. The top 25% of websites across all industries convert at a rate of 5.31% or higher.

  CRO testing is the best way to improve your site’s conversion rate by tweaking elements of your website and implementing the best results. And because it’s based on data, not your intuition, you’re likely to identify changes that move the needle. 

  Optimise the user experience

  CRO tests are also a great way to improve your site’s user experience. The process of CRO testing forces you to understand how users navigate your website using heatmaps and session recordings and fix the issues they face. 

  You could simplify your form fields to make them easier to fill in, for example, or make your pages easier to navigate. In both cases, your actions will also increase conversion rates.

  Decrease acquisition costs

  Improving your conversion rate using CRO testing will usually mean a decrease in customer acquisition costs and other conversion metrics. 

  After all, if the cost of your PPC ads stays the same but you convert more traffic, then each new customer will cost less to acquire.

  How to do CRO testing in 6 steps 

  Ready to get your hands dirty ? Follow these six steps to set up your first CRO test :

  Have a clear goal

  Don’t jump straight into testing. You need to be clear about what you want to achieve ; otherwise, you risk wasting time on irrelevant experiments. 

  If you’re unsure what to focus on, look back through your web analytics data and other tools like heatmaps, form analytics, and session recordings to get a feel for some of your site’s biggest conversion roadblocks. 

  Maybe there’s a page with a much lower conversion rate, for example — or a form that most users fail to complete. 

  If it’s the former, then your goal could be to increase the conversion rate of this specific landing page by 25%, bringing it in line with your site’s average. 

  

  Make sure your new conversion goal is set up properly in your website analytics platform, too. This will ensure you’re tracking conversions accurately. 

  Set a hypothesis

  Now you’ve got a goal, it’s time to create a hypothesis. Based on your available research, a hypothesis is an assumption you make about your conversion rate optimisation test.

  A heatmap of your poorly converting landing page may show that users aren’t focusing on your CTA button because it’s hidden below the fold. 

  You could hypothesise that by placing the CTA button directly under your headline above the fold, your conversion rate should increase. 

  Whatever your goal, you can use the following template to write a hypothesis :

  If we [make this specific change], then [this specific outcome] will occur because [reason].

  Design your test elements

  Most marketing managers won’t be able to run CRO tests independently. A team of talented experts must create the assets you need for a successful experimentation. This includes designers, copywriters, and web developers. 

  Don’t just have them create one new element at a time. Accelerate the process by having your team create dozens of designs simultaneously. That way, you can run a new CRO test as soon as your current test has finished. 

  Create and launch the test

  It’s time to launch your test. Use a CRO tool to automate building your test and tracking results. 

  With Matomo’s A/B Testing feature, it’s as easy as giving your test a name, writing a hypothesis and description, and uploading the URLs of your page variants.

  

  Matomo handles everything else, giving you a detailed breakdown at the end of the test with the winning variant. 

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  Analyse the results

  You can only review the results of your CRO test once it has reached statistical significance — which means the observed outcome isn’t the result of chance.

  In the same way you wouldn’t say a die is unbiased after three rolls, you need thousands of visitors to see your landing pages and take action before deciding which is better. 

  Luckily, most CRO testing platforms, including Matomo, will highlight when a test reaches statistical significance. That means you only need to look at the result to see if your hypothesis is correct. 

  Implement and repeat

  Was your test a success ? Great, you can implement the results and test a new element. 

  Yep, that’s right. There’s no time to rest on your laurels. Continuous CRO testing is necessary to squeeze every conversion possible from your website. Just like fashion trends, website effectiveness changes over time. What works today might not work tomorrow, making ongoing CRO testing beneficial and necessary.

  That’s why it’s a good idea to choose a CRO testing platform like Matomo with no data limits.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  CRO testing examples you can run today 

  There’s no shortage of CRO tests you can run. Here are some experiments to get started with :

  Change your CTA design and copy

  Calls to action (CTAs) are the best elements to optimise during your first CRO test. You can change many things about them ; even the smallest optimisation can have a huge impact. 

  Just take a look at the image below to see how diverse your CTAs could be :

  

  Changing your CTA’s copy is a great place to start, especially if you have generic instructions like “Apply Now.”

  Try a more specific instruction like “Download your free trial” or “Buy now to get 30% off.” Or test benefit-led instructions like “Reduce your ad spend today” or “Take back control of your data.”

  Changing the colour of your CTAs can also yield more conversions. Bright colours are always a good bet. Just make sure your button stands out from the rest of your page. 

  Move the CTA button placement

  The placement of your CTA can be just as important as its copy or colour. If it’s down at the bottom of your page, there’s a good chance most of your visitors will miss it. 

  Try moving it above the fold to see if that makes a difference. Then, test multiple CTA buttons as opposed to just one. 

  Heatmaps and session recordings can identify whether this test is worthwhile. If users rarely focus on your CTA or just don’t scroll far enough to find it, then it’s a good bet you could see an uptick in conversions by moving it. 

  Try different headlines

  Your website’s headlines are another great place to start CRO testing. These are usually the first (and sometimes only) things visitors read, so optimising them as much as possible makes sense. 

  There are entire books written about creating persuasive headlines, but start with one of the following tactics :

  • Include a benefit
    • “Achieve radiant skin—discover the secret !”
  • Add numbers
    • “3 foolproof methods for saving money on your next vacation”
  • Using negative words instead of positive ones
    • “Avoid these 7 mistakes to unlock your potential for personal growth”
  • Shortening or lengthening your headline
    • Shortened : “Crush your fitness goals : Expert tips for success”
    • Lengthened : “Embark on your fitness journey : Learn from experts with proven tips to crush your wellness goals”

  Add more trust signals

  Adding trust signals to your website, such as brand logos, customer reviews, and security badges, can increase your conversion rate.

  We use it at Matomo by adding the logos of well-known clients like the United Nations and Amnesty International underneath our CTAs.

  

  It’s incredibly effective, too. Research by Edelman finds that trust is among the top three most important buying decision factors, above brand likeability.

  Start CRO testing with Matomo

  CRO testing is a data-backed method to improve your site’s conversion rate, making it more user-friendly and decreasing customer acquisition costs. Even a small improvement will be worth the cost of the tools and your time. 

  Fortunately, there’s no need to allocate hundreds of dollars monthly for multiple specialised testing tools. With Matomo, you get a comprehensive platform offering web analytics, user behaviour insights, and CRO testing – all conveniently bundled into one solution. Matomo’s pricing starts from just $19 per month, making it accessible to businesses of all sizes.

  Plus, rest assured knowing that you are GDPR compliant and the data provided is 100% accurate, ethically empowering you to make informed decisions with confidence.

  Take the first step on your CRO testing journey by trying Matomo free for 21 days ; no credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• Multivariate Testing vs A/B Testing (Quick-Start Guide)

  7 mars, par Erin

  Traditional advertising (think Mad Men) was all about slogans, taglines and coming up with a one-liner that was meant to change the world.

  But that type of advertising was extremely challenging to test, so it was hard to know if it worked. Most of the time, nobody knew if they were being effective with their advertising.

  Enter modern marketing : the world of data-driven advertising.

  Thanks to the internet and web analytics tools like Matomo, you can quickly test almost anything and improve your site.

  The question is, should you do multivariate testing or A/B testing ?

  While both have their advantages, each has a specific use case.

  In this guide, we’ll break down the differences between multivariate and A/B testing, offer some pros and cons of each and show you some examples so you can decide which one is best for you.

  What is A/B testing ?

  A/B testing, or split testing, is testing an individual element in a medium against another version of the same element to see which produces better results.

  

  A/B tests are conducted by creating two different versions of a digital landmark : a website, landing page, email, or advertisement.

  The goal ? Figure out which version performs better.

  Let’s say, for example, you want to drive more sales on your core product page.

  You test two call-to-action buttons : “Buy Now” and “Add to Cart.”

  After running the test for two weeks, you see that “Buy Now” produced 1.2% conversions while “Add to Cart” produced 7.6%.

  In this scenario, you’ve found your winner : version B, “Add to Cart.”

  By conducting A/B tests regularly, you can optimise your site, increase engagement and convert more visitors into customers.

  Keep in mind that A/B testing isn’t perfect ; it doesn’t always produce a win.

  According to Noah Kagan, founder of AppSumo, only 1 out of 8 A/B tests his company conducts produces significant change.

  Advantages of A/B testing

  A/B testing is great when you need to get an accurate result fast on a specific element of your marketing efforts.

  Whether it’s a landing page or product page, you can get quick results without needing a lot of traffic.

  A/B testing is one of the most widely accepted and used testing methods for marketers and business owners.

  When you limit the number of tracked variables used in a test, you can quickly deliver reliable data, allowing you to iterate and pivot quickly if necessary.

  This is a great way to test your marketing methods, especially if you’re a newer business or you don’t have substantial traffic yet.

  Splitting up your traffic into a few segments (like with multivariate testing) will be very challenging to gain accurate results if you have lower daily traffic.

  One final advantage of A/B testing is that it’s a relatively easy way to introduce testing and optimising to a team, decision-maker, or stakeholder since it’s easy to implement. You can quickly demonstrate the value with a simple change and tangible evidence.

  Disadvantages of A/B testing

  So, what are the downsides to A/B testing ?

  Although A/B testing can get you quick results on small changes, it has limitations.

  A/B testing is all about measuring one element against another.

  This means you’re immediately limited in how many elements you can test. If you have to test out different variables, then A/B testing isn’t your best option since you’ll have to run test after test to get your result.

  If you need specific information on how different combinations of elements interact with one another on a web page, then multivariate is your best option.

  What is multivariate testing ?

  If you want to take your testing to the next level, you’ll want to try multivariate testing.

  Multivariate testing relies on the same foundational mechanism of A/B testing, but instead of matching up two elements against one another, it compares a higher number of variables at once.

  Multiple + variations = multivariate.

  Multivariate testing looks at how combinations of elements and variables interact.

  Like A/B testing, traffic to a page is split between different web page versions. Multivariate testing aims to measure each version’s effectiveness against the other versions.

  Ultimately, it’s about finding the winning combination.

  

  When to use multivariate testing

  The quick answer on when to use multivariate testing is if you have enough traffic.

  Just how much traffic, though ?

  While there’s no set number, you should aim to have 10,000 visitors per month or more, to ensure that each variant receives enough traffic to produce meaningful results within a reasonable time frame.

  Once you meet the traffic requirement, let’s talk about use cases.

  Let’s say you want to introduce a new email signup.

  But you want to create it from scratch and aren’t sure what will make your audience take action.

  So, you create a page with a signup form, a header, and an image.

  To run a multivariate test, you create two lengths of signup forms, four headlines, and two images.

  Next, you would create a test to split traffic between these sixteen combinations.

  Advantages of multivariate testing

  If you have enough traffic, multivariate testing can be an incredible way to speed up your A/B testing by testing dozens of combinations of your web page.

  This is handy when creating a new landing page and you want to determine if specific parts of your design are winners — which you can then use in future campaigns.

  Disadvantages of multivariate testing

  The main disadvantage of multivariate testing is that you need a lot of traffic to get started.

  If you try to do a multivariate analysis but you’re not getting much traffic, your results won’t be accurate (and it will take a long time to see accurate data).

  Additionally, multivariate tests are more complicated. They’re best suited for advanced marketers since more moving parts are at play.

  Key differences between multivariate and A/B testing

  Now that we’ve covered what A/B and multivariate tests are, let’s look at some key differences to help clarify which is best for you.

  

  1. Variation of combinations

  The major difference between A/B and multivariate testing is the number of combinations involved.

  With A/B testing, you only look at one element (no combinations). You simply take one part of your page (i.e., your headline copy) and make two versions.

  With multivariate testing, you’re looking at combinations of different elements (i.e., headline copy, form length, images).

  2. Number of pages to test

  The next difference lies in how many pages you will test.

  With an A/B test, you are splitting traffic on your website to two different pages : A and B.

  However, with multivariate testing, you will likely have 4-16 different test pages.

  This is because dozens of combinations can be created when you start testing a handful of elements at once.

  For example, if you want to test two headlines, two form buttons and two images on a signup form, then you have several combinations :

  • Headline A, Button A, Image A
  • Headline A, Button A, Image B
  • Headline A, Button B, Image A
  • Headline A, Button B, Image B
  • Headline B, Button A, Image A
  • Headline B, Button A, Image B
  • Headline B, Button B, Image A
  • Headline B, Button B, Image B

  In this scenario, you must create eight pages to send traffic to.

  3. Traffic requirements

  The next major difference between the two testing types is the traffic requirements.

  With A/B testing, you don’t need much traffic at all.

  Since you’re only testing two pages, you can split your traffic in half between the two types.

  However, if you plan on implementing a multivariate test, you will likely be splitting your traffic at least four or more ways.

  This means you need to have significantly more traffic coming in to get accurate data from your test. If you try to do this when your traffic is too low, you won’t have a large enough sample size.

  4. Time requirements

  Next up, just like traffic, there’s also a time requirement.

  A/B testing only tests two versions of a page against each other (while testing a single element). This means you’ll get accurate results faster than a multivariate test — usually within days.

  However, for a multivariate test, you might need to wait weeks. This is because you’re splitting your traffic by 4, 8, 12, or more web page variations. This could take months since you need a large enough sample size for accuracy.

  5. Big vs. small changes

  Another difference between A/B testing and multivariate testing is the magnitude of changes.

  With an A/B test, you’re looking at one element of a page, which means changing that element to the winning version isn’t a major overhaul of your design.

  But, with multivariate testing, you may find that the winning combination is drastically different than your control page, which could lead to a significant design change.

  6. Accuracy of results

  A/B tests are easier to decipher than multivariate testing since you only look at two versions of a single element on a page.

  You have a clear winner if one headline yields a 5% conversion rate and another yields a 1.2% conversion rate.

  But multivariate testing looks at so many combinations of a page that it can be a bit trickier to decipher what’s moving the needle.

  Pros and cons : Multivariate vs. A/B testing

  Before picking your testing method of choice, let’s look at some quick pros and cons.

  

  A/B testing pros and cons

  Here are the pros and cons of A/B testing :

  Pros

  • Get results quickly
  • Results are easier to interpret
  • Lower traffic requirement
  • Easy to get started

  Cons

  • You need to be hyper-focused on the right testing element
  • Requires performing test after test to optimise a web page

  Multivariate testing pros and cons

  Here are the pros and cons of multivariate testing :

  Pros

  • Handy when redesigning an entire web page
  • You can test multiple variables at once
  • Significant results (since traffic is higher)
  • Gather multiple data insights at once

  Cons

  • Requires substantial traffic
  • Harder to accurately decipher results
  • Not as easy to get started (more advanced)

  Use Matomo to start testing and improving your site

  

  You need to optimise your website if you want to get more leads, land more conversions and grow your business.

  A/B testing and multivariate testing are proven testing methods you can lean on to improve your website and create a better user experience.

  You may prefer one testing method now over the other, and that’s okay.

  The main thing is you’re starting to test. The best marketers and analysts in the world find what works through testing and double down on their winning tactics.

  If you want to start improving your website with testing today, get started with Matomo for free.

  With Matomo, you can conduct A/B tests and multivariate tests easily, accurately, and ethically. Unlike other web analytics tools, Matomo prioritises privacy, providing
  100% accurate data without sampling, and eliminates the need for cookie consent
  banners (except in the UK and Germany).

  Try Matomo free for 21-days. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

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• Encoding AV1 to h264 error : Assertion pkt failed at D :/code/ffmpeg/src/fftools/ffmpeg_dec.c:518 [closed]

  1er mars, par KyonGiang

  I used below code to convert from AV1 to x264 mp4, and I got error message : "Assertion pkt failed at D :/code/ffmpeg/src/fftools/ffmpeg_dec.c:518"

  


  ffmpeg -i input.mp4 -c:v h264_nvenc -c:a copy output.mp4 


  


  

  • I'm using Windows 10 64b, Command Prompt, ffmpeg version 2024-01-20-git-6c4388b468-full_build-www.gyan.dev

  


  


  I removed h264_nvenc, Run as Administrator but the result is same.

  


  ffmpeg -i input.mp4 -c:v -c:a copy output.mp4