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• Incrementality Testing : Quick-Start Guide (With Calculations)

  26 mars 2024, par Erin

  How do you know when a campaign is successful ? When you earn more revenue than last month ?

  Maybe.

  But how do you know how much of an impact a certain campaign or channel had on your sales ?

  With marketing attribution, you can determine credit for each sale.

  But if you want a deeper look, you need to understand the incremental impact of each channel and campaign.

  The way you do this ?

  Incrementality testing.

  In this guide, we break down what incrementality is, why it’s important and how to test it so you can double down on the activities driving the most growth.

  What is incrementality ?

  So, what exactly is incrementality ?

  Let’s say you just ran a marketing campaign for a new product. The launch was a success. Breakthrough numbers in your revenue. You used a variety of channels and activities to bring it all together.

  So, you launch a plan for next month’s campaign. But you don’t truly know what moved the needle.

  Did you just hit new highs because your audience is bigger ? And your brand is greater ?

  Or did the recent moves you made make a direct difference ?

  This is incrementality.

  

  Incrementality is growth directly attributed to marketing efforts beyond the overall impact of your brand. By measuring and conducting incrementality testing, you can clearly see how much of a difference each activity or channel truly impacted business growth. 

  What is incrementality testing ?

  Incrementality testing allows marketers to gauge the effectiveness of a marketing tactic or strategy. It tells you if a particular marketing activity had a positive, negative or neutral impact on your business. 

  It also tells you the overall impact it can have on your key performance indicators (KPIs). 

  The result ?

  You can pinpoint the highest-performing moves and incorporate them into your marketing workflows. You also discard marketing strategies with negligible, neutral or even negative impacts. 

  For example, let’s say you think a B2B LinkedIn ads campaign will help you reach your product launch goals. An incrementality test can tell you if the introduction of this campaign will help you get to the desired outcome.

  How incrementality testing works

  Before diving into your testing phase, you must clearly identify your KPIs.

  Here are the top KPIs you should be tracking on your website :

  • Ad impressions
  • Website visits
  • Leads
  • Sales

  The exact KPIs will depend on your marketing goals. You’re ready to move forward once you know your key performance indicators.

  Here’s how incrementality testing works step-by-step :

  1. Define a test and control group

  The first step is to define a test group and control group. 

  • A test group is a segment of your target audience that’s exposed to the marketing campaign. 
  • A control group is a segment that isn’t. 

  Keep in mind that both groups have similar demographics and other relevant characteristics. 

  2. Execute your campaign

  The second step is to run the marketing campaign on the test group. This can be a Facebook ad, LinkedIn ad or email marketing campaign.

  It all depends on your goals and your primary channels.

  3. Measure outcomes

  The third step is to measure the campaign’s impact based on your KPIs. 

  Let’s say a brand wants to see if a certain marketing move increases its leads. The test can tell them the number of email sign-ups with and without the campaign. 

  4. Compare results

  Next, compare the test group results with the control group. The difference in outcomes tells you the impact of that campaign. You can then use this difference to inform your future marketing strategies. 

  With Matomo, you can easily track results from campaigns — like conversions. 

  Our platform lets you quickly see what channels are getting the best results so you can gain insights into incrementality and optimise your strategy.

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  Why it’s important to conduct incrementality tests

  The digital marketing industry is constantly changing. Marketers need to stay on their toes to keep up. Incrementality tests help you stay on track.

  For example, let’s say you’re selling laptops. You can increase your warranty period to three years to see the impact on sales. An incrementality test will tell you if this move will boost your sales (and by how much).

  Now, let’s dive into the reasons why you need to consistently conduct incrementality tests :

  Determine the right tactics for success

  Identifying the best action to grow your business is a challenge every marketer faces.

  The best way to identify marketing tactics is by conducting incrementality testing. These tactics are bound to work since data back them. As a result, you can optimise your marketing budget and maximise your ROIs. 

  It lets you run multiple tests to identify the most impactful strategy between :

  • An email marketing strategy
  • A social media strategy 
  • A PPC ad

  For instance, an incrementality test might suggest email marketing will be more cost-effective than an ad campaign. What you can do is :

  • Expose the test group to the email marketing campaign and then compare the results with the control group
  • Expose the test group to the ad campaign and then compare its results with the control group

  Then, you can calculate the difference in results between the two marketing campaigns. This lets you focus on the strategy with a better ROI or ROAS potential. 

  Accurate data

  Marketing data is powerful. But getting accurate data can be challenging. With incrementality testing, you get to know the true impact of a marketing campaign. 

  Plus, with this testing strategy, you don’t have to waste your marketing budget. 

  With Matomo, you get 100% accurate data on all website activities. 

  Unlike Google Analytics, Matomo doesn’t rely on inaccurate data sampling — limiting the amount of data analysed.

  Try Matomo for Free

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

  Start for free

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  Get the most out of your marketing investment

  Every business owner wants to maximise their return on investment. The ROI you get mainly depends on the marketing strategy. 

  For instance, email marketing offers an ROI of about 40:1 with some sources even reporting as high as 72:1.

  Incrementality testing helps you make informed investment decisions. With it, you can pinpoint the tactics that are most likely to bring the highest return. You can then focus your resources on them. It also helps you stay away from low-performing strategies. 

  Increase revenue

  It’s safe to say that the goal behind every marketing effort is a revenue boost. The higher your revenue, the more profits you generate. However, for many marketers, it’s an uphill battle. 

  With incrementality testing, you can boost your revenue by focusing your efforts in the right direction. 

  Get more traffic

  Incrementality testing tells you if a particular strategy can help you drive more traffic. You can use it to get more high-quality leads to your website or landing pages and double down on high-traffic strategies to increase those leads.

  How to test incrementality

  

  Developing an implementation plan is crucial to generate accurate insights from an incrementality test. Incrementality testing is like running a science experience. You need to go through several stages. Each stage is important for generating accurate results. 

  Here’s how you test incrementality :

  Define your goals

  Get clarity on what you want to achieve with this campaign. Which KPIs do you want to test ? Is it the return on your overall investment (ROI), return on ad spend (ROAS) or something else ?

  Segment your audience

  Selecting the right audience segment is crucial to getting accurate insights with an incrementality test. Decide the demographics and psychographics of the audience you want to target. Then, divide this audience segment into two sub-parts :

  • Test group (people you’ll expose to the marketing campaign)
  • Control group (people who won’t be exposed to the campaign)

  These groups are a part of the larger segment. This means people in both groups will have similar attributes. 

  Launch the test at the right time

  Before the launch, decide on the length of the test. Ideally, it should be at least one week. Don’t run any other campaigns in this window, as it can interfere with the results. 

  Analyse the data and take action

  Once the campaign is over, measure the results from both groups. Compare the data to identify incremental lift in your selected KPIs. 

  Let’s say you want to see if this campaign can boost your sales. Check to see if the test group responded differently than the control group. If the sales equal your desired outcome, you have a winning strategy. 

  Not all incrementality tests result in a positive incremental lift ; Some can be neutral, indicating that the campaign didn’t have any effect. Some can even indicate a negative lift, which means your core group performed better than the test group. 

  Lastly, take action based on the test findings. 

  Incrementality test examples 

  You can use incrementality testing to identify gaps and growth opportunities in your strategy. 

  Here’s an example :

  Let’s say a company runs an incrementality test on a YouTube marketing strategy for sales. The results indicate that the ROI was only $0.10, as the company makes $1.10 for every $1.00 spent. This alarms the marketing department and helps them optimise the campaign for a higher ROI. 

  Here’s another practical example :

  Let’s say a retail business wanted to test the effectiveness of its ad campaign. So, the retailer optimises its ad campaign after conducting an incrementality test on a test and control group. As a result, they experienced a 34% incremental increase in sales.

  How to calculate incrementality in marketing

  Once you’ve aggregated the data, it’s time to calculate. There are two ways to calculate incrementality :

  Incremental profit 

  The first one is incremental profit. It tells you how much profit you can generate with a strategy (If any). With it, you get the actual value of a marketing campaign. 

  It’s calculated with the following formula :

  Test group profit – control group profit = incremental profit 

  For example, let’s say you’re exposing a test group to a paid ads campaign. And it generates a profit of $3,000. On the other hand, the control group generated a $2,000 profit. 

  In this case, your incremental profit will be $1,000 ($3,000 – $2,000). 

  However, if the paid ads campaign generates a $2,000 profit, the incremental profit would be zero. Essentially, you’re generating the same profit as before, which means the campaign doesn’t work. Similarly, a marketing strategy is no good if it generates lower profits than the control group. 

  Incremental lift

  Incremental lift measures the difference in the conversions you generate with each group. 

  Here’s the formula :

  (Test – Control)/Control x 100 = Lift

  So, let’s say the test group and control group generated 2,000 and 1,000 conversions, respectively. 

  The incremental lift you’ll get from this incrementality test would be :

  (2,000 – 1,000)/1,000 x 100 = 100

  This turns out to be a 100% incremental lift.

  How to track incrementality with Matomo

  Incrementality testing lets you use a practical approach to identify the best marketing path for your business.

  It helps you develop a hyper-focused approach that gives you access to accurate and practical data. 

  With these insights, you can confidently move forward to maximise your ROI since it helps you focus on high-performing tactics. 

  The result is more revenue and profit for your business. 

  Plus, all you need to do is identify your target audience, divide them into two groups and run your test. Then, the results will be compared to determine if the marketing strategy offers any value. 

  Conducting incrementality tests may take time and expertise. 

  But, thanks to Matomo, you can leverage accurate insights for your incrementality tests to ensure you make the right decisions to grow your business.

  See for yourself why over 1 million websites choose Matomo. Try it free for 21-days now. No credit card required.

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• What Is Incrementality & Why Is It Important in Marketing ?

  26 mars 2024, par Erin

  Imagine this : you just launched your latest campaign and it was a major success.

  You blew last month’s results out of the water.

  You combined a variety of tactics, channels and ad creatives to make it work.

  Now, it’s time to build the next campaign.

  The only issue ?

  You don’t know what made it successful or how much your recent efforts impacted the results.

  You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

  The key is incrementality.

  This is a way to properly attribute the right weight to your marketing tactics.

  In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

  What is incrementality in marketing ?

  Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

  It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

  

  For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

  The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

  It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

  With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

  See why over 1 million websites choose Matomo today.

  Try Matomo for Free

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

  Start for free

  No credit card required

  How incrementality differs from attribution

  In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

  Incrementality and attribution help marketers and business owners understand what efforts impact their results.

  But they’re not the same.

  Here’s how they differ :

  

  Incrementality explained

  Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

  Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

  In other words, how much revenue would you have generated this month without campaign A ?

  And how much additional revenue did you generate directly due to campaign A ?

  The reality is that dozens of factors impact revenue and growth.

  You aren’t just pouring your marketing into one specific channel or campaign at a time.

  Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

  Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

  So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

  And, if you add in that campaign, how much additional revenue and growth did it directly create ?

  That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

  So, how does attribution play into all of this ?

  Attribution explained

  Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

  While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

  For example, in any given marketing campaign, you have a few marketing tactics.

  Let’s say you’re launching a limited-time product.

  You might have :

  • Paid ads via Facebook and Instagram
  • A blog post sharing how the product works
  • Organic social media posts on Instagram and TikTok
  • Email waitlist campaign building excitement around the upcoming product
  • SMS campaigns to share a limited-time discount

  So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

  Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

  Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

  Or do you credit your SMS campaign that shared a limited-time discount ?

  Which channel is responsible for the sale ?

  This is what attribution is all about.

  It’s about giving credit where credit is due.

  The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

  Leveraging incrementality and attribution together

  Incrementality and attribution aren’t competing methods of analysing what’s working.

  They’re complementary to one another and go hand in hand.

  You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

  Why it’s important to measure incrementality

  Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

  Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

  1. Accurate data

  If you want to be an effective marketer, you need to be accurate.

  You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

  That’s not how it works.

  Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

  Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

  Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

  

  2. Helps you to best determine the right tactics for success

  How can you plan your marketing strategy if you don’t know what’s working ?

  Think about it.

  You’ll be blindly sailing the seas without a compass telling you where to go.

  Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

  It shows you what’s moving the needle (and what’s not).

  Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

  3. Allows you to get the most out of your marketing budget

  Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

  Guess what happens when you start doubling down on the most impactful activities ?

  You start increasing revenue, decreasing ad spend and getting a higher return on investment.

  The result is that you will get more out of your marketing budget.

  Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

  4. Increase traffic

  When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

  Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

  When you can increase traffic, you can increase your overall marketing impact.

  5. Increase revenue

  Finally, with increased traffic, the inevitable result is more conversions.

  More conversions mean more revenue.

  Incrementality gives you a vision of the tactics and channels that are converting the best.

  If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

  By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

  How to calculate and test incrementality in marketing

  Now that you understand how incrementality works and why it’s important to calculate, the question is : 

  How do you calculate and conduct incrementality tests ?

  Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

  If you’re not sure how incrementality testing works, then follow these simple steps :

  

  Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

  It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

  Here’s how it works :

  1. Choose your target audience.

  With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

  • • Visitors from the UK
    • Returning visitors
    • Mobile users
    • Visitors who clicked on a specific ad

  2. Split your audience into two groups :

  1. • Control group (60% of the segment)
     • Test group (40% of the segment)

  3. Target the control group with your marketing tactic (the simpler the tactic, the better).

  4. Target the test group with a different marketing tactic.

  5. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.

  6. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

  Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

  Try Matomo for Free

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

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  Here’s an example of how this incrementality testing could look in real life.

  Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

  The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

  1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
  2. They split this segment into a control group and a test group.
  3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
  4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
  5. They ran the campaign for three weeks with the goal for sale conversions and noticed :

  • • The control group had a 1.5% conversion rate.
    • The test group (with Facebook ads) had a 2.1% conversion rate.
    • In this scenario, they could see the group who saw the Facebook ads convert better.
    • They created the following formula to measure the incremental lift of the Facebook ads :

  

  • • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

  The Facebook ads had a positive 40% incremental lift in conversions during the sale.

  Incrementality testing isn’t a one-and-done process, though.

  While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

  They should continue conducting tests to verify the initial test.

  Use Matomo to track incrementality today

  Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

  If you want more help tracking your marketing efforts, try Matomo today.

  Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

  Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

  At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

  As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

  If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.

  Try Matomo for Free

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

  7 mars 2024, 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.

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