Anti-depressants such as Paxil and Zoloft dominate the pharmaceutical market. However, they build dependence and are made using chemicals that are un-natural to your body. It can also have major side effects. Provanax aims to solve this – It’s a natural supplement that not only helps depression, but it also helps reduce anxiety and stress. It has no side effects, and use safe, clinically proven Ingredients.

Take a look at the treatment below. We didn’t change much, but the increase was significant. The test concluded quickly even with a small dataset. We’ll go more in-depth as to why we believe we achieved these results.

The Variations

Control: $1.12 revenue-per-visitor

Treatment: $2.57 revenue-per-visitor (+129.1%)

Conclusion

Although we’ve just begun optimizing this page, we’ve already seen significant improvement. Whenever you land on a webpage, the first thing your brain tries to figure out is “Where am I?” and “What can I do here?”  This is why headlines tend to be so important – it answers those 2 questions very quickly. But why does it have to be that way? Simply because it’s the way our brain tends to figure things out.

This leads me to another concern we had with the original page – Where the headline should be, there was a testimonial. Intuitively, this makes sense, as it builds social value and reduces anxiety of the visitor. In essence it’s a sort of incentive. But, even when offered lots of incentives, we still need to see value in it in the first place to take action. For example, would you submit a form titled ‘Take a free trial”, if you knew nothing about what the free trial was for? Probably not. It’s a kind offer, but until you see value in it, you won’t be interested.

All we did on the variation is make the page more congruent with the thought sequence of someone being introduced to Provanax. This was done by replacing the testimonial with a headline describing where the visitor has landed and what the page has to offer. The test reached conclusion quickly because of the large improvement, however, with a small dataset we can’t be sure by how much exactly the conversion increased, although I’m sure it’s significant.

Back in the day when you had to manually transfer old contacts to your new phone by typing them in, DataPilot saved many peoples’ time (and fingers). Today they support over 4,000 different phone models, and serve as a solution to sync contacts between those phones. When we took a look at the analytics, one of the key things we noticed is that although they sell multiple products on the site besides DataPilot, they were all given even attention regardless of their popularity. Right away we decided it was important to test the hypothesis that conversions would be increased if we focused the site around their main product.

Another thing we noticed is that the navigation-flow felt like it was creating friction. For one, the “Products” link just showed some of their products, but the corporate, consumer, and retail store links also linked to products which were just meant for those types of customers. The old navigation made it feel like “retail store” linked to something that gave more information about their physical retail locations. We decided to try navigation titles that gave more clear information about the destination – and because they had a small amount of products, we tried making them drop-downs and linking to the product pages.

The Variations

Control: $0.99 revenue-per-visitor

Treatment: $1.60 revenue-per-visitor (+62.29%)

Conclusion

The gains were pretty significant – over 60%. A few key takeaways:

1. Navigation links should be titled in terms of what comes next and what they can get there.
2. Look at analytics and figure out why people are visiting your site, and segment by pages. In this case, we noticed most of the homepage visitors were coming through “datapilot”-related terms so we made that the hero.
3. If you have a small amount of products that are similar, try and figure out a way to link straight to the product pages intelligently.

Hope this helps. Enjoy!

Let’s say you have www.domainA.com and www.domainB.com – whereas www.domainB.com uses a CNAME or an alias pointing to www.domainA.com. Using this trick you can track both domains in a single google analytics account (or profile) using the same code on both sites. There is no limit as to how many domains  you can do this for, as long as they share the same files.

Change your GA code to look like this:

And then set up your standard cross-domain profile filter:

Enjoy!

Jumpoutthegym.com provides e-books, training videos, and other educational materials that teaches athletes how to jump higher. Jumpoutthegym.com acquires customers by email marketing to visitors who subscribe to their newsletters. Their funnel starts with an e-mail submit, and it being the wider part of the funnel, we decided to focus on this part first. By increasing the conversion rate on their e-mail sign-up rate, we were able to increase bottom-line revenues.

The Variations

Control LP: 34.2% CR

Variation: 41.7% CR (+21.95%)

Why It Won

The original headline was very unclear – it didn’t state what the page offers, nor why a user should submit their e-mail. It’s also very qualitative, and that tends to perform poorly compared to quantitative statements. The new headline clearly states what the page has to offer, and is specific about the offer. The key here was to get away from qualitative words such as “best”, and use specific facts 7 figures such as “72 inches higher”.

• Business performance should be measured by how much is learned in a certain span of time.
• To accomplish this, you must build a minimum viable product, test it, measure results, and then learn from it.
• The faster you iterate this process, the faster your business will grow.
  

The book reminded me exactly why conversion optimization is so effective – We build an experiment to test a hypothesis, measure results by creating a split-test, and then derive a conclusion based on the results.

Something he pointed out that interested me the most, however, is that when 2 companies compete, the company who iterates through this process the quickest is the one who usually wins. In CRO, this also applies. Each test teaches us something about our visitors – and the more we know about our visitors, the better we can sell to them. Every time you learn something about your visitors, you can make a “change” to your site that increases conversions. For example, imagine you had a $50 product but you had low conversions because your visitors were only willing to pay $40.  As long as you don’t learn that information, you’ll be losing out on the additional revenue you could’ve gained by lowering your price. This is what I like to call a “blind spot”, and every business has tons of them.  Uncovering them is how you’ll learn to grow, and split-testing is simply a vehicle that allows us to uncover them. It mitigates the consequences of our assumptions.

This article will detail unique optimization strategies that you will find extremely useful. Some topics will be somewhat technical, requiring the understanding of some programming. Either way, you should read it – understanding why you should apply these strategies is what will ultimately help you improve your conversion rates.

Return on Effort

The effectiveness of an experiment should not be measured solely by the percentage of increase it brings in conversions. Every case study brags about how they hit xxx% increase in conversion, but I believe the most important factor is return on effort. You should measure the effectiveness of your test by taking into account the effort and time it took to implement that test. Imagine how much more time and money it would take to test a new video compared to testing a new headline. Headline tests take me about 10 minutes to implement, whereas testing a new video would require a lot more money and resources.  With this in mind, we can begin to lay out a better way to run tests.

Choosing What to Test

If you asked a few experienced optimizers what element they would test first on a specific landing page, I believe you would receive varied responses. One may think the navigation should be tested first, while another would go for a headline test first. Without an effective strategy, most optimizers tend to decide what to test first based on one of two things:

1. What they have seen work before – This is because we want winning tests, and duplicating past wins intuitively seems to have the highest chance of success.
2. What element they believe is most lacking – Optimizers intuitively want to work on whatever has the most room for improvement.

There’s nothing wrong with this – it’s a good place to start. But we shouldn’t run experiments based on this alone. You need to weigh your ideas against the time it will take to implement the test, as well as the resources (and money) required to do so.

To figure out what to test, follow these steps:

1. Make a list of all your hypotheses about how you can increase conversions.
2. Convert these hypotheses into possible experiments.
3. Identify the following attributes of each test:
   1. Expected change in conversion rate
   2. Time required to implement the test
   3.  Money required to implement the test
   4. The duration that the test will need to run for to be conclusive. VWO’s test duration calculator will help you with this.
4. Taking these attributes into account, prioritize each test by weighing the expected change in conversion rate against the time, money, and test duration required

This methodology of testing allows you to be more efficient, and is especially necessary for smaller sites that are not getting a lot of conversions to run tests with. This can make the difference between a test that runs 2 months versus a test that runs 2 weeks! Once you figure out what to test, we need to implement it. 

Implementation

 I’m not going to get into setting up basic tests – you probably already know how to do that. I’m going to show you some advanced techniques for setting up tests that will allow you to run multiple site-wide tests at the same time. I like to call this “layering”. There are 2 huge benefits to running layered tests:

1. By using all of your visitors, you can run tests quicker.
2. By running multiple tests at once, you can run more tests in less time.

jQuery

What makes layering possible is client-side scripting – namely Javascript. With Javascript, we can dynamically adjust a website on-the-fly. jQuery is a Javascript library that allows you to accomplish this with relative ease, much more quickly than if you were to use plain Javascript. With jQuery, you can modify elements dynamically using a selector. I’ll outline a few strategies and show you how to implement each one. Even though you don’t intend to learn the coding, but rather intend to hand the task off to a developer, you should still take the effort to understand how it works.

Regular Expressions

Regular expressions allow you to match strings that meet certain conditions. For example, if you want to run some code on product pages but not category pages, you would use a regular expression.

Layering Site-Wide Tests

In order to learn more efficiently, you have to minimize the time between deciding to implement a test and launching that test. Most of that time in-between goes into development. Site-wide tests often require creating a duplicate of the entire site either in a sub-directory or a sub-domain.  Take a look at the image below of what your test setup might look like in a standard site-wide test using VWO.

The problem with this is that not only does it require you to create an entire duplicate of your site in a sub-directory then make the changes, but it also allows you only 1 site-wide test at a time.

Of course, you can test just certain sub-directories, such as creating a split-test for domain.com/products/* and another for domain.com/category/*, but you still have to create copies of all the pages residing in that subdirectory. Think about it – you’re duplicating 100% of the content, even if you are only changing/testing 1% of that content! Something about that just doesn’t seem right. And what about when your visitors link back to that URL? If it’s in a sub-directory, that link will send the visitor to a “page not found” after you stop the test. There’s a better way, and I’m about to show you.

A simple A/B test works by redirecting 50% of the traffic to the variation page. But something else happens in order to ensure that the person sees that page if they leave and come back – a cookie is saved to their computer that identifies which version of the page they should see. Modern software gives you 2 ways to create a split-test: A/B tests, and split-URL tests. An A/B test will show the same URL no matter which variation you are assigned, but a split-URL test will redirect you. The A/B test has the advantage on that front because it prevents people linking to broken pages in the future, but it has a huge disadvantage as well – you can’t test multiple pages.

In software such as Optimizely or VWO, A/B tests are set up using a visual WYSIWYG editor that makes it really easy to create tests, but you can’t make changes to multiple pages at once with a WYSIWYG editor.  For example, you can’t tell a WYSIWYG editor that lets you edit just one page to increase all your prices by 10%. However, these software include a nifty feature that allow you to get the best of both worlds – a Javascript API.

This API allows us to run Javascript code based on the value of the cookie – in essence, the variation they should see. In VWO, it’s a feature of the A/B editor and it allows us to layer site-wide tests on top of each other.

Here’s how you layer site-wide tests:

1. Visit a relevant page on your site.
2. Pull up the developer console, and write/test the code that makes the change you want site-wide.
3. Set up an A/B test, and add just that code to your variation.
4. Change your A/B test’s URL pattern settings so that it runs on the relevant pages, and excludes irrelevant ones.  If your software doesn’t meet your needs of proper URL matching, you can also use regular expressions in your code.
5. Launch test, then repeat steps for next test.

Let’s pretend I want to test 2 things: The effect of changing my background color, and the effects of increasing my prices by 10%. I’ll show you how to set this up in VWO, using Apple’s online store as an example.

First, I visit a page that the test should apply on.  In this case, any page. I’ll just go to the home page. I highly recommend jQuery injector for Chrome. This will allow you to run jQuery from the console on any site.  Here’s the code I’ve come up with:

Here’s the before/after.

Make sure you test the code on other pages to make sure it works. Now, I’ll go setup the A/B test. In VWO, you’ll create an A/B test, and just put any URL for now when it asks you for one. I’ll just put apple.com

Next, we are taken to the WYSIWYG editor. Click on the little gear next to “variation 1” and click “Insert Javascript/CSS”. Insert your code there, as shown below.

That’s it. Save it and move on. Set up your goals and hit next. On the last step where it says “Run test on URL(s):”, put in your test pattern. If you want it on all pages, put domain.com/*, if you want just a subdirectory, put domain.com/subdirectory/*. You can also exclude URLs. For this test, I’m excluding the checkout process as well as the help section. Below is what that might look like

What you see in the “Exclude URLs” section is a regular expression. They can be very complex, so you’ll either need to take time to learn it or find someone who knows it well.

Now we launch the test. That literally took me about 5 minutes. Compare that to setting up a sub-domain and cloning the site just to test the background color! Once that’s done we can layer our next test on top of it. We’re going to test the effects of raising the price of iPhone cases by 10%. I’ll use this page as the testing page.  Here’s the code I came up with:

For sake of time I didn’t test it on every page (and it’s not going to actually submit this price when you hit add to cart), but it’s a good example because it’s somewhat complex and it works on the page I tested it on. This took about 15 minutes, and it will be the same for any decent developer.

Real quick, I’ll tell you how this code works:

1. Look at the breadcrumbs and make sure the last word is “Cases”
2. If so, save the price of the product into a variable.
3. Add 10% to the price, and overwrite the old price.

Once we launch this test, we have layered 2 site-wide tests, and in less than an hour. That’s efficient. To make an entire copy of the apple site just to add this test would have taken tons of time, money, and resources.

I hope this is getting you excited – I know I was when I first discovered this! But you probably noticed a small issue with this – when the test completes and you stop the test, you still have to implement this to your site. However, changing the price of something on a site is much easier than duplicating the entire site. Also, if you duplicate the entire site and the test fails, you’ve gone through all that work for nothing.

There’s almost nothing that you can’t manipulate with jQuery – it’s awesome. If you want to go even deeper, you can also read the cookie manually using a server-side language, and have even more options for testing. However, that’s another post in itself that I’ll cover another time.

Measuring Efficiently

To iterate even faster, you can take advantage of techniques to lower the confidence level needed by your testing software. Here’s a few ways to analyze tests so you can finish a bit earlier, as well as get a better idea of how your tests are doing.

Goal Correlation

You should always measure as many goals as possible. At minimum, always measure revenue-per-visitor, conversion rate, engagement, and visits to intermediate funnel steps. If you’re not too confident in the results of a test, look at the correlation between the metrics. If they are all green, you can give it a bit more confidence. The test below is only at 70% statistical significance in revenue, but I wouldn’t mind finishing this one at about 75% or so because of the correlation.

Tracking multiple goals also gives you more insight as to how your variation is affecting visitors. For example, if you have a lead capture form and notice engagement is down but conversions are up, it usually means you’re doing a better job qualifying your visitors.

Chart Path

If you look at the line graph for any split-test you’ll notice that it goes up-and-down a lot in the beginning and then starts traveling straighter. As more data is collected, our conversion rate range decreases, which is the basis of the calculation for statistical significance. If you notice the lines on your graph have been parallel for a while, you can have more confidence in the results.

Conclusion

Conversion optimization is simply a method for learning about your visitors. The quicker you learn about them, the quicker you’ll grow. Taking advantage of this methodology for testing will have significant effects on what you can accomplish with your own tests, or what your testing team can do for your business. If you have any technical questions or any feedback, please leave a comment. Now go run some tests!

Hire Us

After initially reviewing the website we felt this was a perfect candidate for an experiment with multiple variables changed in the new page rather than a single variable change. This allows for greater range and is usually ideal for sites where you feel like lots of variables need to be changed immediately.

The Variations (click to enlarge)

The Changes

Here’s what we changed and why:

1Smaller header: If you read our case studies you should already know we do this on almost every experiment because it’s always produced results for us. Read more about it here.

2Used social toolbar that has counters: Without the counter, social buttons really give you no credibility.

3Moved headline up, centered it, and made it stand out more: Usually we have to change up client’s value propositions because the original isn’t good enough, but this one was pretty good to begin with. It tells you what it does, and why it’s gonna benefit you. However, it was very dull and didn’t stand out. Headlines are one of the biggest factors in bounce rates, so it’s important that it stands out. I’m very sure that this change was key to the variation’s success.

4Replaced headline and the text under it with benefits: We were left with some empty space by removing the headline – this gave us a perfect place to add some benefits and key points.

5Reduced friction on the CTA: Having 3 buttons, equally weighted and next to each other is almost always a bad idea. Why? – because you effectively reduce the relative weight of each one to 33.3%. We decided to put a select list instead to choose the quantity. We added some anxiety-relieving text under it.

6Removed the 3 boxes under the video: Because we added video testimonial we no longer needed the “our users” container that had a single text testimonial. Also, we moved the benefits in the “how it works” container to replace the old headline section (By the way, that should’ve been called benefits, not ‘how it works’). And last, we have no need for the “ships tomorrow” container because we added that as text under the CTA. This let us remove that whole section completely, and put the description there instead.

7Added video testimonials: Video testimonials always tend to be the most effective – therefore we added those to the homepage rather than text testimonials.

Our 2nd variation container a twitter feed – We wanted to test the effects of this separately because it took up a lot of real estate. It ended up having a negative effect on conversions – an interesting thing you should take note of before adding a twitter feed to your own site. It’s distracting. Distraction causes friction.

Another key thing to note: We also tried forcing the user to buy 2 for $10 by removing the select list and changing the CTA text to say “Get 2 for $10″. This performed horribly. Keep this in mind, and if you want to do something similar, make sure to test it.

I hope you guys get some good insight from this to use in your next experiment, and to optimize your own sites. Feel free to leave feedback in the comments below!

Want us to optimize your site? Contact us!

For this first test we wanted to test what kind of layout would work best. We came up with 2 alternatives:

Variation 1 (Divider-less): In this variation we did 3 things – First, we removed the divider. We felt that the division was causing friction to the page. We also removed the grey background behind the left content area in order to remove the feeling of division on the page. Also, we made the left side 70% width, and the right side (CTA) 30% width. This has been shown to be a best practice for landing pages time and time again.

Variation 2 (Single Column: As I said earlier, this site is sort of like kayak for a different industry. So we decided to try a layout similar to kayaks, which is a single-column, vertical layout.

Conclusion

Honestly, I thought the single-column page was going to win. I figured kayak had probably done tons of split-testing to get to that page, but in the end it’s all about the visitors, and they are not all the same. With this experiment, we were able to double the overall conversion rate which we are very proud of.

Want results like this? You should hire us.

Test #1

Test Page: Product Pages

Variations: 4

Hypotheses:

• Variation 1 (Anxiety Relief): Addressing  concerns that the visitor may have when deciding whether to purch ase a product will decrease their anxiety level, therefore increasing conversions.
• Variation 2 (Proximity + Add-on Friction): We noticed that many yes/no options were using select lists instead of radios or checkboxes, and were creating friction by making it seem like it was a multiple-choice question. We replaced these with tickers and used the extra space as a place to put our anxiety-relieving elements.
• Variation 3 (Head-less): Previous tests have shown that shorter headers usually convert better due to browser sizes – We removed the top banner and moved the search box above the navigation to test this.
• Variation 4 (Scarcity): We wanted to test the effect on scarcity on their visitors – we accomplished this by changing the price label to “Today Only:”
  

Conclusion: All of our hypothesis had positive results on conversion rates – we ended up putting together all the concepts we learned and implementing them globally.

Test #2

Test Page: Category Pages

Variations: 1

Hypotheses:

• Variation 1 (Larger Images): With 4 products per row on the category pages, it was hard to see any details of a product without zooming into it. We thought putting just 3 products per row would increase engagement.
  

Result: The Variation saw a 22% increase in revenue-per-visitor. The overall conversion rate increased 11%, which means revenue-per-conversion also increase.

Conclusion: Visitors will engage more when product details are clearly visible.

Test #3

Test Page: “You may also Like”

Variations: 1

Hypothesis:  On this particular site, visitors were being sent to a recommendations page after hitting “add to cart”, instead of the cart page. We wanted to see how effective this was, so we set up a custom funnel in Google Analytics. We found that the recommendations page had a pretty high exit rate – about 60%. We wanted to test the effects of removing this un-necessary step.

Results

Conclusion: Removing this extra step increased overall revenue-per-visitor by 32.91%.

Want these types of results on your site? You should hire us.

Demo

Today, I’d like to take some time to walk you through how to use our plugin and how to convert your existing forms into multi-step forms Make sure to A/B test before implementing it permanently, as we have seen tests where a multi-step form actually decreased the conversion rate.

1. Download the plugin here: http://landersoptimized.com/i/multistep.zip 

2. Unzip, then upload the folder to your server.  For simplicity’s sake I’ll assume you uploaded the folder to the root of your domain  for the rest of the tutorial.

3. Make sure you have jQuery. If you already have jQuery, skip this step. If you aren’t sure, there’s a simple way to find out. just check the source of your page and do a find (ctrl+f or cmd+f) and type ‘jquery’. You should find a match in a line that looks like the following code. If you find it, move to the next step. If you dont have it, put the following code in-between the <head> tags of your page:

4. Add the following tags to the <head> section of your page, AFTER the jQuery code:

note: use “multistep/multistep.css” and “multistep/multistep.js” if you didn’t place files in the root of the domain.

5. Give your form a ID tag of ‘multistep-form’ like so:

6. Separate your steps by wrapping them as follows. Also, give the last step an ID of ‘last-step’:

7. Give each step a button

8. You’re finished! If you are having trouble or want more info, visit the project page or leave a comment below and I’ll help out.

Why is this happening?

Popular belief tells you to change 1 variable per test. The reasoning for this is actually mathematically sound and valid. Let’s assume we created an experiment with 1 variation. In this 1 variation we make 2 changes – Make the CTA blue, and move the form higher on the page. The conversion increases by 6%. How do we know which variable caused the increase? It’s possible that moving the form up raised conversions by 8% and the button color decreased conversions by 2%, therefore making the outcome 6%. The basis of a scientific experiment in and of itself requires that only 1 variable be changed to arrive at a valid conclusion. But in Landing Page Optimization, there’s a reason as to why you should test multiple variables at once, going against the basis of scientific experimentation – Money. Let me explain:

Let’s say we run the following experiments:

• Test #1: Single-variable test – 4 variations. Result: 5% lift in conversion. Control LP Revenue: $10,000/mo.  Increase in Revenue: $500/mo.
• Test #2: multi-variable test – 4 variations. Result: 10% lift in conversion. Control LP Revenue: $10,000/mo.  Increase in Revenue: $1,000/mo.

Note: do not confuse multi-variable tests with multivariate tests. these are 2 completely different things.

By running a multi-variable test, we can see bigger differences between each variation’s conversion rate, and therefore have made an extra $500/mo. This also means that by not running the multivariate test and only running the single-variable test, we would be losing out on $500/mo that we could have had by running the multi-variable test. The only downside is that you don’t know for sure which change caused the increases. I’ll explain how to solve that issue.

Optimization Flow

We all know that 1 experiment is not enough. We should always be creating new experiments to continually optimize our conversion rate. In order to run multi-variable tests while also singling out variables, you need to follow the following optimization flow:

• Experiment #1 – Multi-variable test
• Experiment #2 – Single variable test using the winner of Experiment #1 as the Control LP

 source: MarketingExperiments.com

 So first, you run experiment #1 so that you get a big differentiation between your variations, then you test the single variables on the winner in order to pluck out the things that didn’t help and to verify the success of the changes that increased conversions. This allows you to also avoid losing out on increases in conversion that would’ve taken much longer to figure out by running a bunch of single variable tests. You should continually be repeating this process over and over. But the questions remains: “What variables should I test?”

 Creating Range

In order to create a test that results in a high increase in conversions, you need to create experiments that have range.  Range is the amount of differentiation you have between each variation in your experiment.

Popular belief says you should test things such as:

• Button Color
• Trust Logos
• Call-to-action text (Buy now v.s. Get it Now)
• Form on right versus left of page
• Social Icons
• Adding an incentive (“Fill out this form and we’ll send you a picture of a cute kitten!”)

Now, I’m not saying not to test those things. You should definitely test those things. It just shouldn’t be the first thing you test. You see, things like button color can make a difference, but when was the last time you changed your mind about buying something because of the color of the “Buy” button?  You need to test variables that make a big difference. You need to test Categorical Variables.

Categorical Testing

A categorical variable is a variable that is governed by an idea rather than an element on your page. They tend to affect your conversion rate a lot more than the usual things you would test. It’s very important you test these things first, as they are what will bring you the most value out of testing. Let’s explore a few example tests:

Process-focus v.s. Product-focus v.s. Outcome-focus LP

This experiment tests the best way to present your product or service in terms of what part of your product or service you focus on.

Let’s assume we are making a test for Apple’s MacBook Pro landing page. This is how our tests would look:

Test #1 (Process-focused): On this variation I would talk about the process of making a MacBook. I would probably use a picture of a factory worked shaving down the aluminum body of the MBP as a hero image. I would talk about how much precision goes into the process of making a MackBook, therefore showing the visitor how much work goes into making one, and maybe selling the visitor on that fact.

Test #2 (Product-Focused): On this variation I would use a beautiful picture of the MacBook as the hero image, and talk about it’s specs and capabilities. I would talk about the amount of RAM, screen resolution, CPU speed, etc. The goal would be to sell the visitor on the product itself.

Test #3 (Outcome-Focused): In the end, we all spend money for one reason: to become happier. In this LP I would try to prove how they would become happier by buying. I would use a picture of a woman looking at photos of her wedding on her MacBook, with a big grin on her face. I’m selling the visitor on the actual outcome  of what you get by buying.

source: MarketingExperiments.com

Lead v.s. Sale

You’re always going to see a lower conversion if you ask the visitor for money on your page. In many cases you will make more money by simply asking for their contact information, then converting the lead afterwards. This is tricky to setup because a conversion on a sale is much more valuable than a lead conversion. This means you can’t test their conversion rates against each other. You have to test the revenue-per-visitor. In order to do this, you total the amount of revenue each page created, then divide it by the amount of visitors to that page.

RPV = Revenue/Visitors 

Tonality

Testing the tonality of your page makes a big difference. This post has an informational tone. All bloggers have a different tone. Some make you laugh, and some make you inspired.

Here’s a few examples of different tonality:

1. “You need this because…Your life will change…Your time is important…”
2. “We hand-make our…We have been doing this for 30 years…We are committed…”
3. “People always say….What they don’t understand is…”

 Design

Completely changing your design can have a big effect. Hire different designers to design variations and test them against each other. 

source: MarketingExperiments.com

 Steps to convert

Sometimes when people see a form on a page it scares them away immediately. Rather than having a form on the landing page, try putting it on a 2^nd page and use a button on the LP instead.

If you these ideas are completely new to you, you are going to see a big effect on your experiments by applying them. I hope this helped. Now, go run some experiments!