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We are delivering a pile of traffic here at your favourite traffic exchange and as usual we have a whole lot more for you today as well as some info about split testing, an awesome prize draw and more! The content, design, color and fonts used in your landing pages can all dramatically affect conversions.
If you’re an affiliate, split test multiple offers to see what gives you the highest Earnings Per Click (EPC) for your traffic.
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Split-testing is where you create different variations of your website and test which one performs the best, i.e. Using split-testing as a form of marketing will allow you to see which version inspires people to browse for longer, and which version attracts more website conversions. Organise a brainstorming meeting, and use the most popular ideas to split-test your website. The most crucial part of split-testing is making sure you test your ideas systematically, so that the outcome is fair, and negates any other variables which may affect the result. You may start seeing results from your split-test and get excited, but you need to make sure that you have the correct data to analyse before you make any conclusions.
You need to ensure that enough traffic has participated in your split tests, and that an equal amount of traffic has been driven to the different versions of the site before you can make any important decisions.
Optimizely alerts you  once you’ve collected enough data and lets you see what works best for your site.
The tool also helps explains the process which makes split-testing a lot easier for novices!
And if you are happy to pay for traffic to be sent to your website so you can see the results quicker, you can use Google Adwords to generate more clicks. Once you have split-tested your site, you will be able to provide real data to give to your designer, who can then improve your site so that it can reach its potential in terms of performance, bringing in more revenue for your business.
Therefore, we’ve put together these tips for improving your split testing and optimising your email marketing.
To illustrate the point, we’ve included the results of a recent split test we carried out on a Forfront campaign. After a split test you can edit your message in line with the test’s “winning” variables before it goes to the rest of your contacts, ensuring a prime return for all your effort. Often a subject line can make or break an email and split testing can reveal a huge variation in display rates. Sometimes the time and day that you send an email campaign is even more important than the subject line. A recipient might be really eager to open the message on Tuesday morning at 8am on the train to work, whereas another contact might be far more likely to give your message the attention it deserves at 4pm on a Friday when they’re winding down for the week.
If you’re just split testing to discover which subject line gets the best display rate, you’re missing out.
To really optimise your email marketing campaigns, a split test is a great way to experiment with your design and layout.
Recently, Forfront sent out an email campaign promoting our website development services which included a free downloadable guide and this special offer.
Instead of simply blasting the email to our desired group of selected contacts in one go, we wanted to establish two things; the ideal sending time for optimum displays and engagement, plus which subject line elicited the best response from the recipients. In order to figure this out, and to practice what we’ve been preaching in this post, we carried out a series of split tests.
The 8am “A poor website” email and the 6pm “Six reasons” campaign both got gigantic display rates – far higher than any other test.
On the other hand, the “Six reasons” test email at 8am got the highest click through rate, but only by a small margin. Both of the midday sends got adequate display and click through rates, but evidently our test contacts were most engaged, responsive and receptive to the email campaign early in the morning or at the end of the working day.
However, this split test didn’t conclusively answer which subject line had performed best, or which time was ideal. Subscribers were most likely to engage with “Six reasons” at the end of the day – with time on their hands during the commute or taking a break from work perhaps? On the other hand, “A poor website” was a more effective, attention-grabbing subject line early in the morning – producing a large spike in display rates – yet the click through rate underperformed in comparison. As the results weren’t entirely conclusive, we decided to split our main bulk of the campaign sending in line with our findings, to take advantage of the early morning response of the “A poor website” campaign as well as the huge evening display rate of “Six reasons”. Once again, “A poor website” worked exceptionally well in the morning – getting a colossal display rate. This wasn’t the perfect split testing example – especially considering our indecision on picking a winning subject line and sending time. During the tests, “Six reasons” had the higher averages but the spikes in “A poor website” at 8am couldn’t be ignored. Nevertheless, it helped us eradicate midday as a sending time and pushed us to split the campaign into two, in an effort to capitalise on certain trends spotted during different times of day.
While not a ground-breaking response, the final send was a great deal better than a lot of the tests.
After seeing the new headline, did more people click a ‘more’ link on one of our case studies? Worst case scenario – you continue to optimise for the metric that increased, because that ‘feels good’. If you absolutely must focus on more than one metric, be very clear which metrics are most closely linked to you ‘making money’, and have the guts to ignore changes to ones which aren’t. So we’re fans of both the “user interface tweak” test and the “change the words around” test.


If you’re still stuck, it may be time to bring in external help in the form of a consultant – often a fresh pair of eyes is all that’s needed.
This is the fun part, and as a lot has already been written all over the web about it, we won’t labour the point. If you see a major lift, say in the triple digits on the first day of a test, the testing tech will conclude that the changes are statistically significant at probably around a 99% confidence rate. We need to humanize the numbers and account for changes in interaction based on time of day, week, and other considerations.
All you truly know is that removing the exact 4 fields you actually removed resulted in double signups. The most important thing about the analysis phase is keeping a record of your conclusions, so you can revisit them and keep learning from them. However, if in a few months time, a new designer joins your team and questions the size of the form, you run the risk of restarting this whole process, unless you’ve got a record of your design decisions and the motivations behind them. For another example, let’s look at the ‘change the words around’ tests we mentioned earlier.
Hopefully these examples show how you how errors can creep in to your analysis, and how you can avoid them.
Let’s assume you ran “save time -vs- save money” test properly and confirmed that your site visitors prefer saving time to saving money (incidentally, this is an AWFUL value proposition – try harder!), that’s a really valuable bit of market research.
Even on small screens, you’re guaranteed to see more information when you land on the site. Well, because our hypothesis was clear, and we made one change, we’re pretty confident that we weren’t giving people enough to engage them. But because we were lacking in market research, we weren’t sure what the ‘perfect’ value proposition for our target audience was. More people reached the plans and pricing page, but this time, the numbers aren’t enough for Optimizely to tell us that the results are significant.
But still – more engagement and more people looking at how much it costs to get the benefits we provide. You could argue that the results of this test weren’t strong enough to draw these conclusions, and you’d have a good point. Testing record spreadsheet: Copy this spreadsheet and use this to track all your tests and conclusions!
Massive thanks to Lance Jones at CopyHackers and Justin Rondeau at Which Test Won for reading early drafts of this post. Split testing represents one of the easiest ways to increase conversion rate and it also gives you important insights about your audience. Once you have decided on the element you want to submit for split testing, you need to choose the tools for testing it. Google Analytics offers you the possibility to experiment in order to improve your conversion goal or any other element on your website. Another way to start creating and implementing a split testing is to choose a specialized service to help you do it.
Whatever tool you choose to start creating your split testing, your should remember to never surprise your regular visitors while testing a core part of your website, but include only new visitors in the tests. Split testing is when you split the traffic to your website to different versions of your site, tracking the performance of each to find the highest converting page. Create multiple landing pages on your website, and use identical ad copy to direct to each of the pages. Look at what your competitors are doing, then create one ad that’s similar to theirs. Just before server flip each day – I will check who has left a comment on our fanpage and you will score a freebie! All you need to do is leave the BRC and your Traffic Showdown ID below in a comment and you score yourself a nice free traffic bonus that will surely help you get more free website traffic to your sites and promotions!
We hope you found the info about split testing helpful, enjoy all the free website traffic and have a sensational Sunday! Improving display and click through rates is, naturally, one of the ultimate goals of email marketing. Good split testing gives you an unbeatable insight into the elements of an email campaign that will really engage your audience.
One subject might see huge amounts of recipients opening the message to find out more, whereas another one will get barely a single display. Don’t get me wrong, the subject line is extremely important, but you can test other hugely influential factors as well. If you split test your sending times or the layout of your email, paying attention to the click through rate is invaluable. Try putting your biggest call to action button in different positions on two different test emails and see which receives more clicks. If we’d plucked a subject line and sending time from the air, the response could quite easily have been far lower (see the 0% click through rate at 6pm for “A poor website” for instance).
And if you’re experienced, we’ll keep it interesting for you by busting a few myths along the way. We’re fairly keen on this type of test as words are subtle, devious things, and the way you combine them can have unexpected results.
Occasionally, changing a headline on a landing page may improve metrics deep in your conversion funnel (for example, increasing purchases because it single-handedly changes a new visitor’s understanding of what you are offering), but just as often, it only affects behaviour on the page where you have changed the headline (i.e. But unfortunately the metric which decreased is the one that was more important to your business. If a variation results in more engagement on a heatmap, but fewer sales, it’s not a winner! It’s really important to get this clearly defined and documented, because everything else in your test hinges on it.


The aim of the test isn’t to win design awards, it’s to learn something new about your visitors that helps you sell more. If you expect a variation to do well, and Optimizely (or your tool of choice) tells you it’s doing well, don’t end the test early!
Well, keep the above ‘form’ example in mind and imagine you ran a second test to check your conclusions. Maybe your customers actually care more about saving time, and if you combined a ‘time saving’ message with a customer testimonial, you would have seen a 400% increase in downloads! Remember – keep clear hypotheses, and change one thing to make your job of analysing a test easier! Being wrong is often uncomfortable, but if being wrong leads to a 500% increase in sales, it can be easier to take.
It’s great that you’ve found a change you can make on your website which increases conversions – but your business is so much more than your website!
Are you just going to use to improve your website, or are you going to use it to improve your whole business? How are they going to internalise it and use it when they discuss your company networking events? If you sell something complicated like Software as a Service (SAAS), you might need to change the messaging within the product itself, or even alter its functionality to emphasise the ‘time saving’ benefits it offers. This is the most exciting, and least discussed benefit of split testing – it’s not just a way of boosting conversions on your site, it’s a data-driven way of doing market research. But this is where the experience and intuition that I mentioned come in: We are pretty clear that we offer customer feedback you can act on, not customer service, and we have a back-story to prove it. If your goal is to increase your conversion rate, you need to look at the elements involved with conversion and decide with which one to start experimenting. There are several options: you can either integrate this experiment with your Google Analytics account, or you can create an experiment with another specialized service. There is a simple process for creating and starting your split testing and Google Analytics offers you a complete guide for doing things right.
Also, keep in mind that split testing is done for better conversion rate or other important goals and not for aesthetics, so try not to involve your gut feelings and never reject a result just because of your arbitrary judgment. It is important not to split-test ads and landing pages concurrently — this makes it difficult to attribute conversion changes to either landing page or ad variables.
After you have received 30 clicks or more on each ad, you will have enough data to decide which ad converts better. Create another ad that’s completely different and split test those two against one another. Because Google AdWords wants to display relevant ads, it rewards ads that have a higher click-through rate by making clicks less expensive. But they very often just confirm what most user interface designers would consider ‘best practice’. In the example I gave above, would you really optimise for people playing a video, over people giving you their email address and permission to market to them? You’ll waste time in your testing tool changing things that don’t need to be changed, and you’ll draw bad conclusions from the test results if your hypothesis is murky.
If you’re stuck for a good hypothesis, it may be that you’re thinking too much about your site, and not enough about your visitors.
If we create a successful variation that’s ugly, we can use this variation (and the conclusions we draw from it – see the next section) as a brief to our talented designer (hi Ryan!), to create a beautiful new page that incorporates what we learned from the test. Surprisingly the 7-field form performs as well as the 4-field form – it was just that one ‘troublesome’ field all along! We updated our personas, our social media profiles, and used this learning when we redeveloped the ‘welcome guide’ to CustomerSure – ensuring that we focused on helping people get feedback rather than carry out a more general, less focused customer service program.
If this had been a surprise to us, we might have tried to do more tests, but as it was, it was all we needed to double down on something our existing messages. But it is important to initiate these simultaneous experiments having in mind just one change since split testing is limited to single elements of a page.
To split test your ad, create a second ad in each individual ad group, and wait for the results. Step away from the site, and make educated guesses about what could encourage even more of the human beings who visit your site to ‘convert’ (whatever ‘conversion’ means to you). In fact, it can be wise to try variations that are a bit ugly – challenge everything, including the assumption that a ‘beautiful’ design is what sells.
Are there factors happening outside of your site (for example a targeted Adwords campaign) which are driving unnatural traffic to your site which would make this variation perform better in the short term, but make it a bad long-term idea?
Maybe your visitors just resented being asked their age and saw it as annoying or intrusive. If you’re not confident in your conclusions, why not run a new test comparing the 4-field form against the original form with only the ‘annoying’ field removed? You may as well keep the 7-field form as it gathers more information for your inbound leads database. It would be good to set up some more on-page goals to see if the ‘Customer Feedback’ headline is having an effect on people in the moments after they read it. Otherwise, you can use Multivariate Testing in order to determine a combination of changes that needs to be implemented.
Once you have a few hundred views on each of your ads, delete the ad with the lower click-through rate and create another. You simply don’t know for sure, and unless you test every possible combination of fields you can’t know for sure.



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