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Button color tests. Font size tests. Headline tests. Run them all you want.

But remember that your website’s conversion rate is only as limited as the risks you take. Small tweaks = small wins. If you’re craving for big wins, you’ll have to make big changes.

I understand that you want to “play it safe” and be cautious. But sometimes it is best that you test a radical redesign against your original one, instead of testing small tweaks over and again.

Scenarios When a Radical Redesign Makes More Sense than Testing Small Tweaks:

When You Have a Low-traffic Site

The problem with a low-traffic site is, small tweaks will take a long time to reach the 95% confidence levels for a valid test result. But if you test two radically different designs against each other, you will require a smaller sample size and the conclusive results will be reached in a much lesser duration.

You can see the table below elaborating this, where the test duration has been calculated from our Split test duration calculator:

Assumptions:
Number of visitors: 500 per day
Current conversion rate of the site: 2%
Variations: 2

Percentage Increase Split Test Duration
5% 1254 Days
10% 314 Days
15% 139 Days
25% 50 Days
50% 13 Days



Assumptions:
Number of visitors: 20,000 per day
Current conversion rate of the site: 2%
Variations: 2

Percentage Increase Split Test Duration
5% 31 Days
10% 8 Days
15% 3 Days
25% 1 Days
50% Less than 1 day



Like you can see in the above tables, the higher the expected increase in the conversion rate (which also reflects how big is the change made by you), the lesser will be the duration for which you will have to run the test.

The only difference between the two tables is the number of daily visitors received by the sites.

This clearly shows that a high traffic site can test small changes as much as they want. But for sites that receive less traffic, it is best to make big changes (at least to start with). After this, you can tweak your new, winner-design and optimize it further for small wins.

When No Matter What Tweak You Test, You Get Negative Results

When you focus on small tests only and test every element that you can find on the page, there will come a time when any tweak that you make will only give you negative results. This means that your current design has reached its maximum conversion potential, also knows as the “local maximum.”

Solution? Test your fully-optimized page against a new design that is entirely different from your current design.

When Your Current Design Clearly Has Huge Scope of Improvement

If you’re a beginner in A/B testing, it’s perfectly fine that you start with 2-3 small tests first because you’re testing the waters. And if you’re someone who needs to convince your management of the power of AB testing, small tests are again your best bet.

But if you are well aware of conversion optimization practices and clearly see a huge scope of improvement in the current website design, be bold and start with testing an absolutely different design at once.

Look at the homepage given below. I cannot even begin to write what is wrong with this page. Believe it or not, such pages do exist.

Poorly designed page which needs a complete redesign

Now do you really think that small tweaks will be enough here? The page clearly needs a drastic redesign.

Wasting time in testing smaller tweaks on the current design that needs a complete overhaul is a mere waste of time.

When You are Not Ready to Settle for Less and You Want Big Wins

Small tweaks can only take you so far. But if you hear about huge wins and wish when you will hit the jackpot, it’s time you leave the “safe harbor” of running small tests and test some radical redesigns.

This involves high risk, yes. But if you do it right, your chances of hitting your jackpot will also be much higher.

But wait…”how exactly can I do it right?” Is that what you’re thinking? Read the approaches given below and you will hopefully find your way to a great hypothesis.

4. Approaches to Come Up with a Solid Hypothesis for a High-Converting Redesign

1. Take Them Closer to the Must-have Experience

The must-have experience is allowing visitors to understand the true value of the product by trying it out themselves.

Reduce the number of steps or even the number of clicks that a user must complete to try out your product. If your product is powerful, making people realize how useful your product is, can do wonders for your conversions.

Eliminate any complicated steps or requirements, unless absolutely necessary. The lesser the effort required by the user, the better it is.

Hello Bar understands this perfectly well and guides visitors to try out their product with a single click on their homepage. Here’s what their visitors see on the next page:

Hello Bar's Must Have Experience is Only One-click Away for Their Visitors

Notice how the fields above do not ask for any personal information of the user at all. Visitors can try out their product right away without giving any email address, name, or filling any signup forms.

The point is, your conversion goal should come after the must-have experience and not before it.

It might seem like this approach is only fit for SaaS websites, but that’s actually not true. See the “Click to look inside” option provided by Amazon:

Amazon provides the must-have experience to its customers

If the nature of your business does not allow you to provide this must-have experience on your website, you can treat your final order or sale as your must-have experience. And please don’t do anything stupid like this:

This eCommerce site places its registration conversion goal before their must-have experience (final sale)

Looks like, for this website, registration of their customers is a lot more important than actual sales. “Login to buy”…Seriously?

By adding a silly sign-up goal before their must-have experience (final sale), they are losing tons of money. This is why guest checkouts are so popular these days. And how can you forget the awesome 1-click checkout of Amazon?

Start from your conversion funnel in web analytics. Lookout for steps where you are getting most drop-offs.

Consider if you can completely skip any of these steps, or at least reduce the friction for visitors by reducing the number of clicks or form fields that are in their way in getting closer to the must-have experience.

2. Challenge the Approach of the Current Design

Testing a radical makeover doesn’t mean that you design a page randomly that is drastically different from your current website design.

The point here  is to focus on challenging the assumptions or approaches of the current design and testing it on the basis of a solid hypothesis.

For example, Sierra Tucson is a rehabilitation facility that tested a radical redesign on their web page. They found that their trust-focus landing page converted better than their luxury-inclined page. This got them 220% more leads.

3. Conduct Customer Surveys

You cannot be your own customer. To understand what special points about your product or service resonate best with your audience or if they have any concerns or apprehensions, conducting customer surveys can provide great insights.

Once you know what your customers like the most about you, you can emphasize it on your page to get positive responses. You can combine this with heatmaps/clickmaps in your Visual Website Optimizer app to see what interest your audience the most and redesign your page accordingly.

One of our customers recently conducted a customer survey, followed by testing a radical redesign against their original page. The insights from the customer survey were used to design almost every element on the redesigned page along with the changes in the copy that used the same words that their customers used in the survey to define core benefit of their service.

The redesigned page increased their sales by 64.8%. You can read the complete case study here, or see its comparison image below:

Loft Resumes Comparison Image

4. Test Pricing Experiments

When it comes to prices, asking people how much they would pay for a particular thing is not a good idea. After all, spending hypothetical dollars is a lot easier than spending the real ones. This is why experimenting with prices is a long shot. And when you have A/B testing to do it in real time, what’s better than that?

One of the most popular pricing experiments you must have seen around is the prices ending with the magical number, 9. For example, a $1400 bed will be displayed for the charming price of $1399.

According to the book, Priceless, eight studies published between the period 1987 and 2004, reported an average of 24 percent relative increase in sales for prices ending with the number 9.

You can even try playing with your pricing plans. One of our previous customers gave up his Freemium plan which increased his paid signups by 268.14%. This test definitely involved a lot of risk but the percentage increase from the test sure made it worthwhile.

Contrast is another great concept that works well with pricing. Conversion expert, Peep Laja, explains this well in his post about pricing experiments:

Nothing is cheap or expensive by itself, but compared to something.

Once you’ve seen a $150 burger on the menu, $50 sounds reasonable for a steak. At Ralph Lauren, that $16,995 bag makes a $98 T-shirt look cheap.

What’s the best way to sell a $2000 wristwatch? Right next to a $12 000 watch.

Just like in any other business, you will have to take calculated risks to grow your online business too. As long you are making informed, data-driven risks, rather than random testing, it should be fine. Remember, with greater risks come greater rewards.

About The Author

6 Comments

  1. In one of your examples, where Acuity Scheduling increased their paid signups by 268.14% by giving up their Freemium plan – they eventually reverted to Freemium plan. Check here: http://www.acuityscheduling.com/signup.php

  2. I nice introduction into the world of the local maximum. Something that many more people need to come to terms with.

    I would issue a word of caution on the early point of radical designs needing a smaller sample size! – Don’t get to comfortable with that idea as in my experience many people will continue to end their tests to early and get the wrong result.

    Set a minimum number of days, no matter what traffic levels you have to account for change in the profile of the visitors.

    There is also no guarantee that a radical design will cause a 10+% increase where small designs create a 5% increase.

  3. Hi Gleb,
    Good question. I’m founder of Acuity Scheduling. Our tests were a great success, wildly increased the number of paid signups, and after a month churn we still saw a ***50% increase in revenue***, and that’s just from a test only 50% of our visitors saw.

    So why still offer free? My mom. She inspired the business, and part of that was having something she could always afford. Even a $10 paid plan hasn’t always been affordable for her. Instead of implementing what we tested directly, we’re taking what we learned (trying to reduce the free->paid shock), and running more tests to find the best way to still offer a free plan, but have anyone who might ever want the paid features to go that route first.

  4. Hi Gavin,

    “50% increase in revenue” – it’s a lot. You’d better find the other way to provide a free plan for those who cannot afford paid version.

    We also removed free version some time ago. But we provide our software for free for those who need it but cannot afford it, students etc.

    Thus we have more resources to make a better product for everyone.

  5. Should be 50% increase in revenue growth (not quite revenue), still quite a bit.

    Yes, but at the same time I’m not looking to eek out every penny. The original test succeeded well at that, but went slightly against my values. Hopefully I’ll have more to share after tweaking our testing further!

  6. @Gavin – Thanks for the follow up!

    @Gleb – Here’s another similar case study you might find interesting: http://labs.openviewpartners.com/should-you-drop-your-freemium-model/

    @David – Some great points there. I think I’ve lost count of the number of times I’ve seen people not wait for even the 95% statistical confidence, let alone the sample size. Thanks for bringing that up!

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