How to Strengthen the A/B testing to Boost Revenue?


A/B testing is knowing the visitors if your hypotheses are right, or your conversion plan is on the right course. A/B testing will provide concrete evidence of what actually works in marketing as well as a better understanding of customers instead of guessing. Having a clear idea of what your customers actually like and prefer can do wonders for your branding and marketing in other channels as well. A strong A/B testing plan will allow you to increase your revenue. So how can we improve it?

seo_on_page

A/B testing is actually a process that we run a simultaneous experiment between two pages to see which performs better: version A is the existing design (the “control”) and version B is the “challenger”.

For an A/B testing to be successful, we will have to start from measurement, prioritization, finally testing and repeat the process.

1. Measure website’s performance

To continually improve the conversion rates, we must start by properly measuring our website’s performance by determining what is happening and why it’s happening.

What is happening: Getting actionable data from Google Analytics

1.1. Define business objectives

Just answer these questions: “Why does the website exist?” Make objectives DUMB – Doable, Understandable, Manageable, Beneficial”.

1.2. Define website goals

Goals are your priorities, expressed as simply as possible. Before you start working on your data, make sure you have them defined and properly set up in Google Analytics

1.3. Define Key Performance Indicators (KPI)

KPIs are metrics. And a metric becomes a KPI as it is measuring something connected to objectives. Having proper KPIs will keep strategy on track.

1.4. Define target metrics

For your KPIs to mean something for you, they need target metrics.

Why is it happening: Talk to your visitors

Getting real feedback from your visitors is invaluable, they can from surveys or Google Analytics with qualitative data. But remember that we should use appropriate segmentation strategies to focus on:

  • Segment by source from e-mail campaigns, Google, Twitter or Youtube.
  • Segment by behavior
  • Segment by outcome
  1. Prioritize the testing opportunities

The next step is to prioritize what to test.

2.1. Prioritize pages with high potential for improvement

The Analytics data can show clearly problematic pages, like landing pages with high bounce rates. However, none of the information sources will identify split testing opportunities perfectly. That’s why you need to detect several pages at the same time.

Top exit pages

This is the last page that someone sees before leaving your site. By observing the “% Exit” in Google Analytics, we can identify the percentage of visitors who leave your site immediately after viewing the page.

Look at funnel drop-off rates

A funnel in Google Analytics focuses on the bottom end of the funnel. If you have your funnels correctly set up, you can gain valuable split testing information from it. If you’ve identified a drop-off step in your transactional funnel, you should ask yourself why the problem is happening:

  1. Where are the visitors coming from?
  2. Is anything stopping them from taking action on the page?
  3. What information were they looking for?
  4. What were they expecting to see on the page?

2.3 Prioritize important pages

Pages with the highest volume is the most important ones for testing.

2.4 Pages with a high volume of traffic are important

As tests on high-traffic pages finish sooner, we can move on to the next tests faster, which will definitely speed up our optimization process. Let’s choose most-visited pages, top landing pages and pages with expensive visits.

2.5. Prioritize tests based on value and cost

Start with high-value, low-cost testing ideas. An example of this can be testing variations in a checkout process step that is showing significant abandoment rates compared to previous steps.

3. Testing

Form a clear hypothesis for test: A hypothesis will let our split testing results give us useful information about customers and define the exact problem occurring, which will help you to come up with testing variations that give meaningful results. A good hypothesis should be testable, have a goal of solving conversion problems and gain market insights.

Pay attention to statistical relevance

Ignoring statistical confidence while running an A/B test is worse than not running a test. The statistical importance of an experiment should be more than 95%, which help us be sure that our results are valid and not based on chance.

Test for revenue

At the end of the day, revenue is the bottom line. An increase in conversion rates may even sometimes mean a decrease in revenue as you are not tracking the correct indicators. By contrast, your conversion rates may drop, but your overall revenue still increases as if the demand for your product is high enough for people to buy.

What to test – the low-hanging fruit

Always observe analytics and get customer feedback for any hypotheses you test. But for a general guideline, here are some of the elements that have historically given good results:

  1. Learn from results and start over

Once the test is completed, you should decide whether you carried out an excellent version of A/B testing in association with statistical confidence, enough traffic as well as a serious difference in conversion rate between the original page and the challenger.

If the result is positive, don’t stop testing. Let’s repeat this A/B testing procedure to achieve the goals established in the first step due to the fact that the consumer behavior and demand are changing constantly along with the technological progress and other social media factors and more importantly other rivalries are competing to your business. It will be be easier to adapt to changes more rapidly than competitors and even you can be a trendsetter and pioneers.

 

Moreover, the A/B test results will tell you what is going to happen if you make a change on the website instead of guessing like lottery game.

Indeed, the customers’ reaction to the website’s elements is reflected in the performance indicators that show you how you are doing again your ultimate objective: growing your online business. So try to get the most perfect version of A/B testing. And the patience will certainly pay off.