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Power of A/B Testing for Improved Mobile and Web
App Results

• If you are an owner of a successful app and
  desiring to redesign it. You may have several
  desired goals rather than redesigning it, like
  improving the applications UX experience and
  switching to modern technology. But how will you
  know if the changes will be adopted by the
  audience warm-heartedly or not? The answer is A/B
  testing.
• But are you capable of conducting A/B testing? If
  not, you can hire Indian App developers who will
  help you from preparing to conducting A/B testing
  and suggest the best updates for the improvement
  of your mobile and web app.

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What is A/B Testing?

• A/B testing or split testing is a marketing
  experiment to find out which variation (out of
  two or more) of the same feature or interface
  element is more appreciated by the users. In
  other words, you can understand A/B testing as an
  experiment wherein you show version A of a new
  feature or design to one of half of your
  audience, and version B to another half to
  determine which performs better. There are two
  types of A/B test, you can conduct in order to
  increase the conversion rate of your website.

Design Test In this scenario, you will test to
see the change in conversion rate by changing the
colour of your call-to-action (CTA) button. To
A/B test this theory, you would design an
alternative CTA button draped in different colour
controlling the same landing page. Suppose your
existing CTA buttons colour is red in your
marketing content and your variation green colour
receives a better response in the A/B test.
Therefore, changing your CTA button colour from
red to green turned beneficial for you.
User Experience Test Suppose, you want to see
how people will react if a certain call-to-action
(CTA) button position is shifted from sidebar to
the top of your homepage. Will it turn into an
improved click through rate? To A/B test this
theory, an alternative web page will be created
with CTA placement change. And then you will
compare both these designs by showing each of
them to a predetermined share of the visiting
audience. The audience share will be ideal for
both versions. The existing design or version A
is the control while the newly developed design
with CTA placement change is Version B or the
challenger for the A/B test
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What are the Benefits of A/B Testing?

• The A/B tests help marketers and business owners
  in eliminating uncertainty about making decisions
  for their mobile apps and web software. This way
  they can try out ideas hovering in their mind and
  tests them based on data from reports. The A/B
  testing is a platform where you can check the
  viability of your idea and users responses
  accordingly. Given below are some more benefits
  of split testing.
• You can test updates before implementing them
  permanently for everyone. This helps in managing
  risks and saving money.
• You can improve the KPIs of your business.
• Gets an idea for improving the user interface,
  user experience, and content.
• Get to know the actual behavior and responses of
  users for new designs and features.

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How to Run an Effective A/B Testing for Mobile
Apps and Web Software?

• Analyze your app data before starting split
  testing
• All the major names like Google, Facebook,
  and Netflix perform A/B testing regularly. For
  which, they utilize enough data to get reliable
  results. You can estimate success for your A/B
  test only with proper metrics.

Conversion rate  The percentage of users
completed a goal in your app, whether to make a
purchase or subscribe
Retention rate  It is the percentage of those
users who are making purchases regularly and
paying for a subscription in your app. It is
calculated as an average as on a half-yearly or
yearly basis.
Churn rate  It can be elaborated as the number
of users has stopped using your services or
buying anything from your app over a given period.
Active users  It is the number of unique users
who use your app on a daily or monthly basis.
Such users translate into daily active users and
monthly active users.
Daily sessions  These are numbers that show how
many times an active user opens your app in a
single day.
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Go with the A/B testing flow

• Its possible when you are collecting important
  data for A/B testing of your mobile apps and web
  apps. You will encounter several updates to make
  to the multiple parts of your app and redesign it
  as well. And this will crave you to perform
  testing on all of them but we recommend not to do
  so. Because, if you perform A/B testing on
  several elements at a time, you will not be able
  to find which of them will drive you the desired
  results. Therefore, performing spilt tests one by
  one is a better approach, which will help measure
  the accurate influence of every single update.
  Lets move to the phase where you will learn how
  to A/B test your mobile application or a web app.
• Prioritize Elements
• First and foremost create a priority list of
  elements for A/B testing based on the benefits
  you get from them and the problems they will
  solve. For example, if your landing page is
  confusing and you need to update the colour of
  buttons then you should start first with the
  onboarding page. Since in the very beginning

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Affirm your hypothesis

• The hypothesis is an idea of what elements you
  will test to get the desired results. So it is
  necessary to affirm first what you want to split
  the test. You can test any changes for improving
  metrics and creating a better user experience. To
  do so, you need to set a goal first. Like you
  want to boost your retention rate to 35.
• Decide on segment and time duration
• You must be wondering, how you can ensure the
  accuracy of the test results? To do so, you have
  to calculate the number of users and the duration
  of the test. Simply, you cannot do this manually.
  So there are several size calculators available
  in the market for free. You have to enter details
  like your current and desired conversion rates,
  number of variations, and number of daily users.
  And you will be provided with a recommended
  sample of users and test duration.

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Create variables

• To test the hypothesis, content is necessary and
  you can perform a single split test using several
  variations. However, more variations require more
  users. So, check on its own as for a 20
  conversion rate, you will need 7200 users as
  suggested from the sample size calculator. But
  with the 4 variations, these users figures will
  manifold by two times. In case you dont have
  that many users, you can be 100 sure of your
  test results.
• Test multiple variables at the same time
• Besides testing variables for the same part of
  your app at different times, try to test them at
  the same time. Because testing variables at
  different times can lead to insignificant
  results. The timing of split testing can turn out
  to be an exception when you test the proper time
  to send push notification to your users.

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Consider user feedback

• Considering user feedback along with analytics
  data is the right approach to perform a well
  informed A/B test with desired results. Because
  better metrics also contain plenty of angry
  users. Ignoring them can easily misinterpret your
  A/B test outcome. So go hand in hand with
  analytics data and user feedback.
• Report A/B test results and repeat
• Once the A/B test gets completed, share test
  results with your team and users. It will let
  them know why the app is being updated. These
  results will inspire you for future results with
  new hypotheses, so you can conduct tests and
  arrange meetings regularly for the improvement of
  your app. If possible, draft a testing roadmap
  with detailed descriptions and repeat the A/B
  test flow all over again.
• Final words
• Preparing for conducting A/B testing or split
  testing, it is not that easy. But you should know
  that A/B testing plays a vital role in
  identifying where your app requires an update.
  Also, it helps business owners in making firm
  decisions with confirmed success which results in
  saving money and resources as well. We hope our
  guide of A/B testing for mobile and web apps will
  turn out fruitful to you.

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