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A/B testing landing pages in Digital Marketing - Mini Project: Build & Apply

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A/B Testing Landing Pages
📖 Scenario: You work as a digital marketer for an online store. You want to find out which landing page design gets more visitors to sign up for the newsletter. You have two versions of the landing page: Version A and Version B.To decide which version works better, you will set up an A/B test by tracking how many visitors see each version and how many sign up.
🎯 Goal: Create a simple A/B test setup that records the number of visitors and sign-ups for each landing page version. Then calculate the conversion rate for each version to see which one performs better.
📋 What You'll Learn
Create variables to store visitor counts for Version A and Version B
Create variables to store sign-up counts for Version A and Version B
Calculate the conversion rate (sign-ups divided by visitors) for each version
Compare the conversion rates to identify the better performing landing page
💡 Why This Matters
🌍 Real World
A/B testing is widely used in digital marketing to compare different versions of web pages or ads to find which one performs better in engaging users or generating sales.
💼 Career
Marketing analysts and digital marketers use A/B testing to optimize campaigns and improve user experience based on real data.
Progress0 / 4 steps
1
Set up visitor counts for landing pages
Create two variables called visitors_A and visitors_B with the exact values 1500 and 1700 respectively to represent the number of visitors for Version A and Version B.
Digital Marketing
Hint

Use simple variable assignments like visitors_A = 1500.

2
Set up sign-up counts for landing pages
Create two variables called signups_A and signups_B with the exact values 120 and 180 respectively to represent the number of sign-ups for Version A and Version B.
Digital Marketing
Hint

Assign the sign-up counts to variables just like visitor counts.

3
Calculate conversion rates for each version
Create two variables called conversion_rate_A and conversion_rate_B. Calculate each by dividing signups_A by visitors_A and signups_B by visitors_B respectively.
Digital Marketing
Hint

Use division to calculate conversion rates like conversion_rate_A = signups_A / visitors_A.

4
Determine which landing page performs better
Create a variable called better_version. Use an if statement to set better_version to "A" if conversion_rate_A is greater than conversion_rate_B, otherwise set it to "B".
Digital Marketing
Hint

Use an if-else block to compare conversion rates and assign the better version.

Practice

(1/5)
1. What is the main purpose of A/B testing landing pages?
easy
A. To compare two versions and find which performs better
B. To create multiple unrelated web pages
C. To increase website loading speed
D. To design logos for the website

Solution

  1. Step 1: Understand the goal of A/B testing

    A/B testing is used to compare two versions of a webpage to see which one works better for visitors.

  2. Step 2: Identify the correct purpose

    Among the options, only comparing two versions to find the better one matches the goal of A/B testing.

  3. Final Answer:

    To compare two versions and find which performs better -> Option A

  4. Quick Check:

    A/B testing purpose = Compare versions [OK]
Hint: Remember: A/B testing compares two versions only [OK]
Common Mistakes:
  • Thinking A/B testing creates many unrelated pages
  • Confusing A/B testing with website speed optimization
  • Assuming A/B testing is for design tasks like logos
2. Which of the following is a correct step in setting up an A/B test for landing pages?
easy
A. Change the entire website design during the test
B. Test multiple changes at once to save time
C. Randomly split visitors between two page versions
D. Ignore visitor data and guess the better page

Solution

  1. Step 1: Review proper A/B testing setup

    A/B testing requires splitting visitors randomly to fairly compare two versions.

  2. Step 2: Identify the correct step

    Only randomly splitting visitors between two versions is a correct and essential step.

  3. Final Answer:

    Randomly split visitors between two page versions -> Option C

  4. Quick Check:

    Visitor split = Random between versions [OK]
Hint: Always split visitors randomly for fair comparison [OK]
Common Mistakes:
  • Testing many changes at once causing unclear results
  • Changing whole website instead of just landing pages
  • Ignoring real visitor data during the test
3. If version A of a landing page has a 5% conversion rate and version B has a 7% conversion rate after testing with equal visitors, which version should you choose?
medium
A. Version A because it was tested first
B. Version B because it has a higher conversion rate
C. Neither, because conversion rates are too close
D. Both, by showing them randomly forever

Solution

  1. Step 1: Compare conversion rates of both versions

    Version A has 5% and version B has 7%, so B performs better.

  2. Step 2: Decide based on performance

    Choose the version with the higher conversion rate to improve results.

  3. Final Answer:

    Version B because it has a higher conversion rate -> Option B

  4. Quick Check:

    Higher conversion rate = Better version [OK]
Hint: Pick the version with the higher conversion rate [OK]
Common Mistakes:
  • Choosing version tested first instead of better performing
  • Ignoring small but meaningful conversion differences
  • Continuing to show both versions without decision
4. A marketer ran an A/B test but changed the headline and the call-to-action button at the same time. What is the main problem with this approach?
medium
A. It makes it impossible to know which change affected results
B. It speeds up the test and gives clearer results
C. It reduces the number of visitors needed
D. It improves the website loading speed

Solution

  1. Step 1: Understand the problem with multiple changes

    Changing more than one element at once confuses which change caused the result.

  2. Step 2: Identify the main issue

    The main problem is losing clarity on which change improved or hurt performance.

  3. Final Answer:

    It makes it impossible to know which change affected results -> Option A

  4. Quick Check:

    Multiple changes = unclear results [OK]
Hint: Test one change at a time for clear results [OK]
Common Mistakes:
  • Believing multiple changes speed up or clarify tests
  • Thinking fewer visitors are needed with many changes
  • Confusing test changes with website speed improvements
5. You want to improve a landing page using A/B testing. You have two versions: Version A with a blue button and Version B with a red button. After 1000 visitors each, Version A has 50 conversions and Version B has 55 conversions. What should you do next?
hard
A. Declare Version B the winner and switch all traffic to it immediately
B. Change both button color and headline and test again
C. Ignore the test and pick a new design randomly
D. Run the test longer to collect more data before deciding

Solution

  1. Step 1: Analyze the conversion difference

    Version A has 5% conversion (50/1000), Version B has 5.5% (55/1000). The difference is small.

  2. Step 2: Decide based on data size and difference

    Small differences with limited visitors need more data for reliable results.

  3. Final Answer:

    Run the test longer to collect more data before deciding -> Option D

  4. Quick Check:

    Small difference + limited data = test longer [OK]
Hint: Small differences need more visitors before deciding [OK]
Common Mistakes:
  • Choosing winner too soon with small data
  • Changing multiple elements before finalizing test
  • Ignoring test results and guessing