Day 1 is assigned to a specific date by the WSP team based on your batch start date.
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📅 Week 1 · Monday
day-01
What is WA.Expert?.
Today you'll learn: what WA.Expert is and why businesses pay for it — explained so clearly you could teach it to your parents by tonight.
⏱ ~20 mins
📖 Read + Quiz + Submit
✅ Need 3/5 to unlock
🔒 Tuesday only
Week
Week 6 of 8
Day
1 of 14
Program
2-Week Program
📖 Read This First — About 8 Minutes
A/B testing on WhatsApp requires discipline — one variable, sufficient sample, correct timing.
Day 32 — Month 2, Week 6. You are in the advanced phase of the 2-Month Expert Program. Today: A/B Testing on WhatsApp.
You now have the full technical and implementation foundation from Days 1–28. The remaining days build the advanced expert capabilities — the skills that differentiate a junior implementer from a senior consultant.
🔬
Expert-level work is about depth within a domain, not breadth across domains. Anyone can configure a Team Inbox. An expert configures it correctly the first time, anticipates the edge cases, and knows how to fix it when something breaks six months later. That depth is what today builds.
Read the reference page below, then apply your expert-level knowledge to the quiz and the day's task. The tasks at this stage are real deliverables — not practice exercises.
🔑 Expert standard: Every task submission from Day 29 onwards should be something you could show to a client or employer as evidence of your capability. Not a draft — a deliverable.
💡
Read the reference page below before taking the quiz.
What is the minimum audience size for a statistically meaningful WhatsApp A/B test?
A
100 contacts
B
At least 1,000 per variant (2,000 total minimum) to achieve statistical significance at common conversion rates — smaller tests produce results too influenced by random variation to be actionable
C
500 total is sufficient
D
Any size works if the difference is large enough
✅ 1,000+ per variant is the practical minimum for WhatsApp A/B tests at typical conversion rates. Smaller tests produce noisy, unreliable results.
❌ 1,000+ per variant minimum. Smaller tests are too noisy at typical conversion rates to draw reliable conclusions.
Question 2 of 5
You A/B test two campaign CTAs: 'Shop Now' vs 'See the Collection'. 'See the Collection' gets 40% higher click rate. What should you do?
A
Immediately switch all future campaigns to 'See the Collection'
B
Validate with a second test before making it your standard — one test could be influenced by the specific offer, time of day, or audience segment. Confirm the result holds across a different campaign before standardising.
C
The difference is too small to matter
D
Switch back to 'Shop Now' because it is the industry standard
✅ One test is a signal. Two tests pointing the same direction is evidence. A 40% difference is meaningful but validate before making it permanent standard.
❌ Validate before standardising. One test is a signal, not proof. 40% difference is meaningful but could be context-specific.
Question 3 of 5
What element should you change ONLY ONE OF in an A/B test?
A
Change as many elements as possible for maximum learning
B
Change exactly one element per test (CTA, subject line, offer, image, send time) — changing multiple elements makes it impossible to attribute the performance difference to any specific change
C
Change two elements — one significant, one minor
D
It does not matter how many elements you change
✅ One variable per test is the fundamental A/B testing rule. Multiple changes = can't attribute the result = cannot learn from it.
❌ One variable per test. Multiple changes = can't attribute the result. Clean single-variable tests produce actionable learnings.
Question 4 of 5
A WhatsApp A/B test runs for 2 hours before you declare Version B the winner. What is the problem?
A
Nothing — faster decisions are better
B
2 hours is too short — early responders may behave differently from typical recipients (e.g. people who immediately check WhatsApp vs those who check hours later). Let the test run for at least 24 hours before declaring a winner.
C
The test should run for a week minimum
D
Version A should always be given more time
✅ Early responders are a biased sample. 24 hours minimum ensures the full range of response behaviour is captured across different times of day.
❌ 24 hours minimum. Early responders are not representative. Let the full response curve play out before declaring a winner.
Question 5 of 5
What should you do with A/B test results that show NO statistically significant difference?
A
Run the test again with the same setup
B
Document it as a null result — equally valuable learning. It tells you this specific change does not affect performance, which narrows your optimisation focus. Keep the simpler or cheaper variant and test something else.
C
The test failed — start over
D
Declare whichever performed slightly higher as the winner
✅ Null results are valuable. They tell you what doesn't matter — which is just as important as finding what does. Keep the simpler variant and move your optimisation effort elsewhere.
❌ Null results are valuable learning. This variable doesn't matter — narrow your focus. Keep simpler/cheaper variant and test something more impactful.
–of 5
Answer all 5 questions, then check your score.
✏️ Your Task
🔒
Score 3/5 to unlock this
Complete the quiz above first. The moment you score 3 or more, this section unlocks.
🏅
🎉 Day 1 — done!
Day 2 opens on your assigned Tuesday.
📝 Today's Task
Someone in your family runs a small business. In 3–4 sentences, explain WA.Expert to them like you're actually WhatsApp-ing them right now. Your own words — not copied from the page.
Start like this: "So there's this platform I was reading about — it's basically for businesses that get too many WhatsApp messages to handle manually. It lets them..."
0 / 800
From your registration confirmation email. Can't find it?
Submitting before 11 PM IST on your assigned Tuesday counts as Day 32 complete.
Week 1 · Coming Tomorrow
Day 2 — WhatsApp App vs Business APIOpens Tuesday on your assigned date.