TL;DR: Stop optimizing only for opt-ins—optimize for sales. This guide shows you how to clone your control page, change just one variable (like the hero video), run a clean split test, and interpret results that move revenue—fast.
If you’ve ever stared at your stats wondering why a page with a higher opt-in rate still sells less, this tutorial is for you. You’ll learn a simple, repeatable A/B testing workflow: set a control, create a single-variable variant, run the test long enough, and choose winners based on sales—not vanity metrics.
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Here’s the punchline from a recent experiment: two pages with similar opt-ins, but one produced 15 sales and the other produced just one. The difference? Visitors on the winner had time and reason to scroll, read the letter, see examples, and then buy.
We’ll walk through setting up a clean split test (Control “1” vs Variant “1A”), using global sections to keep layouts identical, swapping only the hero video, refreshing thumbnails for clarity, documenting each change, and pushing the new winner to control. You’ll also see why an 8-minute timer beat a 2-minute timer on sales, and how above-the-fold opt-ins can sometimes hurt purchases.
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What You'll Learn: How to plan, implement, and evaluate a proper A/B test in your funnel builder, including cloning your control, isolating a single change (like video), setting traffic splits, and interpreting results that prioritize sales conversions over opt-ins.
Winning pages aren’t always the ones with more opt-ins—optimize for sales, not vanity metrics.
Change one thing at a time (e.g., only the hero video) to get clean, actionable results.
Timers matter: in one test, an 8-minute timer outperformed a 2-minute timer on sales.
Above-the-fold opt-ins can distract from reading the sales letter, reducing purchases.
Always document your tests and promote winners to the new control—then keep iterating.
Access to your funnel builder with split testing capability (control and variant pages)
Two page versions (Control “1” and Variant “1A”) and a reusable “Top”/hero global section
Your video hosting link(s) and updated thumbnails for clarity
Analytics that track both opt-ins and sales conversions
A simple test log or notes system to document each change
Time Required: 45–60 minutes to set up; 7–14 days to collect data (traffic dependent)
Difficulty Level: Intermediate
Before testing, review what’s actually happening. Don’t stop at opt-ins—dig into sales. Look for mismatches where opt-in rates are high but purchases are low. Example real-world data points to look for:
Compare opt-ins to sales: Do similar opt-in counts produce wildly different sales (e.g., 15 vs 1)?
Check purchase rates: Identify pages converting at 8%+ versus under 1%.
Note page elements: Is the opt-in box above the fold? Is there a logo at the top? Are headlines plain vs decorated?
“If you got the same amount of opt-ins coming in… how in the world do you have 15 sales versus one sale? Something’s broke.”
Great tests start with a single, specific change. From the insights above, pick one variable that could influence sales (not just opt-ins). Example hypotheses pulled from winning/losing variants:
Video-first impression: “A live, on-camera intro will convert more buyers than a screen-share starter.”
Timer length: “An 8-minute timer provides enough urgency and time to read; 2 minutes is too short.”
Above-the-fold focus: “Removing the above-the-fold opt-in increases reading and sales.”
“People were not going to buy right here until they went through the whole entire page and read my letter and saw examples.”
To isolate the effect of one change, the control and variant must be identical everywhere else. Use your builder’s global sections to keep the hero consistent across pages.
Duplicate your control page and name it clearly: “1” (Control) and “1A” (Variant).
Create or update a global “Top” section (hero area). Save it so both pages can reference the exact same block.
Apply the “Top” section to both pages and remove any previous test elements (e.g., a failed opt-in button).
Now make exactly one change—nothing else. In this example, swap the hero video so the variant uses a different opener (e.g., standing on-camera vs screen-share).
Open Variant “1A” and click into the video block.
Paste the new video URL and save.
Refresh/update the thumbnail. Save a quick screenshot if needed so you can tell the videos apart at a glance.
“People need more time.”
Turn on your A/B test and send traffic evenly to both pages. Keep detailed notes so you know what was changed and when.
In your funnel’s split testing panel, set the Control as “original” and the Variant as “alternate.”
Set a 50/50 traffic split to start (adjust later if you have strong priors).
Create a test note: “Original video vs Alt video,” include date/time, traffic source, and screenshots of thumbnails.
Don’t call winners too early. Allow enough traffic and time for reliable conclusions—and prioritize sales over opt-ins.
Primary metric: Sales conversion rate (buyers/unique visitors).
Secondary metrics: Opt-in rate, time on page, scroll depth.
Duration: Aim for at least one full buying cycle or 1–2 weeks (traffic dependent). Use a sample-size calculator to estimate needs.
Helpful resources:
When a variant wins on sales, make it the new Control and write down exactly what changed and why it worked. Keep a running log so your team can learn over time.
Set the winning page as the new Control.
Update your notes: “Winner: 8-minute timer over 2-minute timer,” or “On-camera intro beat screen-share intro.”
Queue the next single-variable test (e.g., headline style, logo placement, above-the-fold opt-in).
Changing multiple variables at once: You won’t know what caused the result. Change only one thing.
Chasing opt-ins, ignoring sales: A higher opt-in rate can still produce fewer purchases. Judge by sales.
Too-short timers: Over-urgency can backfire. In one test, 8 minutes beat 2 minutes for sales.
Above-the-fold opt-in distraction: If your offer needs context, force a scroll so people read your pitch.
Calling winners too early: Run long enough to reach statistical confidence and account for buying cycles.
Name clearly: Use “1” for Control and “1A” for Variant. Keep a simple test log with dates, screenshots, and notes.
Use global sections to keep shared areas identical and prevent accidental changes between variants.
Refresh thumbnails so you can instantly recognize which video/version you’re looking at in your logs.
Prioritize macro conversions (sales) over micro conversions (opt-ins, clicks).
Iterate endlessly—each winner becomes your new Control.
Optimize the sales journey, not just the top of the funnel. Remove or reposition above-the-fold opt-ins and ensure readers engage with the sales letter and examples before asking for the opt-in or purchase.
Test longer durations. If buyers need time to read, a short (e.g., 2-minute) timer can reduce trust and suppress sales. Try 8–10 minutes and compare.
Cache can delay updates. Hard-refresh or clear cache. Re-upload the thumbnail, then confirm the correct video ID/URL is saved in the variant.
Extend the test to get enough traffic, or tighten your hypothesis. If traffic is low, run the test longer or focus on a higher-impact variable like the hero section or offer framing.
Build a backlog of hypotheses and test them in order of potential impact. Promote winners to Control, document the lesson, and line up the next single-variable test to keep compounding improvements.
Create a 4-week test plan (video intro, timer length, opt-in placement, headline style).
Set up tracking dashboards for opt-ins and sales.
Schedule weekly reviews to pick a winner and launch the next test.
At least one full buying cycle or until you hit the minimum sample size required for significance. For low-traffic funnels, run 1–2 weeks or more.
Sales conversion rate. Use opt-in rate, time on page, and scroll depth as secondary diagnostics—not the final verdict.
Not in a single A/B test. To learn what causes changes, test one variable at a time. Use multivariate tests only if you have substantial traffic and a clear plan.
Test it. If your offer needs explanation and proof, forcing a scroll can increase reading and purchases. In some cases, removing the immediate opt-in improved sales.
Too-short timers can reduce trust and rush readers. In the example here, an 8-minute timer outperformed a 2-minute timer on sales.
Keep it simple: “1” for Control and “1A” for Variant, then roll winners into the new Control. Log each test with date, change, and outcome.
Set an even split (e.g., 50/50). If your platform drifts, manually adjust allocation or restart the test. Ensure sources are consistent across variants.
Use a calculator to input baseline conversion and minimum detectable lift. Start here: AB Test Sample Size Calculator.
“8.38% of people bought over here and less than 1% bought over here.”
“Logo at the top, more decoration in the headline… vs no logo and a plain headline—this failed because they didn’t have a chance to see the whole page.”
“This split test is now live.”
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