Lucas and Luna dig into a counterintuitive CRO case: a well-known subscription service ran an A/B test changing its 'Start Free Trial' button from green to blue, expecting a lift, and saw conversion drop 12 percent. They unpack why colour changes fail when they ignore user expectations, the psychology of habitual design patterns, and how the team recovered by reverting the change and running a follow-up test with a more meaningful variable. Specific numbers, real lessons, no fluff.

#ABTesting #ConversionRateOptimization #CRO #ButtonColour #ColorPsychology #UserExpectations #HabitualDesign #UXDesign #LandingPageOptimization #SubscriptionBusiness #Marketing #FexingoBusiness #BusinessPodcast #CROStrategy #FalsePositive #DataDriven #ConversionFailure #DesignPatterns

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Many CRO practitioners run A-B tests without calculating the required sample size first — and end up with inconclusive or misleading results. In this episode, Lucas and Luna dig into why sample size matters, using a concrete example: a landing page test aiming for a five percent lift in conversion rate. They walk through the risks of stopping too early, the math behind statistical power and significance, and how tools like Evan Miller's calculator can save you from false positives. Along the way, they discuss a common mistake — peeking at results before the sample size is reached — and why it inflates your false discovery rate. If you've ever been excited about a test result that disappeared after launch, this episode explains why sample size planning could have prevented it.

#SampleSize #ABTesting #ConversionRateOptimization #CRO #StatisticalSignificance #StatisticalPower #FalsePositive #PeekingProblem #SequentialAnalysis #EvanMiller #LandingPage #MarketingExperimentation #DataDrivenMarketing #FexingoBusiness #BusinessPodcast #Marketing #GrowthHacking #Experimentation

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Lucas and Luna dive into a surprising A-B test where a B2B SaaS company saw a 14 percent conversion lift simply by switching from a sans-serif font to a serif font on their landing page. They unpack the psychology behind the change, discuss the importance of typography in conversion rate optimization, and explain why testing even seemingly minor design elements can yield significant results. The episode uses a real case study from a project management software company and explores how font choice affects readability, trust, and user perception. Listeners will learn when to test font changes, how to interpret inconclusive results, and why the interaction between font and page context matters more than font alone.

#ConversionRateOptimization #ABTesting #Typography #LandingPageDesign #CROStrategy #FontChange #Marketing #SaasMarketing #UserExperience #B2BMarketing #TrustInDesign #Readability #DesignPsychology #DataDrivenMarketing #FexingoBusiness #BusinessPodcast #MarketingPodcast #CaseStudy

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In episode 70 of Conversion Rate Optimization with Fexingo, Lucas and Luna explore why traditional frequentist statistics can lead CRO teams astray. They walk through a concrete example: a SaaS company that ran a classic A-B test on a pricing page, got a p-value of 0.04, declared a winner, and then saw results reverse within a week. The hosts explain how Bayesian analysis—using prior data and posterior probabilities—would have caught the fragility early. They break down prior distributions, credible intervals, and the rule of thumb: if your Bayesian probability of beating the control is below 95 percent, hold the test. No math PhD required. This episode gives you the one framework change that can save your roadmap from false positives.

#BayesianAnalysis #ABTesting #CRO #ConversionRateOptimization #FrequentistStatistics #PValue #PriorDistribution #PosteriorProbability #CredibleInterval #SaaS #PricingPage #ExperimentDesign #DataScience #Marketing #BusinessPodcast #FexingoBusiness #Podcast #CROStrategy

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Lucas and Luna challenge the classic A-B testing framework and introduce sequential testing. They explain how traditional fixed-horizon tests inflate false positives and waste traffic, and how sequential analysis lets you peek at results without penalty. The hosts walk through a real example: a landing page test that reached significance in four days instead of two weeks, saving the marketing team sixty percent of their traffic budget. They also discuss how platforms like Optimizely and Google Optimize are incorporating sequential methods, and why every CRO practitioner should understand the difference between fixed-horizon and continuous monitoring. Practical, data-driven, and immediately actionable.

#SequentialTesting #ABTesting #ConversionRateOptimization #BayesianStatistics #FrequentistStatistics #LandingPageOptimization #TrafficBudget #FalsePositives #Optimizely #GoogleOptimize #PeekingProblem #MarketingAnalytics #DataDrivenMarketing #CROStrategy #Business #Marketing #FexingoBusiness #BusinessPodcast

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Lucas and Luna dig into the 'winner disappears' phenomenon in A-B testing—when a variant that crushes the control in the test flatlines after launch. They trace the root cause to Simpson's paradox and segmented analysis, using a real-world case from a mid-market e-commerce company that saw a 12 percent conversion lift vanish within 72 hours. The hosts explain how hidden demographic segments (mobile vs. desktop, new vs. returning visitors) can reverse apparent winners, and walk through a simple pre-launch segmentation check that prevents the problem. By the end, listeners understand why a single overall p-value can be misleading and how to design tests that hold up in production. No fancy stats jargon—just practical guardrails for anyone running experiments.

#ABTesting #ConversionRateOptimization #SimpsonsParadox #SegmentedAnalysis #CROStrategy #MarketingExperiments #DataDrivenMarketing #EcommerceTips #LandingPageOptimization #TestDesign #StatisticalFallacy #ConversionLift #ProductLaunch #DigitalMarketing #ExperimentationCulture #BusinessPodcast #FexingoBusiness #MarketingPodcast

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Lucas and Luna dissect a real A-B test where replacing one lifestyle photo on a landing page — a woman looking at her phone instead of smiling at the camera — boosted conversion by 34 percent. They explore why gaze direction matters, how eye-tracking heatmaps reveal attention patterns, and when to test imagery over copy. Plus, Lucas shares a framework for prioritizing image tests based on page scroll depth and user intent. If you run any form of conversion optimization, this episode offers a concrete, data-backed reason to look beyond button colors and headlines.

#ConversionRateOptimization #ABTesting #LandingPageOptimization #EyeTracking #Heatmaps #UserBehavior #MarketingExperiments #CRO #VisualCues #GazeDirection #ImageTesting #ConversionLift #UserPsychology #MarketingStrategy #DigitalMarketing #FexingoBusiness #BusinessPodcast #DataDrivenMarketing

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Episode 66 of Conversion Rate Optimization with Fexingo tackles a common CRO pitfall: running an A-B test without first segmenting your audience. Lucas and Luna walk through a real example from a B2B SaaS company whose overall test showed no winner, but segmented by user persona revealed a 34 percent lift for IT managers and a 12 percent drop for freelancers. They explain why segmentation before launch prevents misleading aggregate results, how to choose your segmentation variables, and why post-hoc segmentation is dangerous. They also touch on the ad-free listener support model that keeps the show independent. Practical, data-driven advice for marketers and product teams who want to stop running tests that lie to them.

#ABTesting #ConversionRateOptimization #CRO #SegmentedAnalysis #Marketing #Business #FexingoBusiness #BusinessPodcast #SaaS #UserPersona #DataDriven #Statistics #Experimentation #AudienceSegmentation #SampleSize #FalsePositive #HypothesisTesting #Optimization

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In this episode of Conversion Rate Optimization with Fexingo, Lucas and Luna dive into a counterintuitive insight: A-B test winners often fade within days of launch. They walk through a real case from a B2B SaaS company that saw a 19 percent lift on day one of a new landing page — only to see it vanish by day seven. The culprit? Recency bias in the test audience. Lucas explains why a seven-day holdout — where part of your audience stays on the original variant after the test ends — is the only way to catch winner degradation before you commit. He shares the specific math: how to size the holdout group (at least 20 percent of your traffic) and what to look for in the first week. Luna pushes back with practical concerns about sample size and timing, and they walk through how one team avoided a costly full rollout by spotting the decay early. This episode is for anyone who runs A-B tests and wants to make sure their winners actually win in the real world.

#ABTesting #ConversionRateOptimization #HoldoutGroup #RecencyBias #WinnerDegradation #LandingPageTesting #B2BSaaS #StatisticalSignificance #MarketingExperiments #DataDrivenMarketing #CRO #NoveltyEffect #TestRigour #MarketingStrategy #DigitalMarketing #FexingoBusiness #BusinessPodcast #Marketing

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Episode 64 of Conversion Rate Optimization with Fexingo tackles a frustrating experience: running an A-B test that shows a clear winner, only to have the conversion lift vanish completely after you roll out the winning variant. Lucas and Luna break down the real culprit — regression to the mean in high-traffic experiments — using a concrete example: a media site that tested two article layouts over two weeks. They explain why large sample sizes can actually mask temporary effects, how to spot a 'winner' that's really just noise, and a practical pre-launch validation step that would have saved the team two months of lost revenue. No jargon, just a clear framework for deciding when to trust your test results.

#ABTesting #ConversionRateOptimization #DataAnalysis #MarketingExperiments #RegressionToTheMean #StatisticalSignificance #HypothesisTesting #DigitalMarketing #WebOptimization #CROStrategy #MediaSite #ArticleLayout #TrafficAnalysis #MarketingMetrics #FexingoBusiness #BusinessPodcast #MarketingPodcast #LucasAndLuna

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