Explorez tous les épisodes du podcast IntelliJAMS
| Titre | Date | Durée | |
|---|---|---|---|
| IntelliJAMS EP 061: How Much Traffic Do You Actually Need To A/B Test? | 15 Jun 2026 | 00:09:46 | |
How much traffic do you need to A/B test? And is your brand actually big enough to run a real experimentation program? These are two of the most common questions Shopify merchants ask before getting started, and most of the time, the answer is "less than you think." In this episode of IntelliJAMS, Alex and Adam break down the actual thresholds that determine whether A/B testing makes sense for your store. They get specific: what order volume you need to reach statistical significance, how your AOV changes that math entirely, what annual revenue level makes an experimentation program pay for itself, and what to do if you're not quite there yet. Here's the short version: if you're doing 500–700 orders a month, you likely have enough volume to run meaningful Shopify A/B tests — especially if you're testing high-traffic pages like checkout and cart instead of niche landing pages. And if you're at $3–5M in annual revenue, a well-run experimentation program that delivers a 3–5% revenue lift will typically pay for itself within a few months. But traffic and revenue aren't the only objections. A lot of brands ask "is my brand big enough to A/B test?" not because of traffic, but because they don't have the team — no dedicated CRO specialist, no data analyst, no developer on standby for test builds. Adam makes the case that AI has largely closed that gap. What used to take four people can now run with one operator and the right tools. They also dig into the AOV problem: a furniture brand doing $5M a year on $4,000–5,000 couches might only process 80–100 orders a month. At that volume, reaching statistical significance on an A/B test takes so long it stops being useful. The math on "how much traffic do I need to A/B test" isn't just about visitors — it's about conversions, and AOV determines how many conversions you're working with. If you've been putting off testing because you assumed you weren't ready, this episode is worth watching before you make that call. Timestamps: Topics covered: How much traffic you actually need to A/B test on Shopify Ready to start testing? Join GEM Academy for free courses and a community of Shopify brands sharing what works: https://www.skool.com/intelligems-academy-1535 Website: https://intelligems.io | |||
| IntelliJAMS EP 060: The Frequently Unanswered Questions | 08 Jun 2026 | 00:25:50 | |
Your product page probably does a decent job explaining what you sell. But is it answering the questions customers are asking themselves and never typing into a chat widget? Adrian Stewart, co-founder of Scale Messaging, has a framework for finding those gaps, and it can change the way you approach A/B testing your messaging. In this episode of IntelliJAMS, Alex and Adrian dig into the "Frequently Unasked Questions" framework: four categories of questions shoppers silently ask themselves while browsing your site. They cover where most Shopify brands fall short on messaging, why reducing friction is easier than building motivation (but both matter), when urgency tactics actually work versus when they erode trust, and how to build hypotheses around messaging that you can test and learn from. Timestamps: Topics covered: The Frequently Unasked Questions framework (understanding, motivation, difference, trust) Why "difference" is the most overlooked messaging gap on product pages The motivation-to-friction ratio and how it affects conversion When urgency and scarcity tactics help vs. hurt your brand How traffic source (paid social vs. search) should shape your messaging strategy Building messaging hypotheses you can A/B test Message vs. expression vs. placement as three layers of experimentation Why trust is the fastest win for most e-commerce brands Ready to start testing your messaging? Join GEM Academy for free courses and a community of brands sharing what works: https://www.skool.com/intelligems-academy-1535 Connect with Adrian / Scale Messaging: Website: https://scalemessaging.com Connect with Intelligems: Website: https://intelligems.io | |||
| IntelliJAMS EP 059: Why Post-Purchase Is the Money Moment for Shopify Brands | 01 Jun 2026 | 00:13:31 | |
Post-purchase upsells sit at the exact moment a customer has already committed — credit card swiped, conversion done. That means there's zero risk of hurting conversion and pure upside potential for your AOV. In this episode, we break down why post-purchase might be the highest-leverage Shopify A/B testing opportunity most brands haven't explored yet. Timestamps: Topics covered: The economics behind post-purchase upsells (zero incremental CAC, no conversion risk) A real-world CBD brand case study: 50% off second pack, 40% take rate, 20% AOV increase Three post-purchase strategies: same product discount, complementary products, and clearance/inventory sell-through Why consumption scales with supply — and what that means for repurchase rates How to match your upsell strategy to your margin profile Running post-purchase tests in parallel without interaction effects How Intelligems measures incrementality, revenue, and profit on post-purchase offers Want to start testing post-purchase upsells (or anything else)? Join GEM Academy for free courses and a community of brands sharing what works: https://www.skool.com/intelligems-academy-1535 Connect with Intelligems: Website: https://intelligems.io | |||
| IntelliJAMS EP 058: Outputs vs. Outcomes: A Better Way to Think About A/B Testing | 27 May 2026 | 00:13:58 | |
Running 10 tests a month sounds productive, but if none of them are tied to a real business question, you're just taking swings for the sake of swinging. In this episode Adam and Alex dig into why "how many tests should I run?" is often the wrong question, and what to ask instead when you're building an experimentation program on Shopify. In this episode of IntelliJAMS, Adam and Alex explore the difference between test output and test outcomes, how to run concurrent tests without confounding your results, and why elevating the conversation from "number of tests" to "strategic priorities" changes everything. Timestamps: Topics covered: Why counting tests is an output metric, not an outcomes metric How to reframe testing around strategic business goals Running concurrent A/B tests on Shopify without confounding data Segmenting tests by funnel stage and visitor type How one test can lead to five new questions Pushing back when stakeholders demand a test quota Real-world example: killing a checkout upsell test 24 hours in The "test the plan, don't plan the tests" framework Want to sharpen your experimentation skills? Join GEM Academy for free courses and a community of brands sharing what works: https://www.skool.com/intelligems-academy-1535 Website: https://intelligems.io | |||
| IntelliJAMS EP 057: Calling out the anxieties of A/B testing | 27 May 2026 | 00:27:13 | |
A/B testing can feel high-stakes, especially in e-commerce. You launch a test, check it an hour later, and either think you've broken your store or discovered a goldmine. Neither is true yet. This episode is a therapy session for anyone who's felt the anxiety of running A/B tests on their Shopify store. In this episode of IntelliJAMS, Alex McEachern and experimentation expert Ally Petretti walk through the most common anxieties of A/B testing and how to manage them with better process instead of more stress. Should you check your A/B test results every day? What is statistical significance and when should you end an A/B test? What is the novelty effect in A/B testing? What is metric shopping in CRO? How should you communicate A/B test results? How do you handle test ideas that aren't backed by data? How do you coordinate A/B testing across teams? Join GEM Academy for free courses and a community of brands sharing what works: https://www.skool.com/intelligems-aca... Connect with Ally Petretti:
Website: https://intelligems.io ---- | |||
| IntelliJAMS EP 056: Instead of planning your tests, test your plan | 11 May 2026 | 00:28:20 | |
Conversion rate went up, but did profit? Most testing programs optimize for one metric in isolation, and that's exactly where they go wrong. In this episode, Amanda Siegel (Director of E-commerce at Scale Media) breaks down why she stopped calling what she does "CRO" five years ago and started treating testing as a tool to validate business strategy, not just chase website wins. In this episode, Alex and Amanda explore what happens when you balance conversion rate, AOV, and subscription adoption in every test instead of picking one, why the old UX tricks (spin-to-wins, slashed prices, CTA color swaps) are losing their edge, and how to get buy-in for short-term metric dips that lead to long-term growth. Timestamps: Topics covered: Why conversion rate optimization (CRO) is too narrow for modern e-commerce Balancing conversion rate, AOV, and subscription adoption in a single test The counterintuitive finding that reducing discounts can improve conversion Getting executive buy-in for short-term metric trade-offs The growth experiment mindset for Shopify brands Why testing needs to be cyclical and revisited over time --- Want to think bigger about your testing program? Join GEM Academy for free courses and a community of e-commerce operators sharing what actually works: https://www.skool.com/intelligems-academy-1535 Connect with Amanda Siegel: https://www.linkedin.com/in/amandadsiegel/ Connect with Intelligems: Website: https://intelligems.io | |||