How To Optimize Your Ecommerce Store With A/B Testing — Yi Hung Lin | What A/B Tests To Run In Shopify, Why A/B Testing Is A Proven Growth Method, What Test Length Works Best, Why Most Tests Won’t Beat The Control, Why Code Cleanup Matters (#395)

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In this episode, Yi Hung Lin (Jeffrey), founder of AB Convert, breaks down how A/B testing helps you grow a Shopify store the smart way. 

Jeffrey explains how smart testing can significantly boost your profits. 

Learn how to make data-driven decisions about pricing, shipping thresholds, and other key factors that can increase conversion rates by 10-15% without spending more on advertising. 

Topics discussed in this episode: 

• What makes A/B testing a scientific growth tool. 
• How simple tests like banner copy swaps yield conversion data. 
• Why starting with a clear hypothesis and the Store Growth formula matters. 
• What native Shopify experiments AB Convert enables. 
• Why only about 7% of tests are expected to win. 
• What test duration to aim for—10K sessions or 200 orders. 
• Why pre-test prep like theme cleanup and code audits is important. 
• How real case studies—like 5% price hikes or AOV boosts—prove ROI. 

Links & Resources 

Website: https://www.abconvert.io/
Shopify App Store: https://apps.shopify.com/a-b-convert-price-a-b-test
LinkedIn: https://www.linkedin.com/in/yi-hung-lin-040889138/
X/Twitter: https://x.com/billionxdev 

Get access to more free resources by visiting the show notes at
https://tinyurl.com/5ajsjnpn 

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Transcript

[00:00:00] This episode is sponsored by ahrefs, the all in one marketing intelligence platform, trusted by SEO professionals, content creators, and digital marketers around the world. Whether you're doing keyword research, checking back links, or analyzing competitors, ahrefs gives you the tools to make smarter marketing decisions.

Explore what ahrefs can do at [00:00:20] ahrefs.com.

Hello and welcome to another episode of the eCommerce Coffee Break podcast. Today we wanna dive into the power of testing. And how this can help you to grow your Shopify store faster, Marty, and with your guest work today, Jeffrey, he's the founder of AB Convert, a no-code AP testing tool built for [00:00:40] Shopify merchants.

He has bootstrapped his way to over 1300 active users and is on track to towards 1 million in a a r. His mission is to make conversion testing simple, effective, and accessible to every store owner. And that's what we're talking about. So let's dive into the welcome into the show. Hi, Jeffrey. How today? Hi everyone, this is [00:01:00] Jeffrey.

And the fun fact is we actually be pronounced as AB convert. So there is a meaning behind this name That is you do AB test and then convert more, so it is the entire meaning of the name. So happy to be on this show talking about the experience, the journey, and tips for helping you guys scale your e-commerce store.[00:01:20] 

Yeah, let's dive right into it. So, when you grow an online store, guessing what works is not really the right way to do. Maybe let's start with, for someone who has never tried AB testing before, what is it and how, why does it matter for online stores? So, uh, AB testing is actually a very scientific approach for anyone [00:01:40] who want to know, uh, a result behind a hypothesis.

So, for example, if you, uh, make, let me make the example more, um, casual like. Closer to day-to-day life. Uh, for example, you have a physical shop and then you want to know whether a banner is better for a coffee [00:02:00] that says, uh, $15 for, uh, coffee plus bagel. Or you want to highlight more on the delicious of your, your, uh, food, like, um.

Best bagels of the town. So this is having two banner of the physical store. So in this settings, the [00:02:20] AB testing wouldn't be possible, but if you bring this up to the online settings, uh, things become possible so you can be able to build two versions of your store and then some mechanisms behind and redirect or like direct customer to different versions and then collect data.

So it will be a very useful scientific [00:02:40] approach to answer any of the questions. Uh, hypothesis. So it was, uh, it was ma majority used in software development, like back in the years, but it gradually become popular as the tool technology improves and then now it, it's somewhat, it must do in a e-commerce or like a deeper D two [00:03:00] C brand operating.

I remember the running joke back in the time that people were starting to test a view button against the red button and to see what works better. But obviously that's the wrong approach. So if somebody's, um, new to it, what would be the first thing for a Shopify store owner to start with when they want to do ad testing?

So, um, [00:03:20] so AB testing might sounds, you know, overwhelming at a first glance. Because, you know, there'll be a lot of guessing, misunderstanding behind it. People will think about, oh, this is very complex. Uh, it needs a lot of work. And, um, uh, I should definitely invest like a couple hundred dollars in the vendors or the software I need to [00:03:40] actually hire a consultant.

But it's actually not that hard because AB testing it just, uh. A way to make a decision by data. So if you follow this principle, everything will become clear. So what I means, uh, a way to make a decision by data is. First of all, you need to [00:04:00] know what's the problem you wanna optimize. So, uh, for people just come to your AB testing, they are looking for a formula that's solving change their operation overnight, which is impossible.

So, uh, we have to set, uh, right expectation. So, uh, what do you do to improve the store in general? That's [00:04:20] something you have to think about. And then. You divide by these actions and label it with each of the data source. So I would say the first step is you go back to thinking this frameworks like what's like a growth or e-commerce store.

It can be, uh, come down with the formula that, uh, uh, your store growth is [00:04:40] equal to a LV times traffic, times the retention. So if you go by this formula and then you try to look at the store, the problem you're facing with and categorize which part of this. Problem you're having the most and that's blocking your growth, then you jump right into the field.

And when you was driving into the field, you wouldn't be, you [00:05:00] know, just guessing around. You have to have a clear source of truth to tell you where exactly is the problem. So you need a data source. Things like Shopify report, ga, clarity, hard job, things that can help you get more information on, uh, identify your problem will be really helpful.

So after you did that, I always [00:05:20] suggest you, you know. Have your data ready, then go and look at the data. And then maybe something you can look at is like a drop off, like a ga sessions, like a traffic source to make yourself, you know, have this right, uh, right mindset or having this, uh, right, uh, conceptions [00:05:40] of what exactly uses the problem.

And then after digging into this problem, playing around with it, you might probably have some, uh, hypothesis or have a guest like. Based on your operations, your business insight, what kind of improvement you should do, so that that's the time when A becomes testing come into [00:06:00] play. So, uh, I also just first step is always know your problem first.

Before you start AB testing, where is the, uh, you know, pricing problem or a shipping problem, or just simply the design problem? You always have to solve problems and then you dig into it and then just do some homework research and talk to people, [00:06:20] and then you, you know, just find some solutions and before you come to the AB test, because AB testing is not done, something that you can just come in and plug and play right, and hope things gotta work.

It's like. It's just a process to help you make a smarter decision. So to make a decision, you have to have a reference point. So always start with the data. Mm-hmm. I like the [00:06:40] approach that you really look into the data and in the past it was really a pain in neck, specifically with Shopify to do AB testing.

Um, there were third party tools, but there were not completely natives to the platform and it was difficult to really slot them in. You have changed this with AP Convert and um, tell me a little bit on how you approach testing within a [00:07:00] Shopify store. So, uh, when I first come to in this space, I was like a totally newcomer and fun fact is, uh, I only started this AB testing software because of my, uh, college friends is having a huge issue to get the pricing right.

So for me, I always, I'm the same. I always start with the problems. So I start with the problems. That's [00:07:20] very simple. How can I get my friend store having the right price point? So this is the first problem I wanna solve. And then I look around, there's not a good solution to solve it either too expensive or not useful at all.

So, um, I just dig in and then try to think about, um, uh, if it's the problem I'm [00:07:40] going after, what should be the approach? So I figured out, uh, this thing should be first, uh, used by. Nearly all of the Shopify store because everyone has this problem, right? Everyone has to get the price point, right? Whenever they start store, whenever they have a existing store, whatever, to scale.

So I [00:08:00] just, uh, dig into this problem and spend a lot of time to figure out what's like the most, uh, native feature to get the price right. So, uh, I figured out a price testing feature at start. It was just a very simple, uh, [00:08:20] uh, very simple functionality that you can still test the page in a product, uh, people can add to car with different price product.

And then just, I start from here because, uh, I look around and I look at this problem and look at my solution and ask myself another questions that, uh, if this [00:08:40] problem is going to solve by me, what will be the problem? And I figured that. For those AB testing software like vw, Optimizely, this software, they have a very strong knowledge in terms of, uh, web technology.

In terms of browser, I have, I have nothing to do with that. I don't have the background, I don't have the engineer anything, but all [00:09:00] I have is like. The knowledge of what exactly is the problem and also the experience with Shopify. So I sort of go back to dig more into what's like the native Shopify AB testing will be like.

So I figured it will be a pricing, it'll be something that you have to touch with the Shopify backend and do some API call, you know, just [00:09:20] become a Navy Shopify feature. So I, I figured that a pricing is a point, discounts the point and shipping it a point. So I, uh, gradually, you know, just like. Uh, combined with these pieces and then work on this feature and then gradually ship to a, uh, complete ab testing feature.

So there's a [00:09:40] pricing test. There's a shipping test. There's exactly, uh, all kinds of tests that can only be done in the Shopify. So the starting point is, uh, ask myself what would be the most needed feature for the seller. And I figure it's like. Uh, it will be divided by different funnel. So first the impression [00:10:00] people come to the website, seeing the price, and then second thing they.

Click the act to card button, go to the checkout, and things that made people drop off in the checkout is certainly just tripping. So I'm playing with the number to get this number right first, and then I go back to fix the things that, uh, people are concerned about the, if they experience the [00:10:20] design layout.

So I divide this, uh, by the funnel and the, the scenario, and then I ship this feature accordingly. But with the, my data, all I need to do is. Uh, it's something that can only be done by us, one by me, and it has to be really shoved by native. So this is how I decide the [00:10:40] entire software. Let's take a moment to thank ahrefs for the free web analytics tool, a free privacy first analytics platform.

It gives you a clear picture of your website activity, doesn't use cookies, and won't weight down your pages. It's incredible, fast, easy to set up, and built by the same team behind one of the most trusted SEO tools in the world. Best of all, it's completely [00:11:00] free and included in ahrefs Webmaster Tools. Plan.

Head over to ahrefs.com/awt to sign up. You will find the link also in the show notes. I like that and I think it's a very pragmatic approach and I think you solved the problem for thousands of sellers out there. We can see that you have a ton of clients burn out, uh, but it really came out of [00:11:20] a practical problem solution scenario.

Now when it comes to the AB testing, and you said data is the point where you make a decision, but you need to have enough data to make a educated decision. What's one mistake that you see store owners make when it comes to running AB test? So when it comes to AB testing, [00:11:40] um, there are several mistakes.

So, uh, the most common mistake is people think about a testing, like a one-off thing. So they just come and. Try to do a AB test and hopefully suddenly the entire things change overnight. But I think this is a huge mistake that, uh, most of the, [00:12:00] uh, beginning of ab tester will, will done to solve or like to bypass this mistake, we need to have the right expectation.

So, uh, uh, this is actually a research or, uh, uh, evidence from, uh, from a lot of scientific or like. Done by enterprise, the in-house research. So, [00:12:20] uh, the conclusion is for all of the AB tasks, only 7% of AB tasks will work. So before we start AB tasks, we have to have this in mind because, uh, chance of that you are getting the things right at first time, then you're lucky.

But most of the time things doesn't work. So, uh, which means you need to be. [00:12:40] Prepare, you need to be, uh, ready for this entire journey. You have to prepare your roadmap. You have to make your depth ready, designer ready. You have to have your data ready and you, you start a long process, more like a, uh, a quarterly AB testing schedule, and they dive in every single point [00:13:00] that can possibly improve.

And then, and then. Be very patient to move this change, ship it one by one, run through the ab test one by one, and don't lose your patient. Just keep follow your plan until you get to a point. So, uh, by, by knowing this, you can overcome a lot of, uh, [00:13:20] tempation, for example, I just wanna do a test right now. Uh, no matter what, I wanna ship it so that will translate to a task is not execute well.

They have some configuration error. Has some, you know, uh, teams issues that's, you might not be aware at the first glance. And then second [00:13:40] is being given up too early because you are an AB task and then you figure, oh, this is not probably my thing, and you are just quitting right away. And then you're missing a lot of opportunity out there.

And third thing is, uh, if you're trying to get the things done at first, then chance are that you might. [00:14:00] Doing the change too drastically. So for example, you are getting right, your right, uh, right price point, and you don't have the patient. So maybe you're just, just testing 50% difference of your price, then a hundred percent of the time or near a hundred percent of the time, it'll be either pretty good or pretty [00:14:20] bad.

So if you are on the wrong side, then you figure, oh, okay, lose money. And then I don't believe this approach. So, uh, to summarize, I will say, uh, just to understand the nature of AB test then can help you to be, you know, anxious or be, uh, [00:14:40] impatient or be, you know, too accurate to see your results. So I'll say AB test is a long one, and you have to have this mindset before you get started.

Okay. I think that's a very important point that you made there. Unfortunately, a lot of founders, um, online store owners are very impatient people, so I hope that helps them with understanding how a b testing works. [00:15:00] Now, how long would you run a test before you make a decision, before you trust the results?

So, um, this will depends on the traffic because. Like I mentioned in the beginning of, of the episode that, uh, AB testing is all about, uh, running the experience, collect data, and then make decision upon this data. So it'll go [00:15:20] back to a core that how much data you can collect in a certain amount of time.

So for the people who has, uh, you know, million session in a month, may, maybe they can have the, um. Very sufficient data in a day or two days, or people who are just starting out, they need to accumulate data for a longer time. But, uh, [00:15:40] in general, I would say for a certain test or a typical task, it's sufficient to make a decision as done.

You have more than 200 orders or 10,000. Sessions, and this is the just general rule of thumb, but if you wanna go deeper, I'll suggest you have, uh, this data run by the statistical [00:16:00] analysis. It will tell you, uh, based on this difference, observe in different variants. Just to give you notes. A variant in the a test means different version of your software.

So if the difference is large enough, but the data is not. That much. Maybe it's still conclusive, [00:16:20] but if the difference is really close, then you need more data to make it statistical significant. So there are two way, just general rule of thumb, uh, 10,000 sessions, hundred orders, or you run a statistical analysis tool to decide.

And uh, the last point I want to add is, um, if you [00:16:40] run the AB test, you somehow get a sense of how your traffic looks like. For the following of your EB test, I would suggest keep a fixed schedule. So if, uh, for example, if your first test is running for seven days, then I'll suggest for the following test you run as you all follow for this seven day schedule because it will [00:17:00] make the analysis, analysis more consistent.

Yeah. Mm-hmm. No, that makes perfectly sense. And when it comes to the testing itself, and you mentioned that you have a Shopify app developed for this. So talk me through how it works. Um, what tasks do I need to do in there? Um, how is the set up [00:17:20] working? Just talk me through it. So, uh, so for AB Convert, uh, our missions is making ab test accessible for everyone.

So, uh, we, we know that to run a successful ab test, you, you will need to co, uh, deal with a lot of complex data. For example, to do a price test, you need to configure a thing. You need to [00:17:40] make a data better works on. Some of the custom code, you know, work with the bundle and to, you know, abstract that away and make the entire experience very smooth.

We actually have a dedicated onboarding process for all of our merchant. They're willing to do prices. Our expert will step in to look at your theme. [00:18:00] Through a website audit, and if there's any huge blocker in the impact, the AB testing result, they will help you to configure that. So install the app and then request a so-called thin check from our team.

Our team will step, step in and took some time, uh, generally one to three business days to finish this set up onboarding. And [00:18:20] then after that you can start testing as you wish. All of our, our AB testing are really straightforward. You can even start a ab test, a price test in 30 seconds. Nothing that, uh, nothing that's too complicated or too advanced.

Just follow the, uh, ui, follow the steps, and then just choose the product, choose the [00:18:40] price and launch it. But, uh, the heavy lifting, uh, you don't have to worry about it because we'll solve for you whenever you just onboard and install the app. Can you share some success stories or case studies of business that you have worked with and what kind of results they saw?

So, um, I've seen a lot of, uh, successful story in the [00:19:00] past, but I think there's a, a, a pattern behind it. So, uh, most of the time we can observe whenever, uh, a store is seriously start to test the price of a product, price of a customer. They're solving puzzle and, uh, their puzzle is like having some unique, um, branding unique, [00:19:20] um, image.

Um, the product. So, uh, they, they are always be figuring that whether I'm charging too low and whether I can increase, increase the price. So they come to us and run a price test for the whole, so because the product, the model are the same, they have all the same price point, [00:19:40] so it just, they just increased the price for 5% and it turns out to be a very successful test.

Uh, uh, the, the, the uplift is more than 20% and they, they switch the price immediately in the follow quarter. They see 6% to 10% increase on the revenue itself and [00:20:00] translate to 15% of the profit. This is the first, uh, specific story, uh, I would say. And then the other story is, uh, more about the shipping tahrefshold, getting a shipping test.

A lot of, um, customer, especially customer in Europe that are selling to America and they're, um, having this, uh, height or they having [00:20:20] this shipping tahrefshold, but sometimes they're selling too low. For example, uh, a store that has a a OV of $30 and they just set the, uh, shipping. Tahrefshold for $30, which means nearly all of the people get free shipping and, uh, they, they, they, they try to [00:20:40] increase this, uh, a LV or reduce the shipping cost.

So they run the higher shipping tahrefshold test, uh, increase the shipping tahrefshold to $50, and it will, it's the perfect spot that, uh. Since all of the product will be under 30 to 20 to 30 range for their, their store, uh, it means people to reach the first shipping have to add [00:21:00] another item to the basket.

So immediately they increase the a OV more than 50% and, uh, earn more on this shipping price. So, uh, conversion rate actually increase. The shipping revenue has to increase and it result in like five to 10% contribution of their following revenue. So I would say these are are [00:21:20] two simple pattern that's occurring all the time.

Get things, get the price right, and cut the shipping right and, um, to them, but few. So, uh, this is, uh, some of the successful story during the past. Just to our listeners, how impactful and how powerful b testing is. So if you can get just the conversion [00:21:40] rates on your shipping price or the price overall, right?

Talking about 10, 15% more profit at the end of the day, uh, that's huge number specifically for D two C companies. Now, is there any kind of harm work that immersion needs to do before they can get started? So, uh, I, I'll say there's, uh, a so-called [00:22:00] homework, but, uh, I'll say like, just I mentioned before, the, um, the expectation has to be right at first, and if you are, uh, quite mature brand, then you have to be able to align your team to execute this AP testing because AP testing is not just about.

Running a testing campaign, [00:22:20] but it also relate to analyzing the data. So if you have a in-house data analyst, uh, try to let them know. We need to dig in the data to some point and then have some, uh, insight or suggestions from data. And for the developer, you can make them aware first that maybe for some complex [00:22:40] theme, uh, we need to have an update.

So they may, maybe they, they need to be having a code changes. Maybe the, um, you know, uh, the code that's like not being fixed for a long time had to be improved again. And in order to make the AB testing right, we need to fix some fundamental issues like, uh, page loading [00:23:00] issue. So for some Shopify brands, they are having a store that is isn't for years.

They're installing, uh, hundreds or thousands of apps. They're. Snippet left order, I would suggest you go and remove all of that on use snippet because AB testing is all about, uh, manipulate [00:23:20] this website performance, uh, uh, behavior. So, uh, there will be highly likely that has a conflict with the script. So in order to prevent wasting the money on tests, we need to, you know, get the website clean, get the teams ready, and be ready to execute.

No, I think that's very important what [00:23:40] you said there, and I think a lot of store owners, um, now you look at their store and see all the plugins that they have installed over the time and they're just lowering down the side. Who, who's your perfect customer? Uh, so, uh, for a perfect customer, I would say, uh, the two types of customer which fit really well in, uh, our app.

[00:24:00] First is the, the people who just get started. They're really eager to drive traffic into the platform, but they just don't know what's like a purpose setup. Uh, it could fit. And the second is the store. They are in a scaling phases. They have decent amount of traffic, but just. Doesn't have a optimized process.

They don't have the optimize user [00:24:20] journey or optimizing price point or optimizing, you know, like a loyalty program. So, uh, I would say, uh, these are a good fit and especially for the people on a scam stage. Uh, they don't wanna spend too much. Um, bringing new traffic or buying new resource, exploring new channel, they can just come back to fix the [00:24:40] fundamental of their store, of their entire user journey, so they will be a perfect match.

How does the pricing work? Oh, so for our pricing, uh, we currently are joining, uh, we, we currently have the pricing model of the flag rate. So we have listened, heard about, about a lot of the complaint for our [00:25:00] users and the, uh. The tools for other tools, it working great at the beginning, but throughout the time it's scale with their operation.

So things like usage or order base, uh, we don't do that. We only offer cloud rate divided by Shopify plan because, uh, by Shopify plan we have different works to accommodate and we [00:25:20] have different, you know, uh, service login. So for basic and Shopify user, it is like you can start a testing with $59 for advance.

Event Shopify, you can start a test with 1 49 for plus customer, you can start any test as two $49, including the customer onboarding and the dedicated support channel. Mm-hmm. [00:25:40] That's very straightforward and I think it's a no brainer at the end of the day before our coffee break comes soon and today. Is there anything that you wanna share with our listeners that we haven't covered yet?

I'd like to share about, um, in this past. Two years journey. What I've observed, and I wanna encourage the people to do, because we all know it's such as a hard time for D two [00:26:00] C, things are getting hard and people are questioning about this, uh, business model or, uh, whether you can be successful in this field, but.

So in the past year, I've seen a lot of people just keep putting in hard work and then, and then try to make things, make good things. So I think the, the most important [00:26:20] thing, either on making a good apps or making a good store is know your customer really, really well. Talk to your customer in the, uh, database basis and surround yourself with the smart people.

Uh, for example, if you are listening to podcasts, chance of that, you're having, uh, more input to your business. So surround yourself with good [00:26:40] entrepreneur and then just keep putting the hard work and don't lose your belief. I, I believe that in the end of the day, everyone will have a good result. Yeah, I totally agree.

I think, um, optimizing is one of the key points that everyone should have on point. Instead of spending more money on Facebook ads, um, optimize their store first, um, that's where the money is better [00:27:00] invested. Can people go and find out more about you guys? So, um, simply go on Shopify App Store Search AB Convert, and you can find us.

Uh, we have, uh, pretty standout logos, or you can just search on Google Convert. Uh, and you can find our website ab convert.io. That will be excellent. I will put the [00:27:20] links in the show notes. Then you just one click away chat. Thanks so much. Great giving us an overview about AB testing. I wish I would have your tool eight years ago when I was running my own store.

That was something I was really missing and I'm glad that you came up with it and now everyone can use it. Thanks so much for the time today. Thank you, cla. Thank you everyone. Have a good day. Thanks again to ahrefs [00:27:40] and ahrefs Web Analytics for supporting the show. If you're looking for a clean, fast, and privacy focused analytics tool, try it for free at ahrefs.com/awt.

That's A HRE fs.com/a wt. You will also find the link in the show notes.

Hey, Claus here. Thank you for joining me on another episode of the [00:28:00] e-Commerce Coffee Break podcast. Before you go, I'd like to ask two things from you. First, please help me with the algorithm so I can bring more impactful guests on the show. It'll also make it easier for others to discover the podcast.

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