How To Fix E-commerce Conversion Rates: The AI-powered Path To Value-based Commerce — Mike De La Cruz | How Brands See 20% Conversion With AI, How AI Personalizes Shopping, How Shopify Merchants Implement AI, What The Future Of Shopping Looks Like (#385)

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In this episode, we dive into the world of ecommerce conversion optimization and explore the AI-powered path to value-based commerce. 

Our guest Mike de La Cruz, President of iAdvize, shares insights on how artificial intelligence is transforming online shopping experiences from overwhelming to personalized. 

Learn how AI shopping assistants can guide customers throughout their journey, anticipate their needs, and provide the kind of personalized guidance previously only available in brick-and-mortar stores. Mike reveals how companies are achieving 20% conversion rates with AI-powered shopping assistance. 

Topics discussed in this episode: 

• Why shoppers get overwhelmed. 
• What value-based commerce is. 
• How AI bridges conversion tools and chatbots. 
• Why traditional chatbots failed. 
• How AI personalizes shopping. 
• What makes e-commerce data AI-ready. 
• How brands see 20% conversion with AI. 
• What future shopping looks like. 
• How Shopify merchants implement AI. 
• Why focus shifted to sales growth. 

Links & Resources 

Website: https://www.iadvize.com/en/
Shopify App Store: https://apps.shopify.com/iadvize-ai-copilot
LinkedIn: https://www.linkedin.com/in/mikejdelacruz/
Instagram: https://www.instagram.com/iadvize/ 

Get access to more free resources by visiting the show notes at
https://tinyurl.com/bd57p67p 

MORE RESOURCES

Store Optimization Beginners Guide: Instant PDF Download! It's FREE. 👉 https://ecommercecoffeebreak.com/essential-conversion-optimization-guide/

Top Tools, Apps, and Services used by leading Ecommerce Brands: https://ecommercecoffeebreak.com/quiz-results/

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Transcript

[00:00:00] Hey there. Welcome to the e-Commerce Coffee Break. I'm your host Claus Lauer, and you're listening to the podcast that helps you become a smarter online seller. In today's episode, we share how to fix your e-commerce conversion rates and explore the AI powered path to value-based commerce. Joining me shows Mike de La Cruz, he's [00:00:20] the president of iAdvize.

So let's dive right into it. Hello and welcome to another episode of the E-Commerce Coffee Break podcast. Today we wanna talk about two of my favorite topics. We wanna talk about conversion rate optimization. We want to talk about ai. Now, big problem for all shoppers out there or no conversions is conversion rates.

And we want to find out [00:00:40] what value-based commerce is and how AI can help you with this. Now that's a very broad topic, and as always, I have a. Expert with me and I'm joined by Mike De La Cruz Mike. He is the president of iAdvize, an innovative AI company, transforming the e-commerce landscape, and iAdvize Mike drives product marketing and strategy, helping brands unlock smarter [00:01:00] and more personalized customer interactions to maximize conversions in sales.

He brings a deep expertise in scaling customer experience technologies and growth to the e-commerce world. So that's welcome onto the show. Hi Mike, how are you today? Hello Claus. Thanks for having me on the show. Let's dive right into it. Most online stores struggle with low conversion rates. Um, [00:01:20] plenty of reasons there, but what do you think is the biggest problem for shoppers?

Well, I think, you know, what's happened in e-commerce is, uh, the shopper overload. You know, we've put more and more information. In a journey that we'd love to orchestrate for every shopper and in the drive to give as much [00:01:40] information as the shopper needs to make decisions. We've made it very complex.

It's overwhelming, there's a lot of choices, and it, it becomes actually unwieldy and not as convenient anymore to get what you want to be able to make a safe purchase. No, totally agree. And I think it's the numbers, and correct me if I'm wrong, it's like 80% of [00:02:00] shoppers drop off somewhere in the customer journey and AI comes to help there.

Tell me a little bit about your approach. How do you see the customer journey? Yeah, so what, what we've looked at in terms of the customer journey is that. For a long time, us included, we were part of a drive to make the orchestrated customer [00:02:20] journey a lot more efficient. Uh, what I mean by orchestration is we, we try in, in, uh, e-commerce to do this great thing where we, uh, try to attract somebody to website.

Get them to our homepage, guide them to a category page, or give them a search bar and keep moving them down the funnel in a very orderly, [00:02:40] uh, step by step way. The problem is the consumer does not shop like that. Uh, the the consumer. Shops in all sorts of different angles. They are in discovery and considerations and post-sale support all at the same time, all in the same conversation, all in the same session.[00:03:00] 

And so really it's, uh, what's happening here is an opportunity to rethink that orchestrated step-by-step e-commerce journey. Say, well, what, what does a real curated one look like? What does it look like to actually take away all the complexity and make it easier for somebody to get the guidance that they need [00:03:20] to shop with confidence?

Mm-hmm. No, I like the approach, but obviously, as I said, everyone is coming from a d different angle. Everyone has a different approach to shopping and there might be on different stages on their purchase decision, what they wanna buy, and, and obviously depending on what, what kind of industry or what your product have your shopping.

Journey might look very, very different. [00:03:40] Now, let's talk a little about AI and specifically about chat. So years ago there were chatbots where that has completely cha changed. Um, tell me a little bit on how AI can help with shopping. Yeah, so I mean, really, uh, there's AI in customer. Um, uh, conversion, conversion rate tools and [00:04:00] CRO tools.

So there's AI and conversion rate tools and there's AI in chatbots, and the two have been kind of siloed pieces of the customer experience. I think what you found with CRO tools is they touched a lot of shoppers, uh, but they had very low success rates. You were looking for minor [00:04:20] 1%, half a percent improvements in conversion or click through from one stage to the next.

Uh, what happened with chatbots is it had high interaction, some good, uh, automation. Uh. But no one really clicked on it. So that's the thing. No one clicked on it to get help to buy something. Um, I think what's happening now with [00:04:40] AI is an opportunity to rethink that and to merge these two ideas and to say what do people really need and when do they need it to shop for something?

Of course, we have really evolved and improved how we handle support, so that continues to imp improve in incremental ways with ai. How do we actually [00:05:00] help with shopping? How do we provide guidance? How do we anticipate what the shoppers actually need at different parts of their process, and how can we advise them to take away all of this noise and all of this choice and help them make a confident purchase?

I like that you mentioned [00:05:20] there were chat bots before, but they were separated from each other. I've never looked at it this way, but it makes totally sense and I think a lot of chat bots back in the time, they were like very robotic, very unpersonal. And obviously with ai this has changed. Talk me through a, a perfect experience of a shopper coming to a store.

What's usually happening when AI bots [00:05:40] help them? Yeah, I, I think the main thing is in the past, um, the AI chatbot would be, they're available all the time. Ready for your questions. Uh, let me know when I can help you. Uh, can I help you? Can I help you? I'm here. Let me know when I can help you. Um, the thing is, [00:06:00] nobody clicked on there because actually most people.

Don't know what help they need. They're browsing, they're searching. Um, they may want actually the experience that you get in a store when a sales associate helps you proactively, um, they, they help you think through what you're really trying to get right. [00:06:20] And, uh, what's happening now, the perfect experience is to come in where.

Uh, wherever you are at. So maybe you came in through an ad, you bypass the search bar, you bypass the homepage, you bypass the category pages, you land just on a product page, right? And the ideal scenario there is you [00:06:40] have an AI that's gonna anticipate what you might be wanting to know and is ready to advise you to make a selection or choose another product at that point.

That's the, that's the ideal experience is actually that personalization we've been searching for, for a long time. Um, how do you make it so that it's what's [00:07:00] needed at that time By that shopper? Mm-hmm. Now a personal assistant, and I think brick and mortar stores is a good example for that. Um, it takes you from wherever you are in the store and takes you to the right product, to the right area in the store.

How does that look on a online store? Yeah, I, I think in an online store [00:07:20] you do stick with the, the pages that we know really well, so people understand this orchestrated experience. And on a category page where you're browsing, um, you have a different need than when you're actually looking on a product detail page.

I. Where you're clicking through and trying to find specific information or specifications about a [00:07:40] product. So just those two examples, they have different needs and the AI needs to present itself as something that's ready to help you with those needs. In one case, on a category page, helping you filter through all that.

Find what you need on a product page, kind of getting your questions or concerns answered [00:08:00] and getting that proof that you need that, that in the data that you need to feel confident to move forward. Mm-hmm. Let's talk about data. A lot of our listeners are on Shopify and some of them have relatively big stores with a lot of skews.

How does AI learn about all the products, about product variations and provide the right information at the right moment? Yeah, well, [00:08:20] you know what? E-commerce is really set up. To take advantage of AI because of all the work that your listeners have been doing to, uh, put their catalogs online, uh, leverage, uh, great platforms like Shopify, uh, improve all of that.

Um, that is an essential part. [00:08:40] Of what AI needs to become product experts and be able to help the shoppers. That's a, that's a key part of it. Not the only part, uh, but taking advantage of the fact that e-commerce data is out there. The whole point is e-commerce stores are trying to provide this data out to the consumer.

Um, being able to take advantage of that and really giving it a [00:09:00] different user experience so that that shopping is much more curated, much more one-to-one, and is less overwhelming than the current approach. Now I advise you have big brands under your umbrella working with you for a long time. Can you give me some examples of brands that you don't need to name them, that work with you, and [00:09:20] what kind of results they saw after they started using I Advice?

We're a specialist in e-commerce. So, uh, all these brands are in different industries. We work with different industries in e-commerce, uh, but we do work from mid-size up to large brands. So we would have a mid-size brand. Uh, we've got a great glasses [00:09:40] manufacturer, online glasses, for example. And what they wanted to do was help get over.

The, the difficulties of ordering glasses online, there's something about being in store, being able to ask a store as about prescriptions, feel confident that you're making the right order that they needed online, and the idea [00:10:00] was to provide, I. Uh, 24 7 support with AI in a lot of cases, help them with their prescriptions, help them understand it, uh, take away any concerns that they have, that they're putting in the right numbers to make a confident order.

And so, uh, this brand, for example, has 20% conversion rates for shoppers that are shopping with ai. And so our goal is to keep [00:10:20] upping the engagement rates so that, uh, that 20% goes sitewide. Right, and that's a smaller company, but we also have, and that's very focused on the category. We also have a seed discount in France, for example, uh, the largest marketplace in France, a second to Amazon, and they've got 80 million products.

So there's [00:10:40] a different challenge where how do you actually provide guidance on all of these products that are on your site? How do you help people, uh, go through all the overwhelm they could potentially have, uh, when they're shopping and make it easier for them? And they used to have human advisors, uh, to help do [00:11:00] this only.

And by leveraging generative AI and and our AI co-pilot, they found that the conversion rates for AI are the same as human advisors. So in that, being able to deal with the complexity of the site. You mentioned your product is called Copilot, and I think that's a good name for it. So how does it guide you through, I'll [00:11:20] put it the other way around.

Do you think that a normal way to shop will be through AI and not the traditional online shopping that we're doing for, I don't know, 20 years? I. I think there's gonna be two types of shopping. People are gonna shop in two ways. One, it's gonna be the traditional experience of [00:11:40] navigating and browsing and making a purchase online on a e-commerce website.

I. That's gonna be powered by ai. It's gonna be much more personalized and it's gonna be much more advisory, if you will, down the process rather than list giving you big, big lists of things to scroll through. Um, that's gonna get improved. [00:12:00] I think there's gonna be another experience which is gonna be side by side with that experience, which is, uh, walk me through this as if you, a store associate took over.

In a physical store and said, Claus, let me, let me, uh, let me help you. I see you're, you're searching through different things. Let me help you. What are you trying to look [00:12:20] for? Are you interested in different sizes? Are you shopping for yourself? Uh, and having that. So I, I actually see those two parallel being available, and I actually see that, um, mobile.

In the mobile world will be much more curated than it is today because it's very, very hard to d to navigate all of this [00:12:40] information, especially for somebody that doesn't know what they want yet or is searching for things in that product discovery phase. It's very hard to navigate on mobile, so I think more of that is gonna go towards a curated experience.

Now let's talk about, about the technical side of it. Online merchants. Shopify merchants are always interested in new [00:13:00] technologies, but they wanna know how complex it is to integrate this in their business. How does it work from your side? I think the main thing is if you're a Shopify customer, you're already ahead of the game because you have, um, a lot of your data, um, and your catalog in a good form.

Mm-hmm. [00:13:20] There are different, uh, levels of it. Of course, you're, you're working on improving it all the time, but you've got the baseline to be able to start an AI project and begin to deliver, uh, and see results and achieve results. I think the main thing actually is thinking about this as an iterative process where [00:13:40] you can get going.

You're gonna see great results. The iteration is gonna come from you really thinking about AI as a transformative tool to help you get closer to what your shoppers actually really need and being able to satisfy it. And in that case, it's really about. Not about [00:14:00] whether it's right or getting started.

It's thinking about, well, what's really needed? What, what information should I provide? What instructions should I provide? The what guidance as if I had a store associate, then I could deploy to every interaction that's happening online. I. You know, what, what kind of guidance can I provide? What information can I provide?

How [00:14:20] can I help it be, be much more effective? And that's an ongoing process that really, uh, it's not crazy amounts of time compared to training a store associate, for example. Uh, but you do have to think about that and not think it's completely hands off. Mm-hmm. That answers basically my next question.

That would've been, um, is there any homework to do by Ion [00:14:40] before they get started? Walk me through a typical onboarding process. How does it work? What steps are involved? How long does it take? Yeah. Onboarding process, really, you know, three steps you would connect with your Shopify catalog. You would take then, uh, all the other information.

Typically these would be buying guides. Uh, very [00:15:00] typical knowledge articles, very typical that you would provide, you know, your FAQ documents, uh, you would provide to, uh, the AI shopping assistant. And the third is you would, you would test it. So this would be the testing process. Uh, people might go from a day or two plus of testing, but really [00:15:20] it depends.

We, we recommend to people to test a lot, really get comfortable with how it works, but then deploy it iteratively, you know, to a set of products that you might have, a category that you might have on your website. Get really comfortable with it and grow from there. Now we're talking about Shopify and you have a [00:15:40] Shopify app.

Um, are there other integrations, APIs that you're facilitating to get the most out of the data you have? Yeah. Yeah. So what we believe is sales, CRO and CX converge. Mm-hmm. Right? And so we really wanna be able to very easily [00:16:00] handle pre and post-sales. Questions we need to be able to provide back, uh, information to maybe, uh, agents, to customer service and customer support.

So we make it very, very easy to push your information, push tickets, uh, escalate to your help desk, [00:16:20] right? And so, uh, any, any help desk, push it out to that and make sure that there's continuation with that customer. Now it turns out. Most people that are looking for shopping guidance are not going to the help center, you know, or they're not going to support.

So they really are abandoning, they're trying, they're searching, and then [00:16:40] they're abandoning. So these are net new conversations, and really most of this is, uh, kind of an unserved group of shoppers that AI will now be reaching out to. I like the approach of bringing everything together because in the past, and I had my own shop for a while, and the, the same problem, people are searching on different sites, on different parts of [00:17:00] your website to get to the contact or point of contact, for instance, for support or product, um, details.

And then they just had to scramble through your website to find the right thing. And with AI, you can bring all of this together. Now, you mentioned a couple of, um, clients you work for, but who's your perfect customer? You know, the, the perfect [00:17:20] customer for us is, um, one, somebody that, uh, really is committed to growing online.

What we found was a big change for us. We did many AI chatbot projects before generative ai. Um, most of those projects were about efficiency as the main [00:17:40] driver we surveyed. We, we've, we've looked at 150 projects with ai right now, 75% of those projects have increasing sales as the main driver. Right. And so by thinking about increasing sales as the main driver, it makes an ideal customer, those that are thinking [00:18:00] that way because it's gonna force you and us to rethink the user experience, the shopping experience, and not just do another automation again, of your support issues.

You know, of course we'll handle support issues, but let's really rethink this and why, uh, maybe if you already had an AI chatbot [00:18:20] in the past. Why it really was only serving maybe half a percent of your visitors. Um. How is it engaging enough? How is it helpful enough at different parts of the shopping experience to drive those high engagement rates and the high conversion rates?

Mm-hmm. I think it's the right time in in [00:18:40] e-commerce history, if I can say so that AI now really kickstarts on the process because now it's like two years into chat, GPT and all the others that people are getting used to use. Chat, GBT or any kind of system out there in their daily life for other tasks.

And now bringing this to e-commerce is, is just a, uh, a [00:19:00] natural continuation basically, of what they do anyway. Now, um, tell me a little bit about, we, we talked about onboarding. Tell me bit about the pricing. How is your pricing structure working? Yeah, so, so our pricing is gonna be based on. Use and those use are interactions with the ai.

Uh, so we have different packages, uh, for different [00:19:20] sizes based on that. Uh, the most important thing about pricing is we wanna work with everybody to define kind of an iterative way to go about doing this. So the big thing about pricing is we're designed, um, to price by package of conversations, uh, by volume.

We don't want to push anybody, nor do [00:19:40] we think it's a good idea to actually think about your entire site at full volume of three years from now. We think it's a process and we wanna, we, we've designed everything so that we can work with everybody from where there's, there are and give them a good starting point.

Mm-hmm. Now, I know that you are, um, based also in [00:20:00] France, not only in the us. Um, how about multi-language multicurrency? Is that something that you support in your system? Yeah. The, the great news is with the advancements in Generat AI in large language models, we're able to take advantage. A lot of those capabilities to support multi-language.

Uh, we have, uh, multiple multi-language, uh, [00:20:20] multicurrency deployments in Europe. So we do, we do support that. Okay, cool. Mike, very interesting topic. I would love to talk much, much longer about that, but before our coffee break comes to end today, is there anything you wanna share with our listeners that we haven't covered yet?

I, I think the main thing is that, you know, AI. Generative AI specifically, we've gotten used to [00:20:40] it. The novelty's wor off, and the great thing about that is now we can focus on how can this actually transform our business? Mm-hmm. Can we take it from the old use case, which is maybe taking our support automation program and putting it on generative AI and building from there and saying, wait a minute, let's attack the [00:21:00] fact that only 3% of my visitors are converting online.

What's causing that? How can we rethink that? How can we really think about the holistic user experience and what users and shoppers are really trying to do? And actually take a, an opportunity to step back [00:21:20] from the siloed piece by piece, uh, projects that we have all along this buyer journey. Where we actually fragment the customer experience.

Uh, and now we have a chance to rethink it, you know, with this approach. So, um, rethink that with us. We'd love to hear from you and, uh, talk to you about [00:21:40] what we're seeing. On that note, where can people go and find out more about your guys? Uh, i advise.com. So go to i advise.com, find out about us. Uh, we we're also in the Shopify marketplace.

You could go from there. Uh, find out about us and would love to work with you and, and share with you our experiences. Excellent. I will put the links in [00:22:00] the show notes as always. Then you just one click away. Mike, thanks so much for the time today to talk about ai, about conversion rate optimization and where the journey goes to.

I think it's exciting times. It's a time where a lot of things will change in e-commerce, and I hope a lot of people will reach out to you. Thanks so much. Yeah, thank you so much.