Why Your Best Content Is Invisible in AI Search (And How to Fix It)

Steve Hutt:
Welcome back to eCommerce Fastlane. I’m your host, Steve Hutt.

Steve Hutt:
Now today I’m chatting with Ivan, who is— I’m going to call him Director of Product, but that’s mostly because he’s currently the only person on the product team for Searchable.com. What’s nice about Ivan is he joined the company early on. He’s one of their first major hires on the product side.

What’s interesting about Searchable.com—and I’m actually a customer, I have it live on my screen right now—is that we’re going to talk a lot about what Searchable does. It’s very unique in the AI realm. I don’t want to give away too much about what the product does and the problems it solves, but it’s very interesting as it relates to AI, chatbots, and AI overviews. It’s already on a lot of people’s radar. People are used to the concept of “Where am I in organic search?” or “What is my share of search?” on the regular blue links.

But people are now trying to figure out, with Shopify’s alignment with ChatGPT, how it all fits together. You can now combine from within the app, and there are all these new alignments with Etsy and Amazon as well. There’s a lot happening around customers doing their research inside chatbots now—ChatGPT, Perplexity, Gemini. So it’s very timely. That’s why Ivan’s on the show today.

So, welcome to eCommerce Fastlane.

Ivan Slobodin:
Hi, great to be here.

Steve Hutt:
My pleasure.

Let’s talk a bit about the platform itself, because I think what’s interesting about Searchable—again, I’m a customer, and I think the platform is absolutely fantastic. I don’t want to rave too much about it yet because I want to get into some of the specifics of the tool. But let’s start with the backstory of the company.

The founding team, including yourself, has a lot of roots in content production, SEO, and now AEO.

Ivan Slobodin:
Chris, our co‑founder, is a serial UK entrepreneur. That’s actually how I first knew him—through his LinkedIn and social content about business. He’s founded four or five businesses himself, so he really knows what he’s talking about. He also used to run a luxury agency, so he’s definitely “done the miles,” I would say.

Our entire team, in one form or another, has done the work in SEO. In my case, I used to be a marketing consultant heavily focused on SEO, ecommerce, and so on. Our other co‑founders, Ari and Sam, came from an AEO background. As soon as ChatGPT started to emerge, they immediately began looking at it and asking, “Okay, what can we do here? How can brands rank?”

So the entire team is experienced from the get‑go. We all know what we’re doing, and we make sure that knowledge gets into the hands of users.

Steve Hutt:
I see. This product is clearly built for me as a media company, but I think there are a lot of people listening who are Shopify‑powered businesses, producing content, trying to build their own competitive moat. They’re educating customers, getting them into some sort of marketing funnel, and building trust and authority through content.

So talk about who you believe the product is actually built for. Is there a sweet spot customer? A specific workflow? Or is it more of a trend now where we simply have to be in AI search? Because right now, I still think organic placement is the highest‑ROI channel—getting into the free listings in Google. But we know people are moving over to chatbots and/or seeing AI overviews.

So overall, what types of brands fit nicely with Searchable.com?

Ivan Slobodin:
In danger of sounding cliché, everyone can use it, because we have a very wide range of customers. We see everything from media companies like yourself all the way up to very large enterprise brands that operate in 40 countries with 60 product categories. Their footprint is very large, but there’s definitely a sweet spot in the middle as well.

Searchable’s core value is boosting your existing team so they become, effectively, a 10x ecommerce manager or a 10x content creator. We not only tell you where you rank, how you rank, and where the problems are, but we give you the skill set and an AI sidekick—what we call our AI agent—to help you fix those issues.

So if you’re a very large company with millions of problems to solve, it’s useful. If you’re a very small ecommerce team with two or three people, it’s also useful because we’re trying to boost everyone. The AI space is so new that everyone is still figuring it out.

That’s why I would say it’s useful for almost every industry. In ecommerce especially, people are starting to shop via ChatGPT—or at least, they’re starting by asking questions there.

Steve Hutt:
Yes. Research, definitely.

Ivan Slobodin:
Exactly. I’ve quizzed it a lot on headphones recently because I bought a new pair. From Amazon’s perspective, I was the perfect customer. I typed in one search and bought those headphones. That’s an ideal customer.

What they don’t see is that it took me a couple of hours of quizzing ChatGPT—rather than Google—before I got there. This is where things are really changing.

Steve Hutt:
It’s interesting. What do you think brands are currently doing without your tool? Because I think there’s a bit of “duct tape” going on. Progressive brands are trying some things. Some are doing nothing and just hoping for the best or simply not sure what to do.

So what do you see from your side?

Ivan Slobodin:
What we see in a lot of cases is a typical response: “I can go do it myself. I can go to ChatGPT and ask for the best headphones, best over‑ear headphones, best running sneakers.” Some brands see themselves in the results. Some brands see Nike, Adidas, and so on.

Many then try to skew the AI in their favor by saying, “Show me only British brands,” or “Only Japanese headphones,” trying to narrow things that way. Or they just give up and say, “I can’t really fight with Nike or Adidas,” which is true in SEO. It’s such an established industry that if you have massive competitors, it can be really hard to rank.

But because AI search is so new, there’s a lot of white space. I’d say for the next 6–12 months, there is a huge opportunity to rank alongside Nikes and Sonys of the world if you really optimize.

When brands do this manually, they might run 10 or 20 prompts on ChatGPT and then stop. We run hundreds of prompts for our customers each day, across up to nine different platforms. Imagine doing that manually—900 prompts a day. That’s a full‑time job. That’s when people say, “AI is making us less productive.” If you use it that way, you definitely become less productive.

What we’re doing is automating that process. On top of that, as you mentioned, there’s the “Now what?” moment. You’ve seen the results—what do you do about them? That’s often the aha moment in our demos. We collect all those responses and turn them into very insightful information in different ways.

AI is very different from basic search and SEO. The next step is, “Here’s what you do about it,” and it’s all in one platform. That’s where it really helps.

Most people come to us after trying things manually—searching themselves or building a few scripts—and quickly realize they can’t keep going like that. It’s not scalable.

In some cases, they come from established SEO platforms. Almost every SEO tool now has an “AI visibility” add‑on. But those are SEO tools with an AI feature tacked on. That’s very different from a platform that’s been built from the ground up for AI search.

Steve Hutt:
It’s interesting. I have it open right now, and what I find great is when you add a URL—so I put eCommerce Fastlane in—and ran a site audit. I just did maybe the first 100 pages or so of my site. I think I’m allowed up to 1,000, but I started with the top 100 pages. I grabbed the sitemap, it did a crawl, and it came back with a lot of opportunities.

Under Site Health, it immediately gave me some issues. In my case, it found 1,727 issues. Even though I have massive traffic—more than 300,000 visits a month—I have pretty decent AI visibility from domain age, authority, and lots of content with a consistent publishing schedule. But it’s interesting that there are still lots of high‑priority and critical issues I didn’t realize needed to be fixed.

They’re now queued in a tasks folder. I check them off, and my VA is taking care of them.

Walk us through what happens when someone gets the tool. They run a quick audit of all pages—or at least the high‑value pages. It comes back with issues. Is that the typical workflow—start with on‑page challenges, then move to where you fit in AI search across different chatbots? Is that usually the next step? And what would be the third step after you identify where you fit in the market?

Ivan Slobodin:
Steve, you’re quickly becoming a superuser, I see. You’ve already covered a feature that’s been out for just over two weeks. We’ve just announced it, and we’re very excited about it. It’s getting great uptake for exactly the reasons you mentioned.

Yes, we run a site audit. If anyone listening has done a Lighthouse audit or a technical SEO audit, some elements will feel familiar. But this is where the debate—“Is AEO just really good SEO?”—starts to diverge.

One of my favorite examples is FAQs. If you were doing SEO up until maybe a year ago, FAQs were probably very low on your to‑do list. They had little impact on SEO. They were just some additional content. They’re great for usability, UX, and conversion rate optimization, but from an SEO perspective, they were pretty “meh.”

Suddenly, you bring LLMs into the picture, and from AI’s perspective, it has everything on a silver platter: the question and the answer. Of course it wants to look at that. Then it looks at another page that doesn’t have FAQs and becomes less confident about that page compared to the one that gives it exactly what it needs.

So now there’s an entire category of new issues that even the best‑optimized websites are seeing, because they were optimizing for SEO, not for AI. You start to really see the differences. That’s probably what you’re seeing in your issues. It’s not that you ignored these things before—it’s that they have a new level of importance now.

Steve Hutt:
Yeah. Under “Critical” for me, there were a few different content things—H tags, on‑page issues that need resolving.

What’s interesting about FAQs—and this is my follow‑up question, maybe the billion‑dollar question—is how these LLMs decide whether to use a page’s FAQs. If one page has FAQs with clear questions and answers, that’s helpful from a learning perspective. But how does the model decide to use that FAQ, or not, and move on?

It feels like there are other trust signals and referral signals at play. It’s easy to say, “Everyone go write a bunch of FAQs, ten per page, and hope LLMs pick them up.” But we both know there are probably other pieces of the puzzle required before you’re even in the pool of potential options for these LLMs.

Does that question make sense?

Ivan Slobodin:
I’d say it qualifies as a billion‑dollar question.

What we’ve noticed is that, yes, we’re talking about AI accessibility, but there’s also an enormous amount of new content popping up because AI makes it easy to generate. People call it “AI slop.” But even before that, even if your content is perfectly good, the key is that if everyone creates content that’s roughly the same and talks about the same things—not just FAQs, but the whole page—then AI finds nothing new in your answer.

It will lump you in with everyone else who may not be terribly written but isn’t adding anything new. It probably already has that information from other sources.

So our suggestion is: first, make sure you bring something unique or at least a complete answer. A page that’s just FAQs is probably as bad as a page with no FAQs—what’s the point of the page then?

Another thing many people miss is schema markup. It wasn’t a big deal in SEO for a long time because Google solved a lot of it automatically. People got lazy because Google handled it for them.

But an LLM needs to see what a page is about in a simple way before it starts scanning. It needs a quick snapshot. If you’re writing a blog post, FAQs are probably at the bottom. If you don’t have a TL;DR—which our article generator can add—AI may never get that far.

So you want to make it as easy as possible for AI to get a lightning‑fast understanding of what the page is about, and then you build out the rest of the content.

Steve Hutt:
Okay, that part I understand.

So the audit is done. Then I see a section about visibility, where a brand sits from a visibility perspective. It found a bunch of competitors and let me accept or decline those, or add new ones if Searchable didn’t identify all of them correctly. It scans my site and suggests notable competitors in AI search. I agreed with most of them. And now it shows I’m at 23% visibility.

Shopify is at the top, and then there are lots of other competitors.

What do you think the next steps are once you understand where you sit after an audit? I know what I do currently, but I’m curious what you recommend as the next steps once you know your current position in AI search.

Ivan Slobodin:
The visibility dashboard is a high‑level snapshot: here’s where you are, here’s where your competitors are. Our additional analytics features let you dig deeper.

I mentioned “sources” before—figuring out which links or websites AI cites and uses for information. There’s an entire section dedicated to that. Because we aggregate thousands and thousands of responses, we get a solid picture of who’s referenced consistently versus who gets occasional, probability‑based mentions.

I won’t surprise anyone by saying Reddit is very high and YouTube is climbing. At the domain level, these sites always win. But we let you drill down to the URL level, and suddenly the picture changes. Yes, Reddit has hundreds of posts that each get cited a bit, but there are always one to five stellar pages—early, well‑maintained, with great technical performance.

Those pages can become your North Star for how to build a proper page or write a strong piece of content.

We provide multiple angles: what AI is talking about on the platform versus where it sends users off‑platform. For someone used to SEO data, that’s a perfect starting place to dig in.

We also go further. If you want someone to do the number crunching for you, that’s where the agent comes in. Our agent is trained on the platform; it has access to all the data, knowledge, and best practices. You can ask, “Which of my competitors are getting cited for good Shopify content?” It will give you an answer, and then you can have a conversation:

“What do I do to make this better?”
“How do I win?”
“Which content should I write?”

You effectively have a partner you can bounce ideas off, which I think is one of the best parts of the platform. It still surprises me when I demo in a category I haven’t seen before. I’ll throw it a question, and it comes back with a fully thought‑through answer. It feels a bit like magic, even though we know it’s just technology.

Steve Hutt:
Yeah, it’s amazing. I use the agent quite a bit. One use case is content gap analysis. It’s currently set up against my site—this could just as easily be a Shopify brand. It finds notable competitors in the same category—for example, if you’re in footwear, other footwear brands customers may consider during discovery.

It then analyzes all the gaps between your site and your competitors’ sites and starts giving you recommendations for missing content.

Talk about what’s going on there, because it’s pretty amazing.

Ivan Slobodin:
This is where scale really matters. A hundred articles can each move the needle a bit, but when we’re getting so many data points and such rich answers from AI, we’re not just looking at titles and snippets like in blue‑link SEO.

We’re working with large, contextually rich responses. We parse all of them to understand what they’re about, the context of why something was recommended, even sentiment. If AI hints that something is “a bit iffy,” we can record that and highlight where you’re falling behind.

So when you run something like a content gap analysis, we’re feeding all of this into your search. We have an ecommerce client that primarily sells socks. They actually found new product ideas because they saw competitors adding certain occasions—Easter, Mother’s Day, and so on—that they weren’t covering.

So it didn’t just stop at content strategy—it affected their product strategy. They realized AI was recommending socks for occasions they hadn’t considered, which is fantastic. You only get that if you cast a very wide net and have a way to surface those nuggets—AI helping AI, in a sense, through our agent.

Steve Hutt:
That’s really cool. I’m looking at one of my examples, and it literally says, “Here’s what your competitors are covering and you’re missing.” That’s exactly what you’re talking about—the discovery aspect.

It shows, “Here’s where I’m at,” and highlights the gaps in my content strategy. Everyone has gaps, in every industry. This gives me a concrete view of what my next steps should be.

Then I can create a task, which feeds into the writing process.

Let’s talk about that. Once you find a gap, the platform is so smart—I’ve run it multiple times now. It understands, “Here are my competitors, here are my gaps—go write a piece of content.”

It knows which piece of content was created with Searchable’s assistance. Once I publish it and give it the live URL, the platform uses it as a new reference point: “You used to have this gap, you wrote content based on our recommendation, and now we know the URL and we’re tracking it too.”

It makes me wonder, why wasn’t this always available? But I guess it’s only possible now at scale, and that’s how the platform works.

I probably sound like a fanboy, but it’s such a hard problem to solve.

It even goes further. We talked offline before recording about stale, dated, and decaying content. Let’s go there.

We know what we need to write from gap analysis, and the content it helps produce is fantastic—structured data, schema, FAQs, introduction, everything. I’ve written a lot of content with it.

But what about content that’s not performing well in organic search and clearly not doing well in AI search either? Talk about how Searchable helps with those pillar pieces that used to rank but decay over time.

Ivan Slobodin:
First, you can optimize existing content. That wasn’t available at the very beginning, but it quickly became one of the most requested features. Customer feedback is our lifeblood. I’m in all our support channels, talking to customers constantly to get those insights.

One of the earliest reviews we got was, “I have this amazing Searchable‑generated article, and now my older articles look rubbish next to it.” A bit of content jealousy.

Now you can upload an existing article, we’ll read it, run research again, and optimize it to that same standard. That’s one of the easiest ways to handle decaying content.

Then there’s the agent. If you see an issue or a gap, you can just give the agent a URL and ask, “What do I do here? Why is this stale? Why is it losing traffic?” Because it’s a chat interface, even if the agent doesn’t automatically have every piece of context you do, it can incorporate whatever you provide and work with that.

That’s also why we have Google Search Console and Analytics integrations. You can track that article over time. You can ask the agent, “How’s that new article doing?” and it will go back to Google Analytics, pull that URL, and say, “You’re now getting ChatGPT traffic for it,” and so on.

It’s all out of the box. We try to keep technical barriers as low as possible.

We have users who don’t believe we’re “just” integrating with GA. They log in and see all this AI attribution data and ask, “Where is this coming from?” But it’s simply that we present the data in a native way. Because we know what we’re looking for, we can surface it clearly.

Steve Hutt:
Yeah, it’s very rare to see a solution with both GA and Search Console data together, actually corroborating a story and stitching the pieces. I think that’s incredibly important.

Now let’s talk about prompts, because a lot of people don’t know what to prompt. It’s similar to the old SEO days: you have your head terms and your long tail. People are changing how they query, both in Google and in large language models.

Even on your phone—I use the Flow app, and I’m often speaking into my phone because I can talk 200 words a minute versus typing.

From a technology mindset, how do you choose which prompts to use? That’s part of Searchable’s ongoing work in the background—figuring out which prompts your target audience is actually using in LLMs.

How do you come up with that? I know you can manually add your own prompts because you know your industry best, but you also surface some really unique ones where I think, “Wow, people would actually ask that.”

They might say, “I’m looking for someone to help my site with CRO,” for example. Everyone uses different language. There’s not an infinite number of queries, but there is definitely a cutoff in terms of how many you’re going to ping these LLMs with.

So how do you choose which prompts you actually want? Is there a mindset or process that makes the most sense? I’m asking for myself, but I think a lot of listeners are wondering the same.

Ivan Slobodin:
Yeah, of course. I think it’s worth noting that, for the first time in a long time—probably since social media—we’re working without official data.

There’s no public prompt search volume. ChatGPT doesn’t tell you, “This prompt is searched X times per month.” Marketers hate flying blind more than almost anything. When Google says they’re deprecating cookies, everyone panics because no one wants to lose their visibility into behavior.

So this is a real challenge, and very openly, nobody has fully solved it yet. Anyone who claims they have—I’d love to talk to them, because they shouldn’t be misleading people.

What we do have is the ability to talk to LLMs themselves to get ideas. Our approach is twofold.

First, we do research based on a seed topic. You can load something like “CRO optimization websites” or “CRO optimization consultants,” and we’ll go to multiple AI platforms and have a short “conversation” with them: “If you’re searching for this, what else would you search for?”

Because we’re already querying them, we want to collect that corpus of related queries from them.

Yes, it’s simulated, but we find small variations of the same prompt often result in roughly the same answers because context is not the same as keywords. With keywords, if you have three words and one changes, that’s a 30% difference.

With a 20‑word phrase that has rich context, if I’m looking for “high‑performance headphones,” I might phrase it differently each time, but the intent and context stay the same: I want premium, top‑of‑the‑line headphones. I’m clearly nerding out over them, which I’m not afraid to admit—I love my headphones.

That lets us simulate a lot of topics effectively.

On the other side, we triangulate search data, our internal benchmarks, and third‑party data to estimate likely volume and difficulty—how many competitors are in that space.

You end up with hundreds of prompt ideas from the research, and we also give you a sense of their relative popularity so you can make informed decisions. It’s not perfect, but it’s informative. It gives you enough information to form a solid opinion on what’s strategic and what’s not.

That’s how we do it.

Steve Hutt:
It’s interesting. While you were speaking, I ran a query with the agent. I gave it my seed keyword—my primary business keyword—and asked for prompt creation ideas I should store in Searchable.

It’s nice how it breaks them down into feature‑specific prompts, really high‑intent prompts with qualifiers like “online” or “website,” and then platform‑specific prompts, like “best platform for X” or “best marketplace for Y.”

Then there are niche category prompts around buyer behavior—keywords like “for sale,” “custom,” “creators,” and so on. Then it goes into activity and wellness angles, and AI‑search‑optimized question‑based prompts like “How much is…?” “Is it safe…?” “Can I…?”

The comparison prompts were great too—“this versus that,” “best app for X,” and so on.

You come up with a lot of great ideas. And I think you’re right—rather than obsessing over ultra long‑tail prompts, as long as you’re framing things around buyer behavior and common angles, you’re covering your bases from a starting point. Then you can slowly widen out as you see results.

And I’m sure the tool will give more insights as weeks and months go by with these prompts in play.

Ivan Slobodin:
Yeah, absolutely. My favorite part is that if you ask the agent to add them, they’ll just appear in your project.

Steve Hutt:
See? That’s amazing, right?

Ivan Slobodin:
Yeah. These efficiency gains add up. Some are big—you can save hours analyzing data—but even small things like not needing to copy‑paste prompts from elsewhere matter.

We have a lot of brands saying they’ve replaced “Claude plus an SEO tool” or “ChatGPT plus something else” because we combine everything. When it’s natively integrated, it’s much easier to get things fixed and actually benefit from the tool because the answer lives right beside the question.

Steve Hutt:
I know this is slightly off‑topic, but is there public information on the LLMs running behind Searchable? Is it a custom hybrid solution, or are you still using an API‑based enterprise connection to a larger model?

And related to that, is there a bring‑your‑own‑key option? Where someone on a plan could plug in their own key instead of being limited by usage caps tied to the subscription? Is there a BYO key option on the enterprise side?

Ivan Slobodin:
Great question.

On bring‑your‑own‑key, we don’t feel there’s a strong need because we provide access to the platform and manage the querying of Perplexity, ChatGPT, and others for you.

It’s worth noting that we don’t use API calls for 90‑plus percent of our prompts. It’s done via the UI, so you get very realistic results. If someone logs into ChatGPT and asks the same prompt, that’s effectively the same process and research ChatGPT would perform.

There’s research showing that API responses and front‑end responses may only have around 15% overlap. They’re very different. We aim to make our tracking as realistic as possible.

In terms of underlying technology, we use a combination of models and LLMs for different parts of the platform. We optimize model choice carefully. I’d say the agent is primarily powered by Anthropic because of its strength in code and reasoning.

But there are many additional layers on top. If someone says, “Why can’t I just use Claude and throw out your agent?”—the answer is context and rules. Those matter.

We’ve also launched an MCP. For anyone unfamiliar, MCP is essentially an API layer for LLMs. It lets you connect tools like Claude’s desktop app or Cursor to our data. We already have users creating some really sophisticated skills—cross‑referencing their analytics and marketing data with Searchable. It’s a joy to see.

Steve Hutt:
Oh man. Wow. It’s such a bleeding‑edge piece of software, and we’re still in the early days. For me, it’s already ready for prime time.

I’m a new user myself, but it’s interesting—maybe ten or so articles I’ve written that I know have gaps. I see those gaps in Ahrefs, I see them via SEO testing, and I see them decaying over time. Those tools are great at showing decaying content.

But the nice thing about Searchable is I can go in and edit an existing piece, or the agent might say, “Let this one lie. Add some FAQs, update it to 2026, do the best you can with minor edits—but we recommend writing a new article on the same topic with a new angle.”

That’s very interesting to me, and I’m really curious how that continues to play out.

Once you get your instance of Searchable running for your business, that’s your starting point in time. The platform knows where you fit today, which prompts you’re relevant for, and where you are in AI search. From there, every improvement is incremental—1% better every day or week. Those are huge compounding gains over time if you keep doing the work.

So what do you think are the next steps for people listening right now? Let’s say there’s a marketing team or a founder who wants to make sure they’re present in AI search for their Shopify business. People are concerned that only major players show up in AI search right now, even through the Shopify–ChatGPT connection.

Why do those big players show up, what are they doing right, and what next steps do you recommend for listeners? Is this truly valuable for everyone? Are all businesses applicable here? I know you have affordable plans, but I’m curious what you see as the best next step.

Ivan Slobodin:
Yeah, this reminds me of when Facebook ads were $2–$6 CPM, and you just needed to advertise—almost anything worked. You could run a blank image or plain text and still get cheap traffic.

We’re currently in a similar 6–12 month window. A lot of enterprises are coasting on strong SEO and authority, but many are not actively doing the AI work yet.

My advice for anyone starting with Searchable is to spend a couple of hours upfront. Set up your knowledge base so we understand your brand. Run your audits so you see everything you’ve done. Start writing or optimizing a few articles.

If you do that initial work and you know where you stand and where your gaps are, then put in a couple of hours a day or a week to chip away at it. About 30% of our users are in the platform daily or at least five times a week, so there’s clear incremental progress happening.

In a year, this will be a much more crowded space. The laggards will start catching up. Right now, good visibility for key prompts is very achievable for almost any business.

We have countless users competing with Salesforce in specific niches or with very large brands, simply by optimizing what they already have, keeping evergreen content truly evergreen—not moldy—and closing content gaps.

If you put in the work now, you’ll have a strong base going forward.

We haven’t even talked much about this, but we’re preparing for it: when ChatGPT ads roll out, there’s going to be a lot of uncertainty. Our advice is always that good organic presence sets you up for whatever comes next.

Once you have a machine that refreshes your content every three months instead of every three years, and once your team is used to these tools and workflows, catching up to that system will be much harder for others once it gets competitive.

Right now, you can see results relatively quickly—sometimes within a week. SEO can take 3–6 months, but in certain niches we see results within a week: upticks in visibility and traffic.

So yes, this window will close, but for now it’s a very interesting playing field because newcomers still have a similar chance to the big guys.

Steve Hutt:
Yeah, it’s amazing. You have a lot of case studies on searchable.com. I’ll make sure in the show notes we link to those, across whatever market you’re in—not just Shopify ecommerce. Those are covered, but there are many others as well. I’m looking at them right now.

We also talked offline before recording, and you mentioned sharing an offer for listeners who think this might be right for them or at least want to try the platform. What do you see as the next step for anyone listening or watching today?

Ivan Slobodin:
Yeah, of course. The easiest way is to connect with me on LinkedIn. I think I’m the only “Slobodin Ivan” on LinkedIn, or at least one of very few.

If you ping me a message saying you came from Steve’s podcast, let me know and we’ll get you an additional 50% off your first month. Combined with the trial, it’s basically like having a full month free.

We believe in our product that much. You can have that month because we know you’ll love it.

Steve Hutt:
Yeah, exactly. So there’s a 14‑day free trial out of the box. I’ll put your LinkedIn profile in the show notes.

Then, for the first 50 people or so who DM you directly, they can get half off. So you’re right—they’re essentially getting a month to really kick the tires and see what’s going on with the platform.

I’m a fanboy; I absolutely love the platform. I think you’re building something very impactful.

I want to thank you for coming on the show today. We’re still in the early days, but it’s so exciting. I know you’re iterating nonstop and listening to feedback. There’s even a public roadmap. There’s a lot going on that I think is fantastic, and I want to give you some public kudos.

You’re building a great product, and this is lovely. Thanks so much for recording today.

Ivan Slobodin:
Thank you very much for having me.

Steve Hutt:
All right.

Ivan Slobodin:
Have a good day.

Steve Hutt:
Have a good day.

Ivan Slobodin:
Thanks, brother. Bye.

Steve Hutt:
Well, that’s it for today’s episode. I’d like to thank you personally for being a loyal listener of eCommerce Fastlane.

It’s my hope that this podcast is giving you a ton of value through growth strategies, tactics, and exclusive insider tips on the best Shopify apps and marketing platforms—all with my goal of helping you build, manage, grow, and scale a successful, thriving company powered by Shopify.

Thanks for investing some time today and listening to the show. I’m so proud and excited that you have a growth mindset and are a constant learner. I truly appreciate you and your entrepreneurial journey.

Enjoy the rest of the week and keep thriving with Shopify.