Why You Will Regret Ignoring Agentic Commerce — Cyril Golub | What Agentic Commerce Means, How AI Agents Change Ecommerce, Why Dashboards Are Losing Value, How AI Optimizes Product Listings, Why Trust Drives AI Adoption, What Comes Next for AI (#503)

Please support the show if you liked today's episode:

• If you love the podcast, please get someone else to listen, too!
• If you enjoyed this episode of the Ecommerce Coffee Break podcast, please head over to Apple Podcasts, leave a rating, write a review, and subscribe.
• Share the podcast with your family, friends, and co-workers.
• Tag the podcast on Instagram @ecommercecoffeebreak and let me know what you like about it.
• If you like the content and would like to support the podcast, you can buy me a coffee here.
• Become a guest on the show or sponsor an episode.

00:00:00:15 - 00:00:25:06
Claus Lauter
Quick one before we dive in. This episode is brought to you by Xero. Running an e-commerce or DTC brand? You know the accounting grind, multiple sales channels, invoices, reconciling every transaction by hand. Xero brings it all in one clean dashboard. Track cash flow, send invoices, and see where your business stands anytime, anywhere. As of the time of recording: Get a special Xero offer - 90% off for six months using this link. Check it out at referrals.xero.com/ecb. Ts & Cs apply. This episode is sponsored by Bizrate Insights. Star ratings tell you how customers feel. Bizrate Insights reveals what’s driving those ratings, helping ecommerce brands create smoother shopping journeys, inspire confident purchases, and build lasting loyalty. Turn verified shopper feedback into clear priorities and better customer experiences. Learn more at bizrateinsights.com/coffee.

00:00:54:11 - 00:01:14:00
Claus Lauter
Hello! Welcome to another episode of the E-commerce Coffee Break podcast. AI is changing ecommerce fast, but we may be looking at the wrong end of the change. The next big shift may not be how sellers use AI, it may be how customers use AI to shop. Imagine AI agents searching for products, comparing prices, reading reviews, and even buy for us.

00:01:14:00 - 00:01:34:17
Claus Lauter
So the question is what does that mean for online sellers? Will customers still search Amazon on Google the way they do today? And what will it take to win the sale? When an AI agent is making the choice to break this down, I'm joined by Cyril Golub. He is the founder and CEO of Jinnify.ai an AI commerce platform built for Amazon sellers and agencies.

00:01:34:18 - 00:01:40:21
Claus Lauter
He also co-founded Aheadworks and e-commerce software company he led for 16 years. So great to have you on the show.

00:01:41:00 - 00:01:53:06
Cyril Golub
Hi, Claus. My pleasure to be with you today, and thank you for the invitation to begin. I must say that actually, my career in the commerce software is for more than two decades already.

00:01:53:07 - 00:02:09:08
Claus Lauter
That's in human years, 200 years. So that's a long time in e-commerce and everything that's online counts like ten times normal time. So let's dive right into it and start simple for listeners that haven't heard about it. What is a converse and why should sellers care about it?

00:02:09:09 - 00:02:31:22
Cyril Golub
Well, the most interesting point is that when we are talking about a genetic commerce, in most cases we are talking about buyer side commerce, buyer site agents and the agents who are advising what to buy or what to choose, what to look for and somehow facilitate you to make a purchase. But actually it's only half of a genetic commerce.

00:02:31:22 - 00:03:03:03
Cyril Golub
And for me, it's less important and less interesting. Rather than seller side agents and seller side AI commerce, to be very precise. Actually, I played all my career on the seller side, starting with the ancient days when they're online. Selling means you need to use any of the hostage solution, so you have to deploy it to your own servers to have the team of software engineers, DevOps, system administrators, and so on and so forth.

00:03:03:03 - 00:03:07:12
Cyril Golub
So I saw it from the almost very beginning.

00:03:07:14 - 00:03:20:24
Claus Lauter
So let's dive into different moving parts of AI and e-commerce. Where do you see the biggest changes happening right now? Because things are happening very, very fast right now and we're trying to keep up what's happening. Give me an overview.

00:03:21:01 - 00:03:52:21
Cyril Golub
Yes, sure. For me, the main point here is too much noise and less positive signal about how to see the nearest future. Actually, it happens every time and everywhere. When we see the great shift in any industry, let's say you can see how the software development industry changed recently. For the recent 18 months, probably even less. No one still writing code manually, almost no one.

00:03:52:21 - 00:04:31:22
Cyril Golub
You see that? How it changed the coding itself. The first question, how this similar situation will happen in e-commerce and the selling selling your goods online. It's a tricky question. A lot of abbreviations about new protocols, and probably a lot of us already are getting messed up with different abbreviations. And to understand what to watch closely, actually. And the main question for me today is how AI capabilities could not be just somehow injected into their old good workflows for online sellers.

00:04:31:22 - 00:04:58:04
Cyril Golub
But what if we rebuild, rethink, and recreate the workflow for typical online seller? From the very beginning, with all the AI capabilities by native? Let's say for my main metaphor for this, the monthly briefing, for example, Claus, if you are running the online store, how your typical Monday looks like, what do you think about that?

00:04:58:05 - 00:05:12:09
Claus Lauter
Basically, it's looking in the orders that came in over the weekend and putting all out, all the little fires that came up and whatever piled up in customer support. So Mondays are not fun days in e-commerce.

00:05:12:11 - 00:05:42:01
Cyril Golub
Exactly. But what if you are running not the small 1 or 2 men online stores, but something medium, let's say medium minus, medium plus. And you have the team of Hume, human beings, team members, or several freelancers. The typical case is the Monday morning briefing, and you start your zoom call, or start sitting at front of your office desk with your colleagues asking, guys, what's going on?

00:05:42:02 - 00:06:08:23
Cyril Golub
Let's check our sales for the past week. Let's say check. Where are we? Good. Where are we bed. And what should be changed. You always have one guy talking about your competitors. The another one the analytics who is showing you the dish boards or graphs or pie charts, something like that. And in this case, your Monday briefing can last, let's say, for entire Monday.

00:06:08:23 - 00:06:33:22
Cyril Golub
And shifting to Tuesday to understand the current problem was going on in the market, your competitors, how you handle it through the next week ahead, should you create some more, let's say short term advertising campaign and all of it on this is it's a part of the work, part of the managerial work. But where is the value for your buyers?

00:06:33:22 - 00:06:40:13
Cyril Golub
Where is the value for revenue. And that's the main question for me why we started creating unify.

00:06:40:15 - 00:06:48:02
Claus Lauter
Now let's dive into this. So how can AI agents help you as a seller to survive in this ever changing, fast changing market?

00:06:48:04 - 00:07:19:07
Cyril Golub
For example, one of the main points we are working now, we started with a very simple things to trying to show the value to our customers, to online sellers. We started with Amazon selling market started with a very simple things, for example creating and optimizing your Amazon product listing. But then we moved further and tried to check what if for our company, what if are the main two words.

00:07:19:08 - 00:07:48:06
Cyril Golub
Actually, what if we can scan and monitor not two, 3 or 5 competitors to yours for your store? For example? What if our agents can monitor 100 of your direct or probably in direct competitors? In most cases you can see what's going on in public. But what if your main competitor started your in-house inner loyalty campaign for their customer base?

00:07:48:07 - 00:08:06:05
Cyril Golub
Exactly. Will you see the outcome? Will you see the effect? How it work? Will with your sales? If your target audience are intense, intersect for example, somehow without AI instrument, without AI tool, probably not.

00:08:06:07 - 00:08:11:17
Claus Lauter
So will the AI just give you the advice, or will the AI also take the action?

00:08:11:18 - 00:08:38:16
Cyril Golub
For me, that's the most interesting point here. You can see that in most cases, the modern AI tools are just advising and from time to time they are just substitute their part of their analytics. Instead of watching the graphs, you can, let's say, understanding the human nature. Human language was going on, but this board is the very beginning.

00:08:38:19 - 00:09:14:09
Cyril Golub
I'm completely sure. And probably you already uncovered this topic in one of your previous episodes, that the age of boards is always. First of all, this board is a kind of rear mirror. It explains what happened already. But we need not just analytics. We need not just recommendations and not just the proposals. First of all, clear understanding, proposal and approval from the human being side, then execution, implementation.

00:09:14:09 - 00:09:42:12
Cyril Golub
And last but not least, measurement and feedback. For me it looks like the closing the loop when the human being put their problem in front of AI agents, getting their recommendations, getting their drafts, then approve the drafts, put the implementation all on AI agents, and the human work begins at the end of the loop to put thumbs up.

00:09:42:13 - 00:10:05:03
Cyril Golub
Okay, robots, you did it great. Or please don't do the same next time. So that's for me the main shift. Could we achieve that with injecting parts of AI capabilities into our current workflows? Probably, I don't know, but if we could rebuild the entire workflow from scratch. Actually, for me it's much more interesting.

00:10:05:05 - 00:10:30:22
Claus Lauter
Let's talk about the headache every online seller knows: multiple sales channels, inventory that never quite matches, invoices piling up, hours lost, reconciling instead of running your business. That's where today's sponsor Xero comes in. Xero is cloud accounting software built for growing e-commerce and DTC brands. Track cash flow in real time. Send and chase invoices automatically, reconcile bank transactions in a couple of clicks and see exactly where your business stands from a laptop or phone. It connects with the tools online sellers already rely on. At the time of recording, get a special Xero offer: 90% off for six months using this link head to referrals.xero.com/ecb to see how Xero can simplify your books. Ts & Cs apply.

00:10:45:09 - 00:11:09:08
Claus Lauter
This episode is sponsored by Bizrate Insights. Your analytics can show you what shoppers do, but verified feedback reveals why BizRate Insights helps e-commerce brands understand the full customer journey from discovery and checkout through post-purchase and fulfillment so teams can create smoother experiences, drive more purchases, and strengthen customer loyalty. Move beyond just star ratings, and uncover the insights that show you where to focus next. Turn shopper feedback into clear, practical action at BizRate Insights.com/coffee I love that you mentioned dashboards because there is just there was a overflow of dashboards. Every provider out there has a dashboard, and you end up looking at 20 different dashboards, being completely confused and not knowing what you look at at all.

00:11:34:07 - 00:11:44:09
Claus Lauter
Now, controlled execution. What does that mean for an Amazon seller? Obviously you want to keep control, but you also want to give it to AI. Where's the middle ground? How does that work?

00:11:44:11 - 00:12:12:08
Cyril Golub
In most cases when we are talking about me, we think about it like a switch. It turned on or turned off, but actually it's not binary because for me it's more kind of a ladder that self. Let's say first of all, read, recommend, approve this recommendation and execute implement it or not, or have it like still like a recommendation.

00:12:12:10 - 00:12:45:05
Cyril Golub
In most cases, all the AI native tools now must first earn enough trust from their customers and prove that their solutions, their offerings are reliable to implement immediately on a live store on Amazon account, and only after that to measure it and to get some feedback from the market. It's for me, it's very important and very hard point to understand.

00:12:45:07 - 00:13:23:03
Cyril Golub
Do you trust it in full or your trust is partial, for example. So the AI tools will win only when the customer can have it and let's say not just trial. And then okay, we are working with these two, but some more steps or some more level to trust we for our GDP commerce. We implemented it as a series, let's say as you can see, for example, for ChatGPT the the level of reasoning for Genie five, it's the level of trust.

00:13:23:03 - 00:13:48:13
Cyril Golub
So to be honest, only one customer of Genie five for this moment got to the final level, the highest level of trust. Most of them are still keeping one step below one level below the complete trust for our accommodations. And that's only the matter of time. No other way to earn trust earlier than than it should be.

00:13:48:14 - 00:14:07:00
Claus Lauter
I think it's a very human psychology approach to AI, and I like that. It's just AI has to prove what it can do to get your trust, and then you level it up. So I think that's a perfect comparison there. Now I want to talk a little bit about the practical side in the day to day business of our Amazon seller.

00:14:07:02 - 00:14:14:18
Claus Lauter
How does it look with Jennifer. So where do they use it. What do they have to do to get up and running. Talk me through it.

00:14:14:20 - 00:14:42:09
Cyril Golub
Good point. And you know that we have two types of lovely users to type of our main customers. The old one, the portrait of old, all old one guy who is running his Amazon account, as it was for years, let's say, and more, more than once, who want to get all the capabilities that AI currently offers have on the table.

00:14:42:13 - 00:15:20:20
Cyril Golub
For the first one, actually, we have Genie as the looks like a typical software as a service, typical SaaS just without dashboards. As I said, main point connect your store, then let some time for a adjusts to check, to analyze, and to provide you with recommendations and ideas. Our main point is to find the leaks where you are losing revenue, and it could be in a lot of places based on your particular data from your particular Amazon account.

00:15:20:22 - 00:15:50:22
Cyril Golub
What's coming next? We're trying to get out and anonymize the data from the market itself, because if you are basing on your store data only, it's good, but it's not perfect. What if you have all the use cases once again anonymized, aggregated, but situation that understanding in the explanation was going on on the market. And how does it reflect to your particular store?

00:15:50:23 - 00:16:26:11
Cyril Golub
And I must say that for most of our customers, work with the listings is still the most important part as far as we can see. We are very accurately track all the changes and tracking all the results out of it, because otherwise it's just one more recommendation engine. Engine without measurement and without feedback from the real world. So if we see that the current recommendation can improve your sells, it doesn't.

00:16:26:12 - 00:16:52:03
Cyril Golub
It does matter. Nothing. We should implement it first, and we should check the real statistics. Real data. And our agents are getting back to the results one day more, or probably after a week of experiments and telling you the real truth. Okay, we made these these and that changed. But unfortunately it doesn't affect positively on your sales. So what.

00:16:52:03 - 00:17:15:24
Cyril Golub
These are our next recommendations. Let's try another one and just imagine it at scale. Not playing it your own store, but hundreds or thousands Amazon stores are still keeping experimenting. What does it mean? The healthy competition between sellers, not just what we see now, the competition of Amazon ads. Budget.

00:17:16:00 - 00:17:32:20
Claus Lauter
Yeah, I think Amazon is a universe for itself. And there are so many data points and there are so many options in there. So Amazon has created a very well all too machine there and sort of a monster as well for somebody trying to be a seller there and squeeze most of it. And AI is just perfect to connect all these data points.

00:17:32:21 - 00:17:51:04
Claus Lauter
And now not only for your own store, as you said, but for everyone who's competing with you. So AI makes total sense because a human would just not be able to do this, even if you have a huge team. Not possible. So if a seller wants to prepare for a genetic commerce today, what are the first steps they or the first things they need to look into are?

00:17:51:07 - 00:18:31:02
Cyril Golub
The first things are to see if you should use someone's solution, or you try to do it on your own. For these kind of customers who want to play their own agents, we created the special branch of our solution. We name it by O. Bring your own agent. You know that Amazon ESP API is quite good, and you can get a lot of information out of that and influence on your real data to change something, to alternate something, to make more autonomous work and stand off instead of manual one.

00:18:31:04 - 00:19:03:15
Cyril Golub
But first of all, it looks like real time, but actually it is not. Or you see that the clear gap between your request to Amazon CPI and the result of your request. We created the special layer as Genie API, we called it. That eliminates some problems that we could have with latency that you could have with understandable predictability, let's say with predictability of your operations through Amazon Speed.

00:19:03:17 - 00:19:42:23
Cyril Golub
And next, when you feed your Claude or ChatGPT agent with raw data, it means you spend too much unnecessary computing. And from time to time, your agents are losing context. For Genie Fire API, we implemented their, let's say mid layer. That is not just the raw data and still not their human readable, let's say human readable sentences like your buyer, your buyer a intended to buy your product XYZ with the consequent result.

00:19:43:00 - 00:20:23:18
Cyril Golub
That's something in between. Something similar to embeddings. How the large language models are working. Currently, we believe that our solution could somehow become, let's say, language of AI, commerce, and language that AI agents are talking and thinking about e-commerce, the cases, the intentions of the buyer, the search intention, the let's say the competitors competition landscape and competitors actions that could affect your store, something like that.

00:20:23:18 - 00:20:43:09
Cyril Golub
And in this case, the Geneva customers can plug in their own beloved agent based by Claude or Gemini. Doesn't matter what exactly to plug in using our public skills and to see if they could play with their identity commerce on seller side on their own.

00:20:43:10 - 00:21:01:23
Claus Lauter
That's a very interesting solution. I have so many questions about that, but it's a great way to go just to keep it open. And then you are open to experiment and find the best way to make the best out of the data. So that's that's perfect. Now obviously Amazon sellers come in all kinds and shapes and sizes. Who's your perfect customer?

00:21:01:23 - 00:21:39:18
Cyril Golub
We have two portraits the perfect customer and the ideal customer. And they surprisingly are very different. The ideal customer is their small and medium medium minus Amazon seller that could get most of their AI solutions. So the most of the benefits out of that, not necessarily from genie free commerce. For example, if you want to manage your own account with 100 SKUs, it's okay if you want to sell more than 500 different products, it's starting challenging for you.

00:21:39:18 - 00:22:11:15
Cyril Golub
As the single human being, you must start getting teammates or, I don't know, freelancers, something like that. But with a good AI solution, good AI tool, you can still process five times more data, ten times more data, and update ten times more listings. For example, if we're talking about the copywriting rather than doing it it manually. But the ideal customer for us is probably even not the seller himself.

00:22:11:16 - 00:22:49:16
Cyril Golub
It's the Amazon agencies that are helping their customers to sell online and to get profit. For example, one of the companies on this market was unfortunate was they are currently going to bankruptcy was the Wonder Family. They tried a large agency that tried to help to Amazon sellers to start their business, to make all their research for them and to keep 80%, at least 80% of day to day operations for them, and still sharing the profit to ante to 8,020%.

00:22:49:17 - 00:23:12:00
Cyril Golub
Getting to the operator, 80% is going to Amazon seller. So for these kind of agencies, the teams that are helping sellers to sell profitably are our they are our ideal customers only at scale. We can see the positive, the main positive result of using a native solution.

00:23:12:02 - 00:23:19:13
Claus Lauter
Could you share some success stories or case studies? And you don't need to name the brand that have used your solution and what kind of results they saw.

00:23:19:15 - 00:24:18:24
Cyril Golub
The most interesting point is that we ourselves are the main source of interesting cases to share. Actually. For example, we spent more than three months trying to understand how to use AI agents as the teammates for our company. If we say that, if we say that our customers will use AI agents instead of human beings in their team, why don't we do it ourselves and our very first version of AI agents team for us was for a team members, human beings, me and three, my colleagues and four more AI agents with every each one with their human like name responsible for different parts of parts of our business operations for one phone, one for market

00:24:18:24 - 00:25:03:24
Cyril Golub
research, another one for managerial operations. And the last one, one for organizing the customer relations. I mean, reading the tickets, support tickets, drafting their responses and so on. But after three months of implementation, one that you don't need to copy paste your organizational chart from the human beings era to AI assisted era. Actually, each of the adjunct can produce interesting solutions, interesting ideas, but when you combine all four, you probably can see that combined value for your business may go to zero.

00:25:03:24 - 00:25:38:09
Cyril Golub
For example, if you summarize all these takeaways and all because of different context for most of them. So actually we got back to the system of single agent that just part of his context is working at a different cadence, for example, and analyzing the human sessions. All the sessions of our customers are analyzed by AI now, and I must say that no team can analyze manually more than 100 obsessions.

00:25:38:13 - 00:26:06:20
Cyril Golub
Actually, our agents did it for 800 already. And it's not just understanding what's going on in particular, it's to getting patterns, understanding the common problem cases or common positive cases. Once again, because when you are looking what your customers are doing with your solution, first of all, you are looking for bugs. You're chasing bugs, chasing problems, unclear situation.

00:26:06:20 - 00:26:17:10
Cyril Golub
But today, with the help of AA, we can analyze the positive cases and put more of our efforts to make them even more positive and beneficial for customers.

00:26:17:12 - 00:26:37:08
Claus Lauter
Now that makes perfect sense, and it's fascinating what agents can do, and it's also interesting that you use it, and that your findings basically brought you to have single agents instead of having them all cooking together. Basically, you already touched a little bit on this, but talk me through the typical onboarding process for a new client. What steps are involved?

00:26:37:10 - 00:27:16:11
Cyril Golub
Good question. And we are still in there. We're in middle of the process to find the ideal onboarding. Actually, you may be surprised here, but the main problem with onboarding, for us at least, was to earn enough trust so that our prospective customer will connect his Amazon store to our system. And that was the main painful point. Actually, our first understanding and first expectation from that was if we rely on curiosity of the market, curiosity of our prospective users, they will do it almost automatically.

00:27:16:12 - 00:27:48:16
Cyril Golub
You know how easy it is to connect your store to an Amazon app. Just open the corresponding screen, tap the connect button, click the approve checkbox and all done. Nothing similar. Actually nothing similar. So we decided to start with the value that we could bring to the user before he connects his store. And in this case what helps us, we just asking.

00:27:48:17 - 00:28:36:04
Cyril Golub
Please let us know about the link to your best selling product or to the product that are selling much worse that you expect and we will think, check and advise you what could be done with the public data only without connecting to your Amazon store data. And it helped. Actually. It helped a lot. When people start understanding their value without store connection or the rate of connecting, the Amazon stores get 50% up, as far as I remember is it's currently about 60% between, let's say, start of the funnel and end of the onboarding process.

00:28:36:04 - 00:29:17:12
Cyril Golub
And last but not least, you know that most of the Amazon accounts may look similar, but actually they are very different. And you cannot say, okay, we will check your data and let you know immediately where your revenue revenue is leaking. No way. We are trying not to put such kind of promises to our customers. But if the system saw several several patterns for another clients and another customers, it's helping helping it to provide more sophisticated reasoning and more sophisticated guess for the new client.

00:29:17:14 - 00:29:23:07
Claus Lauter
Yeah, it's all about trust. At the end of the day. Let's talk a little bit about pricing. How does your pricing structure work?

00:29:23:12 - 00:29:55:16
Cyril Golub
Frankly speaking, we don't like to take money from our customers. Now. Moreover, we even discussed should we create our solution completely free for our first 1000 of customers. Unfortunately, we got rid of this idea, but I'm still the great amateur of this point because unfortunately, once again, processing data with a major LMS is not cheap. Not cheap for us.

00:29:55:16 - 00:30:34:00
Cyril Golub
We tried to implement the staged processing so the only the main requests are going to their major LMS and the simpler ones could be processed with the cheaper versions. But still today we are charging customers only when we see the excessive computing, excessive LM usage that we could not cover from from our budget, actually, because Jean-Yves is a venture backed company and our first angel round was comparatively small, only 290 K.

00:30:34:02 - 00:30:54:14
Cyril Golub
When we get the institutional round for free, probably we will implement much more free features. Once again, our main goal is not money. Our main goal for us is data and the use cases that our customers entrust to unify.

00:30:54:20 - 00:31:08:07
Claus Lauter
Yeah, I think everyone can follow. The train of thought is that somebody needs to pay for the tokens, so absolutely nothing wrong with that. Sara, before our coffee break comes on end today, is there anything you want to share with our listeners that we haven't covered yet?

00:31:08:09 - 00:31:38:03
Cyril Golub
Probably the main thing. We can talk a bit. What will happen with this selling side, a commerce in the next year? When I prepared to our podcast, I started thinking about five year term. But it's completely weird. No one knows what will happen even in the next 12 months, so probably I can see that people and online sellers doesn't matter.

00:31:38:03 - 00:32:10:09
Cyril Golub
Amazon sellers or Shopify customers or standalone stores, those who will do their business, business as usual. Probably they will get out of the competition. And for me, the main value and main thing that makes the difference will be if you're still injecting AI capabilities, as I said in the parts of your workflow, or if you remain in the entire commerce for your store based on third party tools.

00:32:10:09 - 00:32:47:17
Cyril Golub
For example, you know that Amazon assistant, Amazon AI assistant says that 90% of its recommendations are approved by Amazon sellers. What does it mean for me? For me, it means that 90% of sellers are losing their chance in the competition because you see that their AI agents are on the both sides. Assistant is advising something to the customers and Amazon algorithm, then choosing what product to show to the prospective buyer.

00:32:47:19 - 00:32:59:07
Cyril Golub
Can we rely on this play to the one single gate? I don't think so. So third parties, third party tools must be the game changer here.

00:32:59:11 - 00:33:17:06
Claus Lauter
Yeah, I would totally agree. It's just having a monopoly which obviously wants to make money recommending everything's probably not a good idea. So that's where third party is really totally makes sense to level the ground. Where can people go and find out more about you guys?

00:33:17:07 - 00:33:30:10
Cyril Golub
Oh, Ginny Feet or my own LinkedIn profile? Cyril Golub. It's very easy, discoverable, and we're sharing all the main news in my profile and our blog.

00:33:30:12 - 00:33:44:09
Claus Lauter
I will put the links in the show notes and you just one click away. Sir. Thanks so much. I could talk for hours about AI, but for today I think we have, as you said, covered a lot and I hope a lot of listeners will reach out to you and learn how we can help them in their business.

00:33:44:09 - 00:33:45:06
Claus Lauter
Thanks so much.

00:33:45:07 - 00:33:51:01
Cyril Golub
Thanks so much, Claus. It was my pleasure talking to you today and to your audience as well.

00:33:51:03 - 00:34:12:16
Claus Lauter
That's all for this episode. Thanks again to Xero for sponsoring today's show. If you're tired of messy spreadsheets and manual, reconciling, Xero brings your invoicing, cash flow, and reporting into one simple dashboard. At the time of recording get a special Xero offer 90% off for six months using this link. Check it out at referrals.xero.com/ecb. That's referrals.xero.com/ecb. Thanks for listening. We will catch you next time. Ts & Cs apply. This episode was sponsored by BizRate Insights. Every customer journey has opportunities to improve. BizRate Insights, turns verify chopper feedback into clear priorities, helping e-commerce brands make smarter decisions, strengthen customer relationships, and help customers coming back. Learn more at BizRateInsights.com/coffee.