How Retailers Can Unlock Growth With AI — Ravi Achanta | How To Grow Your Sales With AI, How AI Turns Your Store Data Into Growth, Why You Should Trust Data, How AI Boosts Customer Loyalty, How AI Saves Hours in Ad Planning (#442)

In this episode, we dive into the challenge faced by independent retailers in competing with giants like Walmart. 

Ravi Achanta, CEO and Co-founder of RSA America, shares how AI is leveling the playing field. 

He explains how small retailers can use the data they already have to drive growth, boost customer loyalty, and uncover new revenue, making powerful retail tools practical and easy to use. 

Topics discussed in this episode:  

• Why independent retailers struggle against big chains. 
• How AI provides simple, actionable insights from POS data. 
• What fear of technology and cost holds retailers back. 
• Why data-driven decisions attract brands to small retailers. 
• How AI tailors communication based on shopper generation and patterns. 
• What one retailer found: only 4% of loyal customers bought meat. 
• How one New York retailer grew seafood sales by segmenting customers. 
• How AI drastically cuts down time spent planning weekly ads. 
  
  

Links & Resources 

Website: https://www.rsaamerica.com
LinkedIn: https://www.linkedin.com/in/ravi-achanta

Get access to more free resources by visiting the show notes at https://tinyurl.com/27pzbftn

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Transcript

00:00:00:00 - 00:00:22:16
Unknown
Hello! Welcome to another episode of the E-commerce Coffee Break podcast. Today we are tackling a challenge every independent retailer knows competing with giants like Walmart. It's tough out there, but AI is giving smaller retailers a real chance to grow, boost loyalty and uncover hidden revenue to show us how. I'm joined by Ravi Achanta. He is the CEO and co-founder of RSA America.

00:00:22:17 - 00:00:43:20
Unknown
He helps local retailers use AI to drive growth and customer loyalty. With over 25 years in tech and entrepreneurship, Ravi's mission is simple make powerful retail tools easy and practical for independent stores. We have a lot to cover, so let's get started. Hi everybody. Welcome to the show. Thank you. Thank you for having me here and I'm glad to be part of this episode.

00:00:43:22 - 00:01:16:06
Unknown
So let's start simple. Why do small and independent retailers struggle to keep up with the big chains like Walmart? But it's very simple. The small chains obviously do not have the the bigger teams like the Walmart, like the target and whatnot. But they do serve the, the communities like, you know, completely different from Walmart. So when you walk into the corner store, when you walk into the smaller independent, most of the time they know you who you are because you have been shopping with your small kids all the way.

00:01:16:06 - 00:01:43:14
Unknown
Your kids are going up to the high school level. So that's how that that's a difference between these two. Grocery in the independent versus the big mega chains. And the struggle is that they do not have the tools available. They do not know how to leverage the data they have. And if you look at some of these retailers are running their grocery chains for the generations today we have the some of the retailers, the third generation people who are running the stores.

00:01:43:16 - 00:02:02:10
Unknown
They have a lot of data, but they do not have the tools and expertise, to compete with these big chains. Now AI is obviously leveling the field there. We know that Amazon and the big retailers, they have huge data scientists departments and they have all the resources they need to filter out the last out of the data.

00:02:02:10 - 00:02:27:03
Unknown
But now with AI there's help for smaller retailers. As a dependent sitting on the data, they have it. They don't even realize how could how could they grow their business was the data they already have, right? So a lot of times the retailers feel that they don't have the data. They do have the data. Every data is in their has tapped in a tribe for many, many decades.

00:02:27:04 - 00:03:02:18
Unknown
So today the when it comes to the AI, you know the biggest challenges that these bigger chains have, what you, as you said and know hundreds of thousands of people working on the data and then they are to bring the what to do. But what we did in independence is the AI is a simplicity, you know, is you cannot replace the human relationships, but how can you bring the data to or by simple things, you know, know your customers better and then also understand their behavior and also like you know, how to price optimization and it's is it all about the discount?

00:03:02:18 - 00:03:38:04
Unknown
Is it about loyalty. So these are the patterns you like to understand. And what we built is a simple actionable insights. Start with automation. Then apply the AI rather than seeing that AI is a big thing, we cannot afford it. So we brought it to the simple. As you log into the, you know, all the AI portals, you clearly see five, six, seven, eight items, you know, actionable items, which is a simple and adopt start smart and start small and then go into the more into the in-depth personalization and other stuff.

00:03:38:06 - 00:04:02:22
Unknown
Now a lot of our listeners are coming from the brick and mortar store world and probably are running a small online store, are looking into e-commerce. Now when it comes to the customers coming in the store, as you said, there is data already there. They might have different, systems in the background. Talk me through an example how a brick and mortar store or retailer approach is a step into the new world of data and AI.

00:04:03:00 - 00:04:29:16
Unknown
Yeah. So an example that in a became a store, either you have the customer coming online or coming to a store and or buying through the these marketplace apps applications today. So we help the retailers to understand that the one unique customer interacting with through multiple channels. And then you need to learn from that when what they're buying, when they're buying and what channel they prefer to buy.

00:04:29:18 - 00:04:56:09
Unknown
And then this I can help you. Is it a that means legally that the loyalty is important or discounts or important? Our other product mix is important. And then if you if you look at this, some of the, you know, we, we have the national largest Hispanic chains in our or using our technology. So if you if you notice the California is for example, or the now the, the Spanish people or the fourth generation kids.

00:04:56:14 - 00:05:16:17
Unknown
So the way you marketed in the first generation, second generation is not going to work for the third and fourth generation people. So the AI is one where, you know, but the traditional grocers think that, you know, hey, you know, this is how we communicated or decades with the Hispanic population, but that's not true with the latest generation.

00:05:16:19 - 00:05:42:08
Unknown
So the AI is can simplify and that you know how to communicate, when to communicate, what to communicate. And then there are those simple, actionable items are going to help retailers to really leverage the data. And also its most important pieces missing is brick and mortar stores. They don't work with the brands directly. They feel like, you know, they hey, you know, I negotiate with my brand, but brand also wants to communicate to the shoppers.

00:05:42:10 - 00:06:02:22
Unknown
So now we are reaching the not only the CEO by using the AI with the brand and retailer and the consumer. So that's the beauty of it. Just bridging that gap. I don't know I've never done a list and it makes perfectly sense. I mean you as a small retailer become more attractive to a brand because one of a sudden you can really deliver data that the brand is looking for.

00:06:02:22 - 00:06:27:09
Unknown
So that's that's brilliant. I've never thought about that. Now is there any kind of news or any kind of reasons that are holding small retailers back from going full online, full AI, full data driven? What's what's the common reasons for them to not do it? Yeah. The biggest thing is that is is a fear of the technology anymore and the hey, you know, can I trust the machine?

00:06:27:12 - 00:06:46:03
Unknown
That's what we always said. Like, you know, well, you don't need to trust the machine unless it trust the data. So trust the data. Trust the human connections. And so bring the human relationships and use the technology to serve them better. So we most of the time we work with the owners or the decision makers of these small independents.

00:06:46:05 - 00:07:11:14
Unknown
And we did a lot of A and B tests. And now the the trust, the thought process behind the AI. And we brought the data into the picture, do the small things together. An example I can give is a, the one of the a pilot was a year ago and they have the naturally their loyal customers are contributing 80% of their revenue.

00:07:11:16 - 00:07:38:01
Unknown
And then when we I seen that by the way, this is only 4% of your top loyal customers are buying the meat from you. They never realized that then that what he led is a true what it is true. Here is a basket of the people that their basket sizes over $100. But if you look at the meat is only 4%, so that is a person not to open up for a, you know, wait a minute.

00:07:38:03 - 00:08:01:19
Unknown
So we've been promoting meat, just like any, any other retailers in the, in the neighborhood. And we are giving it, you know, best discounts. We have the best cooks and all everything is right seems to be right. But why are your top loyal customers are by contributing only 4% of your meat button meat sales? So that means is a is it this?

00:08:01:21 - 00:08:24:13
Unknown
Then we went for the down. Okay. So what? It makes sense to get these people buy more meat, which is appearing the product correctly and pairing the options correctly for them, which makes sense for them. And then also communication is a broad communication to the, 750,000 shopper to watch this segment. Of this ten 15,000 shoppers is differently.

00:08:24:15 - 00:08:51:17
Unknown
Make them all really successful. So now they're increasing 7 to 8 9% slowly. And that means it's a double within 90 days. So that's interesting that, you know, you walk with them rather than say, hey, you know, I am the second biggest fear is the cost. And obviously that, you know, everybody's reading the news on the AI, the that the AI data centers, all these technologies is affordable.

00:08:51:21 - 00:09:09:14
Unknown
So a lot of people will not even thinking, oh, I know what, I don't think it's for me because it's expensive. I cannot afford it. So so it's a constant integration we are doing. And we are hosting a, a small roundtables with the few retailers together educating them. Hey, you know, you don't need to spend millions of dollars.

00:09:09:14 - 00:09:30:00
Unknown
By the way, you start with small, this one, and then, you know, understand your customer. You already have a customer base, but you need to understand them better. Like, and I given the example of this, no Hispanic community is like, no, hey, you cannot communicate to the every customer the same passion. Right? So that was the biggest thing.

00:09:30:00 - 00:10:04:00
Unknown
And then we have a very forward, looking grocers who's adopted AI. And then those case studies are helping. It's a beauty of this independent community cause is to try to help each other. It's not like a the computers of the law to help each other. So we are part of engineer. We are part of Ida. And then the beauty is that in our customers or did they're not, you know, what we call a failure to share their success story with the other retailers, which is a we are glad to be part of that ecosystem.

00:10:04:02 - 00:10:23:03
Unknown
And a lot of times, you see, I don't want to say anything. I don't want to share anything. But this community is different. This community is very different. So that is the only feature. I would say, hey, you know, it cannot be affordable. I don't want to be online or it's too much work or a, this type of things, but it's evolving.

00:10:23:03 - 00:10:45:07
Unknown
So for us, it's actually pushing growth of, you know, your, people are coming online more and more. Yeah. Now, I love the approach that you basically you learn as a company providing them from what they learn. So it's a constant learning from both sides. And it makes your product better and serve them better. Now give you an example on how it looks for the customer.

00:10:45:08 - 00:11:07:12
Unknown
Obviously there's a mobile app to it as a front end. So how does that look? Yeah. So for the consumer side, it's a mobile app and the web mobile app and everything that's the consumer use. And then the way we designed is a if you look at the crawler, if you look at the Walmart and the way back when we designed better than them, honestly speaking, is because keeping a consumer in mind.

00:11:07:14 - 00:11:29:08
Unknown
So what makes easy for the consumer and the why they should open your app or why they should shop at you, your store, things like that. So then for we enabled the, administration portal on the web for the retailers. So when they log in, clearly they see, okay, this is how my stories today, whether it's online or whether it's offline.

00:11:29:10 - 00:11:48:15
Unknown
And then I see my customers in the how they're shopping, what the my baskets are, all that stuff. And then they have a one section right on the homepage. Actionable insights. This this these are the five things you need to pay attention to it. Example. Hey this category, your sales are coming down compared to the last week or last month.

00:11:48:17 - 00:12:14:23
Unknown
What's wrong with it? You know, is that a promotional strategy needs to be changed or home and things like that. So now with the AI, it is giving an an actionable. Not only the report is giving an action. By the way, these are the five things with a command to promote to this segment of customers. And then we recommend like and I'll change this price to this skew and and also pay this product with this product.

00:12:15:01 - 00:12:38:01
Unknown
And then sometimes they it's unreal. We have one of the largest customer. They are SEO merchants sitting in the AI reviewing the AI. And then it said, wow, meet with the red cabbage promotional. You should do the legwork. They said they meet with the red carpet or the everybody said, look what red cabbage. I know we never done that before.

00:12:38:06 - 00:13:01:05
Unknown
Obviously you never done that before. This is why it is recommending that to me. To with the red cabbage promotion. Pairing those two products was a eye opening for them. And he said, like, you know, I suggested 50% red cabbage for discount with the pound beep. But the merchant said I can give 80% discount on the red keyword and what that means.

00:13:01:05 - 00:13:24:14
Unknown
Here you go. Now you know the cost. But now I is telling you why they wanted to pay this way. It is based on the whatever. They know that ESP based and and on the way you cook the meat and things like that. But now you know the cost of the red cabbage, you are saying that the 50% discount, but you're saying I can give it 80% discount because red cabbage is coming pretty cheap for them.

00:13:24:16 - 00:13:56:06
Unknown
This is these examples were, blue. Well, the way I is suggesting. And we have another customer in New York and they're known for the seafood that they say that we are the best in the town. We you know, a lot of this, a lot of seafood sales. But interestingly, we I segmented a few thousand shoppers, I mean, probably 20, 30,000 shoppers, seeing that they're not buying the seafood at all, that they are not buying this report at all.

00:13:56:09 - 00:14:21:16
Unknown
Of course, that is small percentage. It's A25 thousand out of 350,000 loyal shoppers is a small sect, and that they never paid attention. Okay. In my top line sales, Seafoods great. My loyal customers are buying the seafood, but when they look at this 25,000, I is saying that, hey, if you do this, probably this, these people will buy the, you know, seafood from you and then the cargo adjust for that segment, buy suggestions.

00:14:21:18 - 00:14:47:00
Unknown
And within 90 days they grew to the thousand sales on the 25,000 people, which is a very small. But now probably they're up to a million, with they never bought the seafood from them. Some reason, whatever the reason it is and the with the baiting and pricing and the discounts and frequency of the communication to those people buy I is like late.

00:14:47:02 - 00:15:10:01
Unknown
So now they are like running frequently in the sense like they completely automated. They completely automated for this 25,000 people. I have this communications, this much budget left and then let I run every week. It runs. It gives them an actionable insight. Hey, this is what it performed. And it I wanted to tweak these things, which is they made the life not so easy today.

00:15:10:03 - 00:15:36:00
Unknown
And these are the insights which retailers are trying to take an advantage now from the other retailers. I can totally understand that as, as the frightening I sometimes seems it has so many benefits to it and so many surprising outcomes to it that it just makes sense to put it in. And again, it helps to have a, a personal relationship to your customer.

00:15:36:04 - 00:16:05:20
Unknown
Now the AI is building this relationship depending on the customer. I want to go a little bit more on the technology side of things. Obviously, the retailers have different tech stacks, their, uses system. What kind of APIs and systems do you support to make it work? Yeah. So what we did is first of all that, you know, we built a database which can consume, the data from different sources and from the point of sale, from online sales, from the, you know, a third party and all marketplace applications.

00:16:05:20 - 00:16:35:02
Unknown
So all this data is coming input in the into the centralized database. And then you have a loyalty number attached to it is the unique identifier of the shopper. And then we the we have these algorithms like the AI algorithms which trained for that retail rather than training across the. Now we have for 1400 stores. And then the 6 million shoppers, rather than training a core 6 million shoppers, we train the models for their set of data.

00:16:35:04 - 00:17:01:21
Unknown
But and we also at the same time, we train the, you know, a broader level, a close to like if you look at the General Mills, if you look at the P&G products, what that the model is saying about those products. But we predominantly train the local shoppers data, and then that gives them very specific to their demographics, their customer data, and typically 18 to 24 months worth of data.

00:17:01:21 - 00:17:29:18
Unknown
That's where we use it to train that, train the model and then start with again. We simply started using the ML initially. So machine learning data and then eventually gradually converting into the I believe. So this is a common which is not a heavy lift. You know, you just we have the APIs or even we, we have the XLS, the CSV based files.

00:17:29:18 - 00:17:51:16
Unknown
Can we dump it into secure data, you know, whatever the ATP, and we consume it. How old the data is, we took the we are taking the heavy lift out of it. So let's pump the data into the database so that we can train the model. Brings me to my next question in regards of onboarding. You said you're actually I can come with my spreadsheets and you will help there.

00:17:51:17 - 00:18:16:22
Unknown
What's, what's the typical onboarding process. How long does it take. So the onboarding is it for a is some customers are using already our loyalty. Their a loyalty solution for them is a plug and play. And then the some customers are not using our loyalty or e-commerce. And then for them is a typically two weeks to to pipe the data in and then start mapping the algorithms.

00:18:17:03 - 00:18:40:22
Unknown
So two weeks to onboard, two weeks to do the R&D and then bring them completeness to the retailer's head. How is it do you see versus like, you know, basically testing our human intelligence with the AI and then make sure that we blend them together? Not losing the human relationships to especially, the communication aspect, the communication to the consumer is changing with AI, right?

00:18:40:22 - 00:19:01:04
Unknown
The personalization come in play. So now you have a instead of giving you here is the flier as you walk into the store. And hey this is our front page is the back page in words. But everybody's the same. But now that you know with this segment of customers, it's a brand very changing. So as you they open the app, they see the did different things and you see your your front page.

00:19:01:04 - 00:19:22:17
Unknown
I see my front page is totally different. Could be like some common items there. So the timing of the communication also changing. Like previously they used to send their one email Wednesday, one year, one push message on Saturday or one in the middle. But now it's changing based on. No. You may be shopping on Friday. I may be shopping on Sunday.

00:19:22:17 - 00:19:48:23
Unknown
Somebody in the middle of the week. So based on your shopping patterns and when you're shopping, what time are you shopping? That means that tells a lot about you. You don't want to be getting to the rush hour to do the shopping with the thousands of people in the store, maybe, you know, so that that is also helping a lot with, with these retailers because of the model is trained just on the database.

00:19:49:01 - 00:20:14:04
Unknown
So there's a 3000 neighborhood shoppers or array or a very entire geography, Chicago, like, you know, northern suburbs, which is the southern suburbs. So, so they demographics, they data. And that way it's a very, very, model is like an easy to train. Now, a lot of our listeners might ask is like, how many how much time do I have to invest in maintaining the system and running the system?

00:20:14:06 - 00:20:35:20
Unknown
How does it look on a day to day basis? That's a great question, because this is another thing is not only the, the retailers do not have a lot of teams. Biggest question always ask is, hey, how much time I need to spend? And, on a, on a daily, weekly basis. So we say on a weekly basis probably two hours.

00:20:35:22 - 00:20:57:08
Unknown
And then the daily base at to 2 to 3 hours, a max daily basis because you, you spend a good one hour or 1.5 hour and during the week or beginning of the week or end of the week to set to see what's happening. And then look at the, look at the data, look at the report, look at all the traction, good suggestions.

00:20:57:08 - 00:21:16:13
Unknown
And then you said, okay, you approve, disapprove or modify the AI suggestions and run it. And then daily basis, you just log into the system and see if you have any reds or yellow, amber or whatever to pay attention to it. And then sometimes you go in the middle, most of the time it's like very rare, but sometimes it can be.

00:21:16:13 - 00:21:34:02
Unknown
Let's say you're running a half flash sale on Tuesday because that's what I suggested. That's what you thought is the right thing to do. But all of a sudden, Tuesday's climate says there is going to be a rain all day. And then that means you'll be more, you know, start altering a little bit on that because of the weather pattern, is there.

00:21:34:02 - 00:21:51:22
Unknown
Right. So these are the five, ten minute changes, you know, and then in this case last class of study two the last year is going to be still there by the way. But you do will extend it to the Wednesday. Also like you see sometimes Kroger Wal Mart here. By the way we have two days here. Now this week Y is supposed to be one day.

00:21:51:22 - 00:22:13:05
Unknown
But now it's in the two days with the digital tools today you can do that. So that is the what the time they need to pay attention to. Is it in my system is running smoothly or they were because of the weather pattern. Whatever it is, I need to modify load or not. So I would say that the 2 to 3 hours A is a good enough time to what?

00:22:13:06 - 00:22:33:21
Unknown
That's the beauty of you. I you know, if you are self spending 40 hours basically you don't need I don't want. I think 2 to 3 hours is absolutely doable. And it's probably less time than you spend with your external marketing agency on working on a new flier or something like that. And the outcome properties tons of better than anything you can do in the old fashioned way.

00:22:34:01 - 00:23:00:23
Unknown
Now tell me who's your perfect customer? So we we have the one store operator way back when we started because our passion is about serving every independent. Don't leave the indie independent behind. That's our our our model. But ideal customer base today being like a 25 to 50 store chain. And, but we we still have a lot of, couple of hundred, a 1 to 5 store chains.

00:23:01:01 - 00:23:24:03
Unknown
And then there are great operators. We love to help them. We still work with them. And just like we work with the 25 or 50 store chain, but our largest customer has 155 stores. So we but the the philosophy of the RSA behind the scenes is the same. We we work with them. The one store operator, our 200 store operator the same way.

00:23:24:04 - 00:23:46:19
Unknown
So we dedicate our time each store, each customer has their own dedicated customer service and technical support. So the way the we brought the we are small team, but the way we brought the AI tools is to help them, to help them. That an example of the weekly ads to you said like, you know, working with the agency, third party agency, but it brought up a good point of that.

00:23:47:00 - 00:24:15:17
Unknown
So to the before I the before this, looking at the data driven decisions retailers used to spend like, you know, bring all the buyers into the room and putting all the previous ads and then each buyer will bring the product movement data in in Excel. Hey, I sold it with this price, this smart display that's that's a constant a day worth of time with the cancer people to create a net.

00:24:15:19 - 00:24:38:17
Unknown
Now we the AI is giving you, hey, this is our recommendation based on this and based on the inventory price and the pricing based on the past, last year, this week, what happened this year, what happens? And this year, what's the weather predictions are prices are and all that. Based on that it will split and give you each buyer by category, give you the next sell streets.

00:24:38:17 - 00:24:57:01
Unknown
You know you you modify as you see fit. So now it's a like a 30 minute conversation. Everybody come up to the come still dick still come to the room. But they say hey well know I reviewed this this this based on the results. And then this is what, price of the product is. And this should be on the front page.

00:24:57:01 - 00:25:14:11
Unknown
This should be on the inner page, whatever it is. And then within one hour, they're done. Yeah, I think that's it's completely no brainer to, go the road. Was I to hell up there? I've spent a ton of time in the United States and I always got a small retailers like the flier was like, I don't know, baby stuff.

00:25:14:11 - 00:25:31:20
Unknown
And I was like, yeah, that's definitely something I wouldn't buy. So it's it's just a waste from for everyone and getting the right information in the right moment, as you mentioned, that that's the way to go. Tell me about your pricing structure. How does that work? How do you charge? So the the way it is a SaaS based per store, per, right.

00:25:31:23 - 00:25:55:17
Unknown
So that the reason we came up with that model is a it's a based on the size of the stores lately, because we have to be a mindful of their, you know, their revenue, their profits and whatnot. So we came up with the SaaS based. So there is no upfront heavy lift. Hey by the way, we going to do this data consulting to bring all your data to set up on all that stuff.

00:25:55:22 - 00:26:29:11
Unknown
So we charge a very bare minimum like nodes could set up cost. And, that varies from $2500 to $5000. And then afterwards that the, as you used, system to monthly SAS so that store per month basis and typically that, you know, the most of our customers today. A we are glad that, you know, this is one thing, help me also, based on my past, history and my pattern, my know, my family grew up with how do I grow up when I was a kid.

00:26:29:13 - 00:26:52:02
Unknown
So we started giving them so much support, so much thanks to the discipline, the benefits over the years. Now they're giving back to us. So if you look at the beginning, going back in many ways to a the public, you walk about talking about Odyssey, that's one good thing. And then B is A they are they have no fear of signing the you know, if I say a three year contract, no problem.

00:26:52:02 - 00:27:12:06
Unknown
We want you to be the light, calm partner rather than worry about the three year or five year. So we have no issues on that. That means is our a what do you call this relationship? The retailers became much stronger and stronger because of the based on the trust we built in the early days. Yeah. I think trust is the most important thing for smaller retailers.

00:27:12:06 - 00:27:28:22
Unknown
But when they do business with someone and on this definitely given was your solution. Probably before we come to the end of the coffee break today, is there anything you want to share with our listeners that we haven't covered yet? So one thing I want to share that, you know, I never told anybody else because, you know, when when we started this passion.

00:27:28:22 - 00:27:57:08
Unknown
So I grew up in agriculture and that became a technologies because I was an agricultural family. But partner is also I grew up in the restaurant family and became the marketing graduate from Waterman then. And we started this one a we saw the biggest opportunity as a business, you know, because the retail or independent sector is a $250 billion, market share in the United States and 20,000 independents out there, 20,000 independent stores out there.

00:27:57:10 - 00:28:21:13
Unknown
And there is a big gap in the digital transformation, right? So a lot of companies reached out to us as we are making all the way up, is a, hey, will we like to invest in your company? And we'd like to put 5 million, 2 million, you know, whatever or the period. Then I we realized one thing that, you know, we are about to take money from one VC company.

00:28:21:13 - 00:28:46:07
Unknown
I don't know or name it, but the. So when we ready to take the money, then we realized one thing which is a hey is all money comes with the problems. Of course money needed to scale the company as well, but can we pull fill the retail of needs and then this VC needs. Then two days later I realized that I don't think I can justify both of them.

00:28:46:09 - 00:29:11:11
Unknown
Then we said, look, I know politely and we're still friends with those of that VC company. Although Saint Louis. And then, hey, you know, I'm so sorry, but I'm allowed to take your money, but I, I'm afraid that I can fulfill your obligations and and then are so happy about it. And we did not take that money because this industry is a very slow but a very passionate.

00:29:11:13 - 00:29:41:04
Unknown
Unless you have a passion to support the industry at all, unless you can invest your valuable time with the retailers, be patience with them, work with them. Otherwise, this is not for this is not for your your business. And then that's the reason we put every store, every single store, 1400 locations across the United. We've been to the store to train the store, train the people, train the staff.

00:29:41:05 - 00:30:09:03
Unknown
And then constantly every other year, probably, we go back to the store again and every month we talk to them. Every quarter we review the data. So that's where kept us today. We call it a fastest growing er company in the in the independent sector. I like that story. I know we couldn't possibly do a complete story about how to deal with investors and venture capitalists and whatever, but that's a story for another time.

00:30:09:05 - 00:30:30:01
Unknown
Ravi, where can people go and find out more about you guys? I'm sorry. What did you say? Where can people go and find out more about Rs. Oh, so we know the our website Odyssey america.com. That's a then we have. But, you know clearly call to actions contact us and they'll immediately and go and talk to them.

00:30:30:01 - 00:30:55:08
Unknown
That's the most best way to to reach out to us. And there are other partners and a lot of partners out there with idea, and they all know about Odyssey America. So it's a lot of customers come through and gig as well. But we have the WW Odyssey america.com. That's you can see a lot of case studies are down there and what our customers are saying about it.

00:30:55:08 - 00:31:12:04
Unknown
And then that's the best way I could. I will put a link in the show notes. Then you're just one click away and people can find you easily. Ravi, thanks so much for your time today. I think there's a lot of listeners who are really curious now to find out more and how they can implement this in their own business, and I hope a lot of contacts will reach out to you.

00:31:12:07 - 00:31:14:17
Unknown
Thank you so much. Thanks for having me here.