Boost Revenue with Smart Pricing AI: Ecommerce Negotiation Strategies - Viacheslav (Slava) Sabirov | Why AI-Powered Negotiation Transforms Pricing Strategies, What Makes Personalized Negotiation a Game-Changer, Why Seasonal Sales Models Are Obsolete (357)

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In today's Ecommerce Coffee Break podcast, join Slava Sabirov, CEO of batna.pro, to explore a groundbreaking approach to retail pricing.

Discover how AI-powered negotiation systems are transforming e-commerce by enabling personalized deals for individual customers.

He shares insights from his extensive background in pricing strategy, including successful implementations in fashion and mattress retail that have dramatically increased average order values and reduced overstock.

Topics discussed in this episode:  

• Why AI-powered negotiation transforms e-commerce pricing strategies
• How dynamic pricing can increase average order value by up to 40%
• What makes personalized price negotiation a game-changer for retailers
• Why traditional seasonal sales models are becoming obsolete
• How AI helps retailers solve inventory overstock challenges
• What drives customer loyalty through intelligent pricing interactions
• Why conversion rates improve when customers can negotiate prices
• How different industries can benefit from smart pricing technologies
• What makes Shopify integration simple for e-commerce businesses
• Why upselling becomes more effective with AI-driven negotiation systems

Links & Resources 

Website: https://batna.pro/ 
Shopify App Store: https://apps.shopify.com/batna 
Check out the BATNA.pro Affiliate Program: https://tinyurl.com/batnapro 
LinkedIn: https://www.linkedin.com/in/sabirov/ 

Get access to more free resources by visiting the show notes at
https://tinyurl.com/4artakwz 

MORE RESOURCES

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Transcript

Welcome to the e commerce coffee break podcast. In today's episode, we explore how AI powered negotiation systems will transform the future of retail in e commerce by personalized deals for each individual customer. Joining me in the show is Slava Sabirov CEO at batna.pro. So let's dive right into it.

This is the e commerce coffee break. A top rated podcast that helps you become a smarter online seller. Each week, your host Claus Lauter and his guests share what's working right now to grow your store, boost your sale. and stand out in a crowded market. Stay ahead in this fast changing world of e commerce and get expert advice you won't find on Google.

Hello, and welcome to another episode of the e commerce coffee break podcast. Today, we want to find out why negotiating personal deals with your customers is the future in retail and e commerce. Joining me for this today is Slava Sabirov. He is the CEO of but not dot pro previously. He was the head of pricing at the KTV group and product manager at UCA, where he drove 70 percent revenue increase per user before it's 200 million acquisition with a background in investment analysis and master's degree in data science, including studies at MIT.

He brings unique insights on pricing optimization and business growth. So he's a seasoned expert in pricing strategy and I want to dive right into it. That's what came up to the show. Hi Slava. How are you today? 

I'm good. Hi, Claus. Nice to meet you today. 

Slava, we want to talk about negotiating prices online and offline, and many of our listeners might think in negotiating prices, that sounds a little bit chaotic.

Give me a bit of a background. Why negotiable prices change the way we think about pricing? 

Well, pricing is a very challenging topic. And in particular in some areas like fashion, where you always have a new assortment and you have to ideally understand what price tag would be optimal for the entire season, but nobody can accomplish that.

That's why we usually have seasonal sales. As a tool to compensate for the mistakes of the pricing that we do in the beginning of the season, which are inevitable. So the other approach is to try to do personal pricing and to understand how much a particular person is ready to pay for a particular product.

And if you can do this, because a particular person comes to your store in a particular point of time, and in that point of time, you know, what is the demand on this product. Now, and so you can negotiate efficiently with this person and try to sell to him as many products as possible for as high price as possible.

Okay. Now, obviously if you're in the store and you have a salesperson, I can imagine that can work, but doing this digitally sounds a little bit difficult for me. So, and I think you came up with a solution to help that. That being said, with personal pricing, why is it so tricky to do this online? 

You have to come up with a good user interface.

So the trickiest part is the dialogue. How do you conduct an efficient dialogue to understand what is the real intention behind the user? And it turns out to be very tricky and to build this algorithm correctly, I spent seven months full time in offline store watching every conversation between the salesperson and the customer.

And I was lucky. Yeah, it was. Lucky many times to get this knowledge. What would be the correct way to negotiate? And it's very non obvious and not easy. It may look like it's very simple and like many store owners who I talk with tend to oversimplify this. Oh, it's easy to build. You just set some threshold.

And if somebody offers a price above this threshold, it means we say yes. And then if below we say no, but this is not. That's simple. So the dialogue is the most difficult thing here. 

Now, it's not very common to negotiate prices in the Western world. Obviously, there's countries in the world where that is the day to day thing to negotiate prices.

For instance, in Europe, in Germany, people might be surprised that they can negotiate. How do they react? 

Um, well, we have over three years experience in one of our money exchange franchises in Europe and over 80 percent of people actually negotiate. Once they learn from the sales rep that there is such an option, they do.

Only those who don't care about prices and there are some people who don't, they don't do this. Everybody else is doing and enjoying this. And we have very, uh, Low negative feedback only from people who used to buy a t shirt at the minus 70 percent sale in the end of the season. They come to the store and then over the season and they don't see the seasonal sale and they're a little upset.

But the trick is that these are the customers that you don't want. You want the customers who come early and you can upsell them because the system from this dialogue upsells. This is the interesting thing that if we, let's say, I'm not happy with the price that the person is ready to pay for a particular pair of jeans, we say, okay, you can buy this price, but you have to buy something else as well.

And that's how you upsell. And then when he chooses the second one, we can say, now when you buy a third one, the second one becomes cheaper and so on. And this chain goes on and on. And we have really good, uh, chain of discounts that maximize the order volume. 

That makes perfect sense. So let me just summarize that.

So basically you're giving them a chance to negotiate the price, but they have to buy a second product. Is that right? No, 

you don't have to. So what the system does behind the scenes, it evaluates every product. In real time, based on the stock dynamics and the offers that other people do when they negotiate.

So every product at every particular point of time is valued. And this is the price that we think that if you don't sell it, that it is good for us to sell it now. So if someone, and we see that someone can offer more than that, we are happy to approve it. If you see that So, and you won't have any conditions to get this discount.

If you see that this is the maximum you want to pay. You're ready to pay. You'll never say it by the way, but we will learn it from the dialogue. So if you see that, okay, this person is ready to pay 150 bucks for a pair of jeans, and we are valued this product at 120, we say 150. Good if you buy something else, if we 140.

But sometimes the things are an opposite way, that you are not ready to pay as much as we value the product. And we are valued by looking at the stock dynamics. So if you're not ready to pay as much as we want, we say, okay, but buy something else, please. 

Okay, perfect sense. 

Yeah, people do want to spend extra time and reevaluate again all the assortment of the store to find something that would fit and Will allow to do to get a extra discount for something that they want Initially.

So that sounds to me that there's a lot of data points in there. And I think AI is the helper in the background there to make this work. Talk me through the way on how AI shows the best products and the best deal for the customer. 

Well, again, the AI in our case is used in this dialogue. How do you.

understand what offer to give to a particular customer. So our goal is to find the optimal set of products and prices for every visitor, store visitor, optimal in the sense of maximizing the margin. So for someone, it could be one product at a full price. For someone, it could be five products at minus.

Whatever, 40%? Sometimes it makes sense to sell at this high discount. So, yeah, in our case, we actually use AI in two different ways. The main one is the dialogue. How to understand, how many attempts to give to a customer, to, you know, offer something, what hints to show him, what questions yes, with the yes and no answer to ask.

And then another thing is a prediction of demand, how to evaluate a particular product at a particular time point, because we see the, what the names of the traffic is, and so we can do it more accurate, the evaluation. So we are evaluating a person, his intention to buy a particular product. item and we evaluate items standalone.

It is very challenging to do without an AI here. 

I can imagine. And in the beginning, you mentioned that in the fashion industry, they have high turnover, they have seasons, they have overstock. How does your system help with that? 

Yeah. So basically if you mispriced an item, let's say you have two similar t shirts of a different, slightly different color.

The demand on them could be 10 X different. So 10 times different. So what happens that you price them similarly, and then one of them sells well, and the other one sells not well. So you wait for a long time and then you do minus 30 percent and then this second T shirt, which doesn't sell well, it doesn't sell at minus 30 as well.

So then you wait again and then minus 50 and then at minus 50, it starts to sell, but not very good. So what happens is that before you did the minus 50, all this time, this product sits on the shelf. And with your capital frozen at the wrong price. And so you wasted a lot of time. So what you end up with, uh, with a traditional sales process, including which includes seasonal sales, that at seasonal sale, you already have an overstock that you have to flush, or you will be ended up with.

It's a new collection coming in. You still have unsold stock and you have to go to outlets and sell at 2 percent of value. So in order to avoid this, our system keeps track of the demand of every single product. And when it does an upsell offer to someone, for example, someone is not ready to pay as much as we want for some product, we say, okay, but you have to buy something else.

And then something else from a special list of the products, which are of low demand. And this is, everything is very carefully calculated. So you don't have to think about, Oh, what should I do for this weekend? Should I do discounts on a particular category or how much discounts you never know, you just can use our system and make it autopilot.

You just forget. You just set the prices, set the maximum discount we can offer. And we will, by the way, very rarely offer as maximum discount. We will try to do our best to maximize your. Margin on every order in urban will end up without overstock. You don't have to do seasonal sale. That's what happened with our money exchange.

They have no seasonal sales for three years. Now we are the only way, I mean, the particular franchise, we are the only way to get a discount in that franchise. 

So Armani Exchange is using your system, obviously, and you said they're not doing any seasonal discounts anymore. Is that right? 

Yeah, the particular franchisee of Armani Exchange.

No, not the guys from Milan. 

Okay. Okay. And you said, what's, what's the increase in average order value they saw? 

So the average order volume was very stably. So we compared to other franchisees and to previous periods. Yeah. It went up almost by 40%, but I have to give a disclaimer, the number of orders declines because in the end of the season, the people who tend to buy Uh, t shirt at minus 50%, there is no such order because you already sold this t shirt to someone else much earlier.

Because they sell something earlier, you tend to sell it at a higher price. But the, actually the decrease in number of orders is not very significant, but it is such thing. Yeah. So the number of units per transaction increases by 20%. So we get a discount that you will do through an entire, the season will drop by half.

Your UPT will rise by 20%. So, and it results in about plus 38 percent on average. 

I mean, this is a kind of a very impressive number, um, to get these results just by dynamic discounting by dynamic price negotiation. I was also 

surprised. I didn't know in the beginning how it would work, but it works very well.

Now, I think the interesting part in there, you can do it with your system in store and online. Talk me through how it works in store. 

Yeah, you can do both. So in store, you print our QR codes on every product. Or you can do also one single QR code per store, but it is better to put a particular QR code for particular products.

Because in this case, from the user journey, you exclude one extra step to choose the product. Many stores have many products. So is it better to put, uh, and we do it integration between your ERP system and our system. So you know, we should call to print on which product. So what happens is that the user grabs his phone.

So there is a product, a price tag, a price. He can just go and buy this price or if he is not happy with this price or he tries to trick you he scans the QR code and offers whatever the price and then the system might give you a second chance and then it is complicated but after about 30 seconds 30 seconds to a minute dialogue we understand a real intention of this user and then Everything goes as an online store, except that, so you negotiate in your phone and then you are shown a special QR code that you show on the cashier and the cashier scans this, your particular QR code.

Again, we have an integration and then the process on the cashier even speeds up because your cashier doesn't have to scan a barcode of every product. He scans just our single QR code and all the products at the correct prices already in it. 

Very, very cool. How does negotiating pricing help building customer loyalty?

Are customers coming back because of that? 

They do. It's interesting to watch them doing this. And there are some people, some particular people just start to go to the store much more frequently because of that. Every time they come to the store. Shopping mall, they come, they at least try to negotiate. So it drives traffic in a secondary way.

We are not positioning ourselves as a marketing tool, which will attract people and new customers to your store. It will attract the ones who already used it. So since we're keeping this very high percentage of usage, it means that the people are happy because many of the customers are repeat customers.

So if the percentage of the use doesn't drop, it's It means that they're happy to use it again. 

Okay. Now we were talking about the parallel and fashion industry. Are there other industries where this would work very well? 

Yes. We have another example with company called Ascona and it's about a billion in sales, annual sales company.

They sell mattresses and beds and. Goods for sleep. They are present in many European countries. They have a factory in Portugal. So in their case, what we did, we increased prices. So in our money exchange, we don't increase prices. We just reduce the discounts that the store does. And with Ascona, we increased prices like plus 25 percent on certain models and then allow people to negotiate.

And we ended up selling at Emetris at 11, almost 11 percent higher price. Uh, on average, there were people who paid plus 25 percent because basically what we are solving for fashion retail usually have a warehouse. Which is full of stock and you have to balance this stock versus demand. For Ascona, they don't have warehouse.

They do the mattresses on demand. So once someone comes and buys it, they make it for you, especially so they don't have a stock. So the way to make more money in their case is to increase prices. And it worked really well. I can't imagine it in many other setups. We actually are going to launch soon with a liquor store in Cyprus.

One of the larger ones here, it's not a very big place still, but it is interesting how it will work there because they also have a very, they haven't even worse overstock problem because you have to have a good, a sort of a very big assortment. And if you have a big assortment, you always have a very large number of SKU with a very low.

And this actually, unfortunately for the retailer, this is where you're usually make your money. So you make your money and not on the traffic generating categories, but the ones that are low turnover. And that's, I hope that it will help them to manage this inventory better in an automatic way and in a fun engaging way at the same time for the customers.

I think that. Fashion has the strongest problem with pricing in general, but there are other places where we can work, but we just don't know how it will work in other places besides of mattresses and fashion. I have an idea how it can work in FMCG because I'm from the company which I was in charge of pricing in a big FMCG company.

I mean FMCG retail. Because they're very important thing is the first price. If you can offer a first price on a particular category, traffic generating category like milk or bread. So what basically is happening is that they, all those guys, they're trying to, uh, different chains of stores. They're trying to optimize their set of traffic generating categories and try to find the optimal prices.

For them, because you cannot offer the best price on every traffic generating category and you have to play, play the market, but with this thing, if you can do conditions, we can do a first price on everything, no matter what the customer came for to the store, we can offer the best price for him. So this is a potentially very good thing.

And there are a lot of other things that I would try, but we actually, we didn't try this yet. And I would like, but first we need to scale whatever works and the fashion works pretty well. 

Yeah, I can imagine the fashion industry, as I said, high turnover, low profit margin, and every system that helps to increase the average order value, to increase the sales and to reduce the overstock definitely does help them.

Now, you also have a integration into Shopify and other platforms. Tell me about that. How does the onboarding work? 

Yeah, unfortunately, we only have a integration only to Shopify now among e commerce, but it's very convenient. You can set it up to your store in Shopify. 10 minutes. If your story is not heavily customized, if it is, we will be happy to help you.

In every step, we will do custom things for you. No problem. Just, you can message me, write a support, and I will get this email and we will figure it out for you. We are very open to We're new users and, uh, happy to customize for them. 

Okay. So you can customize the app as well. Tell me a little bit about the pricing structure for the Shopify app.

How does that work? 

So we have a free plan, which will be free forever. You can sell up to 200 bucks. It's worth of orders with our system every month, and it's free. If you want to sell more, then we charge 99 per month, plus 3 percent per transaction. And it makes a lot of economical sense. It may sound like a little high, but once you start using it, you try the free plan.

You will see how your UPT goes up. Your discount goes down. Your virtual ready volume goes up. And you will understand that 3 percent for this is not much. 

Specifically starting with a free plan. I mean, that gives you a good chance to try out the system and see the results that you have, and then you can upgrade anytime.

So I think overall having AI helping with negotiating the prices and just getting stock flowing quicker through your store into, um, to the customers is a huge help. And I think there's also a bit of a gamification idea behind it. I'm sure that customers love the idea that they can negotiate and And, um, get the best deal for them.

Now, before we come to the end of the coffee break today, is there anything else that you want to share with our listeners that we haven't covered? 

I don't think so. Just, they didn't mention that actually also works well for conversion, because if person comes and he sees a price tag, he just goes and you never know why he actually went out of your store.

They say that the number one reason is the person living is the price. So if he will have a option to negotiate, you will have much better chance to convert him. And this is the crucial thing. And then you can upsell and everything else. But the thing is that conversion is a king. 

That's perfectly well.

So great. Cool. Thanks so much for giving us an oversight on how your system works and the benefits that come with it. I hope a lot of people will reach out to you, try the free version and then hopefully become customers of yours. Thanks so much for your time today. 

Thank you, Claus. Thank you very much.

Hey, Claus here. Thank you for joining me on another episode of the e commerce coffee break podcast. Before you go, I'd like to ask two things from you. First, please help me with the algorithm so I can bring more impactful guests on the show. It will make it also easier for others to discover the podcast.

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