Setting prices must be one of the most complicated responsibilities of an entrepreneur. There are several factors that come into play. In the case of eCommerce sellers, these include bestseller rank, reviews, conversions, and more. Oftentimes, a seller would end up overanalyzing their pricing strategy. Or worse, they end up setting the wrong price and not being aware of it.
Chad Rubin is the founder and CEO of Profasee – an AI pricing tool designed for Amazon private label sellers. Profasee is Chad’s solution to all pricing concerns, guesswork, and complications that become barriers to your business’s optimization and growth.
Watch Chad at the Seller Roundtable with Amy Wees as he demonstrates Profasee in the video below:
AI Pricing Tools have been here for a while. In fact, Amazon Seller Central offers an automated pricing feature in your seller account. The exclusive Amazon seller central pricing tool allows you to adjust prices on SKUs based on changes in the Buy Box price.
So what does Profasee have to offer that Seller Central’s automated pricing tool and many other tools cannot? Check out the unique benefits of Profasee below:
- Profasee helps private label sellers – not resellers. They are only concerned with sellers that have an independent pricing strategy – not with big brands that follow a certain price point.
- Profasee’s algorithm is constantly evolving, studying patterns in your customer’s buying behavior. Through time, Profasee gets better at predicting the best prices that would lead to a sale.
- Based on algorithm, Profasee can predict and will automatically set the most optimal price for your product at any given time.
Profasee’s Answer To The Pricing Dilemma
Seasons change, demand fluctuates, and the Amazon marketplace evolves every minute. Pricing is dependent on all these changes – although not a lot of Amazon sellers are aware of that. Chad says, “changing your price is the easiest lever you can pull that can have the largest impact on your business.” A minor price change can lead to major profit or loss, depending on your strategy.
That said, manually implementing pricing strategies are not for the faint of heart. That’s why pricing tools were invented. And today, Chad introduces us to Profasee. The ordinary pricing tools’ smarter and cooler brother.
Using Profasee feels like having your own pricing-focused virtual assistant who never sleeps. Profasee is an algorithm-based AI. It monitors the marketplace and analyzes patterns in the data. Then Profasee predicts the optimal price for your product at any given time. This means no more guesswork, no more pricing errors, and no more over-dependency on your competitors’ price points. Now you’ve got an independent pricing strategy without so much as batting an eyelash.
As with any other area in business, we want to ride through changes the best way we can. Using a smart pricing tool like Profasee will not only keep your business stable but also optimize your profits throughout the ride. Try it out and experience the major profit turnaround yourself.
Amy Wees: I’m here with my friend Chad from Profasee. And Chad has created a pretty cool tool around something that all of us struggle with. And that is setting our prices. I have sellers come to me all the time and not only other sellers, but myself as a seller. You wonder like, how do I set my price? When should I change my price? What’s the best price in my market? You know, how do I even keep an eye on it? It’s like a competitor drops their price like, what should I do? You know, so Chad’s developed a pretty cool tool around this, and we’re gonna dig in today and learn all about it.
So welcome, Chad. And please tell everybody a little bit about you.
Chad Rubin: Sure. Hi, everybody. I’m Chad Rubin. I’ve been in the Ecommerce space for the past over 10 years. ecommerce business DTC private label co-founded the PROSPER show. Started a software company called Cubana for multi channel brands and merchants so that last year, so prosper, I believe in 2018. And started prophecy after staring at a tree and trying to fix my ECOM company in just this past December. So in December ’21.
I’m excited to be here, I’m excited to share with everyone how essentially, I’m all about like solving my own problems first. So Cubana, I needed a software to scale to do a multi channel, built that Prosper show, there was no community and now there’s lots of communities, built that as well, with the team. And now building something where it’s very close to my heart. It’s a beautiful, and it’s challenging problem to solve.
Amy: Wow, that’s amazing. I didn’t know you were one of the co founders of the OG prosper, you know, prosper has changed a lot over the years, I really enjoy prosper. So that’s so cool. And, you know, I’ve also heard of Cubana and some of the other tools that you mentioned, projects that you mentioned. And so I mean, how great to be able to interview you about this new project. Obviously, pricing is still a thing. It’s still something that people struggle with. And I’m interested to learn more about, like how and why we automated that. So everyone, as you’re listening, please say hi to us in the chat. We want to hear from you. If you have questions for Chad, as we’re moving through this. You know, absolutely put them in the put them in the chat and, and we will take your questions as we as we go along.
So I guess Chad, my first question for you around pricing is a really general one, like, what factors should people consider when setting their price?
Chad: Yeah, it’s a great question. So I think there’s so many factors on Amazon, right? So there you have your own product listing, you have your own price that you’ve set or you FBA or you not FBA, or you Amazon choice, or you do have a best seller badge, and you have your competitors, the same thing, what’s their BSR? How many reviews they have the quantity and the recency of the reviews? And so there’s all these factors that need to be processed along with, by the way, your own individual conversion rate and your session rate. It’s it’s overload. It’s like over analysis paralysis. And I was doing it manually. And I was going crazy doing it. And then I was like, okay, there has to be a better way. How do I do this at scale? And how do I build a system that identifies patterns in the data to actually monetize pricing, and most brands, by the way, are under monetizing their price. So it’s all about meeting and meeting the most optimal decision with your price at a given time. And so that’s really what we’re doing. And we’re moving away from a static price where you kind of set and forget your price. Most sellers, by the way, never change their price or have anything they change it maybe once a month. But that’s where we’re seeing the data to actually dynamically and automatically changing price to maximize profit without sacrificing BSR.
Amy: Wow. So, you know, you mentioned a few different business models, like resellers, you know, wholesale as far as you know, whether or not you own the buy box, or whether you’re sharing it with someone else. And obviously traditionally, you know, resellers have had to be the most concerned about repricing because, you know, they they really have to it’s a big factor in winning the buy box is having the lowest price and you know, in changing your price to be lower than the last Buy Box price in order to compete and to be cycled through the buy box. But I guess I should ask, you know what business model is most suited to price changing? Are you also talking about private label sellers who own the buy box? Should they consider changing their price?
Chad: So we don’t actually touch anything we don’t We are strictly working with private label sellers, those that live and die by the SERP by the search engine ranking page on Amazon page one. That’s where we spend most of our time we don’t actually work with any resellers or trying to win the buy box or game the buy box. So I think that’s a pretty big differentiator between us and like every other reprice, er out there is that we exclusively work with private label brands, who are trying to optimally make more money at different times of the day without sacrificing BSR. And we’re seeing actually a tremendous, tremendous lift in the cohort of clients that we have on board the system today, we’re seeing on average, a 10, to 12%, lift in profit.
Amy: Wow, 10 to 12% lift in profit by changing their price and staying on top of their price. So I guess I had no idea that you guys were totally suited. This is the first time I’ve ever seen a pricing tool specifically for private label sellers. So this is a whole new world that you’re educating us about. And there must be, you know, a method behind the madness, we’re gonna we’re gonna get into, like, why you created prophecy? And like, what was the data that you found? But in general, how often should private label sellers be changing their price? And why should they change it?
Chad: So I guess if we just zoom out for a second, every major technology company is using algorithms and data science, true AI to optimize every penny of profit. So if you think about Uber surge pricing, you think about Airbnb, smart pricing, even Amazon, by the way, Amazon is changing price two and a half million times a day. So everybody is actually changing price dynamically. The question is, why aren’t brands and there’s a lot of them, there’s two and a half million Amazon sellers in the US marketplace? Why are they why don’t they have access to these tools? And that’s really where I began my premise like in questioning, well, why? Why are people not changing their price? Why or why is pricing have to be static, what if we actually made pricing dynamic, especially in Amazon, which is a is a marketplace, and if you’ve ever checked out on Amazon, your card, you left them in your cart for a day, there’s a price change, and Amazon notifies you and you probably still buy it anyway, Amazon is driven on commodities and is very susceptible to change pricing on amazon.com. And so that’s really where we started focusing our time on Amazon. So there is no like how often it’s actually what is the optimal price, it’s going to maximize your profit without sacrificing BSR. And by the way, it’s not always increasing your price, it could actually be decreasing your price, actually is gonna be the most optimal price point, because essentially, you’re going to generate absolute profit dollars for making your essentially sell more velocity, which is going to offset the lower price that you’ve made.
Amy: Gotcha. Yeah, you know, I have played around with the pricing on some of my own products. And I’ve seen many clients do the same. And it’s really interesting, because sometimes increasing your price, you know, people just assume that decreasing is the best, you know, like, you just decrease your price, you’re gonna make more sales. And we’ve all seen it where you know, you’re gonna run out of stock, and you you increase your price, and you get more sales. And you’re like, Whoa, what happened? So talk to us a little bit about why changing your price causes an increase in sales? And you know, what, that’s what that’s all about, does it have anything to do with the Amazon algorithm? Like, why does changing your price work?
Chad: Well, I mean, it’s the easiest lever you can pull, that can have the largest impact. And so the challenge is that everybody is scared to change their price, or, and I’m not saying that you should be shameful or shamed or guilted. But like, a lot of people do this, right? They just either copy their competitor, or they just guess what the price should be. And they leave it there. And then they forget about it, and they don’t change it. And then they don’t actually analyze the data. So it’s a very, it’s like, literally, it’s your revenue, right? Your revenue is what drives your bottom line profits. And if you don’t actually ever change your revenue profile, you’re not going to actually maximize the bottom line. So most sellers right now, in my opinion, are actually they batting their head against the wall being like, hey, how do I optimize my PPC? How do I adjust my bids so that my a cost is at 10%. But if you think about it, the other side of the eight costs equation is literally your 10% A cos you’re spending $1 To make 10. Well imagine if you were spending $1 To make 12. So now your ad costs rose from 10% to 8.3%. And that’s amazing. That means that your return on adspend goes from 10x to 12x.
Amy: Got it well That’s so interesting. I mean, so you’ve discovered these things, I guess, you know, my next question for you is, you developed a tool to, I guess, tell us about this tool, because it’s not, it’s more than just changing your price. It’s about knowing what the optimal price is. And then also knowing when to change it, and how much to change it by. So talk to us about this tool and what it does and why.
Chad: Yeah, so we have we built AI and I use the word AI, a lot of people say is artificial intelligence, I like to call it authentic intelligence, right, where we actually have a data science team on staff that are building the algorithms behind the scenes. So if you think about it, you look at Instagram, every time that you like something every time you dwell time on a video, Instagram knows that and they know that that it’s a dopamine response. And that you’re going to do more of it. And they’re going to serve you more of that, which increases your time on the platform. So the same way that we’re doing that for pricing, so we take all the cookie crumbs that customers leave, and we analyze them behind the scenes to generate the optimal price. And we do that in two ways. The first thing is we opt we optimize for, for the for demand. So price elasticity, which is the sensitivity of price changes. And then we optimize for the perfect price after doing that. And we’re pulling in a lot of factors. And I can share some of those factors on my screen here. Example of all the things that we’re pulling into the platform, right, so macro factors, a seasonality or holiday holidays, you’re we taking your 18 months historic information, and it’s analyzing and chopping it up into the actual algorithm algorithm itself. We have your sessions, your conversion rate, the number of competitors, we do a reverse asin lookup based on keywords of your competitors. So all of this is flowing into our model.
Amy: Wow. So you’re really kind of looking at the big picture, using AI using big data to crunch the numbers for us so that we don’t have to manually pull up every page, we don’t have to manually pull up every page of our of our product, you know, every page one keyword to see like, Oh, what are the prices on this page, and, you know, what are our competitors doing and how you’ve actually developed a method to get that out there and get it done, which is really, really cool.
Chad: Sorry, keep it easy. It’s like day parting for pricing. So different times of the day, you could have somebody who can have a lot of people that are coming that are window shopping, and maybe by lowering the price, you’ll get higher conversion. Conversely, you might have people with high intent coming to your pages, and they want to convert at certain times of the day. And maybe you’re leaving room on the table of money on the table during that timeframe.
Amy: Wow. So I guess, you know, you’ve brought up all of these really great points about you know, about why to use an automated method and versus like manually changing your price. But how does it work? So can you talk to us a little bit about, you know, if I, let’s say I’m using this tool, and I’m logging in, and I’m figuring this out, like does it make recommendations? Does it automatically change your pricing? Do you set thresholds? Yeah, just a little bit about students? The tool?
Chad: Yeah, so the first thing is they request access center site, right. So we’re still early stage in this and we’re onboarding people slowly to make sure the experience is perfect. So we put in their information. And again, we’re looking for Amazon US brands that are in the marketplace on three P Seller Central that are have consistent stock that are FBA that are higher velocity, so we don’t work with typically anyone who’s like sub a half a million dollars in revenue. It’s not who we’re working with currently today. So they put this information in, we reach back out, we’ve set them we lift the velvet rope, we let them into our platform. So there’s really three things that have to happen. They have to connect their Amazon advertising API through our platform. They connect Seller Central in the in our platform. And they also have to fill out an input sheet that has their cost, and their floor and their max price, their ceiling price. Yeah, they put this all in our system. And before we reprice, or do anything we will ingest, and train our models around your data and give you an analysis of it the money that we expect that you’re leaving, leaving on the table. So right away, we’re just an analyzing, ingesting the data and you’re getting a recommendation from us as how much money are you leaving on the table today and what can we get you by using prophecy? Once you agree on the subset of skews that you want it Give us right we essentially break down your skews into a cohort. And the cohort is we have our experimentation skews. And we have our control our control skews, so they’re broken apart. So we can actually measure performance and measure success. And we work in, in quarterly quarterly periods. So we’ll have a quarter where we are giving you quarterly business reviews or sorry, monthly business reviews, and giving you results we have we have a shared Slack channel, giving you results and showing you how the experiment is running and showing you with real data, what you would have not achieved had you not use prophecy. So I’m really, really excited about what we built. It’s pretty amazing. And we’re helping other Amazon brands flourish, which is probably the most exciting part of my job and what we’re building.
Amy: Wow, that’s really, really cool. I think I’m most excited about what you said about like, the minute you onboard them, you show them how much money they’re leaving on the table. And I think that’s a really aha moment. So my next question for you is, I think I get it, you know, you get you get the floor and ceiling prices, you understand, like, you know, all of that. So once all of that is set up, then it sounds like prophecy automatically changes those prices for you. Does it like send you a record of what was changed that day, or
Chad: we have an audit trail on the platform that shows you what’s changed. But remember, you’re giving us the boundaries, you’re delineating what your floor and your ceiling prices. So you’re letting us now we we conservatively, go up and we aggressively go down. But we do it within the bounds that you’ve given us so that we’re not operating out of school or something that’s not expected for brands?
Amy: Got it? And then I guess, the most important question is, what are the benefits of using this over just another pricing tool, or Amazon’s own Amazon has their own pricing tool? What’s What’s the benefits of doing this?
Chad: Well, I think if you’re just like, there’s too much data for you to ask for a human brain to process all these data inputs. So if you’re doing it manually, the best you can do is create like a very simple rudimentary logic, like if your competitor goes up 5%, that I want to drop my price by 5%. It’s not cranking out and finding patterns in the data, which is really the whole profession around data science. That’s like saying, like, hey, Instagram, we want you to manually select customers, and figure out what we should show them next. And so if Instagram did that, too, they would never scale and you probably would not use Instagram any longer, because you probably wouldn’t get really what motivates you was hitting your dopamine in your brain to hit the next video like button or to continue watching a real? So in that same vein, right? I think, where are we now it is we consume all this data, you don’t have to worry about it. And we’re making the decisions to maximize profit, and we’re showing sellers that they’re leaving a lot of money on the table, and that the algorithm actually gets better the longer you use it. So it gets smarter over time. There’s very few other technologies out there that actually gets smart, smarter and build recognition of patterns over time to actually improve ROI. And to me, that is incredible. So let’s just say we’re delivering you 10% today, and we started learning by the small levers of price changes that we made throughout the day. Instead, six months, we could we could be earning 18% profit dollars on a monthly basis.
Amy: Yeah, that’s, that’s amazing. I mean, I totally get it. And especially, you know, you mentioned you are working with, you’re still in beta, you’re working with those brands that are you said, doing a half a million or more in revenue,
Chad: right? Yeah. And by the way, it’s not just brands, we work with aggregators, we work with agencies. So we’re working with pretty much everybody. Yeah, there’s only a few aggregators are we’re not working with because they’re trying to just build this in house, which I still don’t get right now and how, why that’s even a thing. But we’re essentially giving brands their own outsourced data science team that an aggregator would have. And I think that is the future. The next the next stage I think of Amazon selling. Its its went through this evolution, right, you went from resellers to private label, private label, organically ranking to becoming advertisers. And now I think the next stage in the evolution of the process is going from advertisers and sellers, to the rise of what I call the algorithmic brand. So brands are going to be using data to make decisions for them that are far more efficient and optimal than if they’re just using like human logic and spreadsheets.
Amy: Exactly. And I think that’s where we have to go because the marketplace is getting as a whole, the marketplace is getting so much more reliant on data, and so much smarter. I mean, even if we look at our Amazon auto campaigns, auto campaigns back in the day, people would always say, no manual campaigns are the way to go. And now we’re seeing the algorithm has gotten so good that auto campaigns are outperforming a lot of our manual campaigns. And it’s and people are missing the boat on that all because like data is changing so fast. So I think it’s, it’s really smart and isn’t always the right answer to try to build your own tool, you know, if somebody else is already has the experience, and you know, is going it’s like the key is outsourcing. Right? So I love that Well, I guess we had
Chad: to give you just like I would say like one line of the benefit outside of having to manually do it the true benefit, right is to unlock Hidden Profit, that you weren’t aware that existed in your business. And I think every seller right now is struggling with profit. Right? They’re struggling with PPC, they’re hitting a wall. Manual, not even manually doing but just bidding in general, they’re cutting costs, we have inflation, that’s here, and that state has staying power. And so one small lever of price can go a really long way. And that’s unlocking profit for our merchants and brands.
Amy: Yeah, that’s huge. I loved your analogy of Instagram. And you know, same thing with any of these social media platforms like keeping your attention is their that’s how they make money, right? They keep you on the platform longer on the platform, the more that they learn about you, the more that they can put ads that are right, you know, and this is the same model where you know, the more that somebody is in the prophecy tool, and you can look at the buying behaviors and all of that it’s like just more and more data. And before you know it, you’ve just got it. So streamline that you’re unlocking additional profits for people that
Chad: if if you look at my stream, this is a webinar that I did. And you’ll see here that I’m talking about this rise of the algorithm. I don’t know if you can, can you see my screen right now? Yeah. And right now, this is like sort of the last hope for aggregators, where they need to own data into decisions for their business. And they can meet their EBIT, da forecasts they can meet, they can start forecasting better for demand planning. And you look at what’s happening. This is just one job page of an aggregator right now. And you see, it’s all data science as all AI. Yeah, in order to effectively compete. It’s it comes down to actually using technology in a way that enables you to compete with these large players that have unlimited pockets in the space, and being smarter about it. Right.
Amy: For sure, for sure. Yeah, that makes a lot of sense. And, you know, I think all all of our brands are realizing that they they cannot just sleep on this stuff, right? It’s, you know, everything is changing so quickly, if we just even look at the last year, on Amazon alone, it is really, I mean, and then we think about Walmart and some of the other marketplaces, how fast they’re growing and developing and changing and we just can’t sleep on it. So it’s wonderful. Cool. Amazing. All right. Well, I mean, I guess the last question that we that we have here is, is how do people get in contact with you? I mean, obviously, you’re obviously you have, you know, certain brands that you certain thresholds that you’re working with right now. But how should people follow your story and, and reach out,
Chad: like, check out profasee.com They can reach out on LinkedIn, my personal email chat, a prophecy.com is always available. I’m on Instagram, Facebook, LinkedIn, really like any which way you want to connect with me. I’m available. I’m around. I eat, breathe and sleep this stuff. So excited to share with the world. And if you have questions, reach out.
Amy: Amazing. Okay, wait, I have one more question. Yeah. For those people that are not qualified to work with you yet new brands, people that are just growing their business, what should they consider when manually setting or changing their price?
Chad: So I would create a spreadsheet and you can actually go to prophecy.com. At the bottom, there’s like this little scroller of what I was doing relative to the platform, I can actually share my screen real quick. And down below here, there’s this and so I was tracking. I mean, this is like a rough idea of what I was building manually. But I was tracking on an on a daily basis, right BSR unit sold price revenue costs, my profit. And I started adding other elements conversion rate, your session data, competitors, price, competitors BSR. So if you don’t have a lot of skews, I would recommend just letting the data drive your decision making process. And making small increments, right. I’m not saying for you to go from a $10, garlic press to $100. garlic press right. I’m saying like small levers swing big doors. So you can adjust your price to 2%. One and a half percent 2% 3%. Find the threshold and find where the sweet spot is as optimal in your price that doesn’t actually sacrifice your competitive positioning on Amazon.
Amy: I love it. I think that’s what most of us are, are doing now. But it’s good to see that you have that spreadsheet there of the things that you were tracking and how we can kind of apply some of the same concepts to be awesome on our brands. All right, I think we’ve pretty much covered it. And I’m so excited to get this information out to the world. I think people should know about what people like Chad Rubin are doing in the space. Because it’s it is really important. And we got to stay ahead of the competition. And yeah, take all this stuff into consideration. And I think the biggest eye opening moment for me today has been that you know that something like this even exists, and that it’s really making a difference because I think a lot of times when we think of private label, we don’t think about price changing. So this has been very eye opening today and definitely given me some stuff to work on Chad thanks a lot.
Chad: For thanks for having me on. This has been awesome.
Amy: Awesome. Well, thanks everybody for tuning in. And we will see you guys next time. Have a great rest of your day.