In this episode Callum McKeefery, podcast host and CEO of REVIEWS.io talks to Burc Tanir CEO and Co-Founder of Prisync ( aka 'The E-Commerce Pricing Guy').
In this episode they discuss how Burc built his company and went on to develop the strongest automated competitor price monitoring platform in the industry. They discuss the importance collecting data from pricing automation, of Shopify reviews, competitive pricing strategies, the best way to managing partner referrals, and the future of eCommerce.
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So today I welcome Burc Tanir. Burc is the founder of Prisync. Prisync is predominantly based in Istanbul, but they have several team members dotted around the world, allowing them to offer around the clock support. Prisync, well, I'll let Burc explain what Prisync does and how it works. Burc thank you so much for being on today's episode.
Really appreciate you being here
Burc: yeah, sure. Well, thanks a lot for having me. So like, as you said, I might simply provide some introduction about Prisync, but yeah, firstly, like I said, thanks to you and all your team members, for having me. So, basically, we are specialised in e-commerce pricing as the name might like slightly imply.
We offer, you know, an automated competitor price checker, to e-commerce companies and on top of this let's say competitive pricing intelligence. We also let merchants, to apply dynamic rule-based repricing. So you know, all sides of merchants essentially can use our app to [00:01:00] apply sort of Amazon great pricing optimisation.
So without really hiring all those hundreds of engineers, you know, spending a lot of time of investment, et cetera. So we sort of built whatever Amazon has in-house into a software product. And now offer that all size of merchants from around the world as a software product.
Callum: So obviously Amazon changes their pricing every second of the day.
I don't think most people realise that. Um, but Amazon has like a dynamic pricing model and they changed their pricing depending on, supply, demand and competitor pricing. And is that, essentially what you guys are doing, but doing it for Shopify stores?
Burc: Yeah, correct, essentially that, but, we at the moment particularly focused on quantitative pricing signals.
So not really the supply side of things demand, et cetera, but we particularly help our competitors or our customers to apply competitive, repricing so they can set up rules. For example, in our engines, such as I would like to be [00:02:00] 5% the cheapest among these sort of competitors, as long as I have, obviously also like 10% profit.
So we don't always really let's say, make them reprice their products to be always at the bottom. Uh, but we also like help them to reprice their products contentedly but also profitably by taking the cost of goods sold into consideration
Callum: yeah, that's interesting. That's interesting. I love this space. I love how pricing can affect your sales and if you get your pricing strategy, correct, you can really see your sales take off. I think it's essential what you guys are doing. I've seen the software working and I absolutely love it. I remember the time, many years ago I was running an e-commerce store and, it's very difficult to, to get your pricing, right. We'd literally scrape hundreds of sites a day, hundreds of products a day off several sites and have to manually do the job that you're doing literally in seconds. When did you [00:03:00] start Prisync?
Burc: Yeah, it was actually in 2013, but honestly the software version of the company was launched in 2015, because for about two years, we started up the company back in 2013, but frankly speaking, I was, I was sort of like broke recovering from another failed start-up. So I didn't have any, let's say investment cash, et cetera, in the bank to really fund the early days of product development but I also needed to make some traction, revenue, et cetera. and, after that failed start-up, I, repeatedly wanted to become an entrepreneur and, I simply observed that, many of my e-commerce friends, either working in different companies, e-commerce companies or starting up e-commerce companies were just, as you said, wasting a tonne of time on, monitoring their competitor's prices, copying and pasting all that data into an Excel file.
And, applying, dynamic pricing or maybe automated pricing with the data. So in day one, so back in 2013, we started with the idea [00:04:00] of kind of offering this data collection as a service. So without any automation, et cetera. So I was literally doing this on behalf of our very first clients in a manual way.
So instead of them wasting their time, I was wasting my time obviously in exchange of some revenue. So for about the first two years of the business, we really like heavily bootstrap with that mentality. We've made our early, early customers, early traction. And then we that early traction, we built, the very first prototype, which was then launched in 2015 and the rest is kind of history, uh, which, which brings us today.
Callum: Awesome. So you built basically an MVP, a really manual MVP to
Burc: without building it
Callum: To be honest, that's how, how SAS products probably should be built, because it shows that you've got product market fit, very early on. At what point did you realise you had that product market fit? Was it 2015, when you launched the [00:05:00] second product, when you launched the actual automated product.
Burc: Well, I think around 2013, 2014 one, we noticed that people were making, you know, paying something in exchange of what we offer to them. I think that was kind of, value market fit, not necessarily product market fit, but you know, what we generate as an output was a valuable asset for those companies or it could be sold.
So I noticed that okay I can already sell this, to an obviously limited set of customers in a manual way. So if I built an automation, this actually constraint will be kind of eliminated. So I tell you today, we automated that. So it made things more scalable, et cetera, but the value market fit or maybe product market fit actually were apparent to me like earlier than we launched the software.
Callum: Yeah. How many is in your team at the minute Burc?
Burc: Uh, 50.
Callum: Oh, wow. You you've grown so much over the last few years. What's your main way of attracting new customers to the product? [00:06:00]
Burc: Well, actually we have been blogging. We have been creating content, you know, educative content, mostly like since our inception, I would say so since 2013, basically.
And in that really helped us to build a, I wouldn't hesitate to say that a dominant position in Google, to be honest. So when you, you know, the listeners might even just do that live. So when you type competitor price tracking, I dunno, dynamic pricing software and all those, you know, relevant nice keywords that are generating traffic to your site.
We really are in position one. I'm not saying page one, it's really first positioning Google. So that really drives a lot of like relevant traffic, qualified traffic to our website, which then converts into like free trials, which we offer. So that's, that's the main like driver of demand and obviously, we do a bit of paid advertising again on Google.
So we also sort of pay our Google tax to, you know, get, uh, traffic. Also we do have a small, I would say sales development team. So outbound team who really [00:07:00] targets the really relevant, segment of the market who might really benefit from our software. So we simply let's say identify the merchants who are on Google shopping, because you know, the context of Google shopping is where really competitive pricing matters. So we tried to identify Shopify merchants who are listing their products on Google shopping, and really try to like honestly do kind of cold or kind of lukewarm prospecting to them. If they are interested, we don't offer demos, et cetera. So, yeah, that's, that's how we generate demand as of today.
Callum: So you're a multi-platform app or are you just Shopify?
Burc: We primarily started with Magento. So we already have Magento extensions available, then moved over to Shopify for all the obvious reasons I would say but yeah, at the moment, our, our primary platform focuses Shopify, but we also work with, companies from more than 60 countries. And, you know, we sometimes, work with some, merchants who just simply built their own platforms. So custom built websites, et cetera, can also use [00:08:00] our technology.
Callum: One thing that we were using a lot of is the Shopify apps, here at REVIEWS.io, um, are you guys using those yet? Not Shopify apps Shopify ads?
Burc: I was kind of one of the early adopters of Shopify ads and I really benefited from the early days where CPCs were pretty low. So nowadays that's kind of really a history, but yeah, I have been testing out all the functionalities since probably day one, if not day two, so we still use them, but we kind of stopped doing, I would say broad advertising on that.
So we were, for example, also testing out, just, just to give some examples. As we believe that we offer profit improvements, profit maximisation, we will also bidding on such more generic keywords, but as more and more vendors are claiming to offer profit optimisation, et cetera CPC has just skyrocketed.
So now we only stick around our own domain of like pricing [00:09:00] optimisation our own brand name in some cases, which are also bidded by our competitors, unfortunately, which, which is something that I really don't like.
Callum: Yeah, we have the same issue with competitors bidding on your name within Shopify.
Burc: Yeah, that makes me partially like proud
Callum: Yeah it's recognition
Burc: commercially speaking, not super nice.
Callum: So with all the data you're collecting, I'm just thinking about what you could do with that data outside of what you're currently doing. Are you monitoring inflation and things like that yet because you're collecting so much data, you can actually do so many clever things with it.
Burc: Yeah. At the backyard, we are working on such, I would say projects, but not yeah man honestly . They are not at the very central of the company because I, the way we structured this monitoring aspect was that it was like really on demand. So what I mean is that, for example, if we have this new, let's say Romanian pet food retailers signing up for our software that automatically triggers [00:10:00] the need of monitoring the Romanian pet food products.
So it's not like that we have an available coverage of the Romanian e-commerce market and we offer this readily available coverage to that merchant, but it's mostly on demand, and this sort of makes our data, like somewhat unrepresentative for some markets, because it's kind of like inclined towards the industries of our clients.
It's not a containing a single SKU, but to overcome that we kind of just actually like last quarter built an internal, I would say data editorial team who are actually now creating the meaningful product assortments in some strategically important countries for us. And then we really would like to build this kind of inflation in the syst of the online retail markets
Callum: You've got so much data on so many products that you could essentially predict inflation probably better than the markets.
Burc: So sometimes, we receive some, leads, from companies who just also tested our software like a year ago, two years ago, et [00:11:00] cetera.
And you know, the funny thing is that. Commercially, like, as we find it viable, we keep the data of every single company who sign up for our service, even in the free trial, we don't delete their products with their product URL's, from our database. Just in case if they ever come back just to show off that we kept it.
So one day, when they revisit their platform. They revisit their account. They see that old data. And in most cases nowadays, the last recorded price information is not like from two years ago and when we update the prices they're always like 20%, 50%, 30% increase from two years data. So in a way a pretty, pretty bad sign of inflation in our context.
Callum: Yeah. I think your data's super powerful. And I think, you know, you, you could do some amazing things with it. How many products do you track at the minute? Do you know?
Burc: Well, I think about 28 million, like almost 30 million.
Burc: And multiple times a day by the way, not just [00:12:00] a singular data, singular price points per day, multiple price points per day for about 30 million products.
Callum: Who do you think is doing pricing well? We've spoken about, you know, the Amazon of this world, Amazon obviously has been red hot on doing pricing fluid pricing for a long time.
Burc: Yeah. I think Amazon is needless to say doing a good job, but I often believe that. Even though it's kind of like always in the second position when it comes to online retail mansions, et cetera, I think Walmart is also doing a pretty good job because, they sort of use their pricing competence as a marketing weapon, if you know what I mean?
So they always claim to be offering everyday low pricing instead of of their time, let's say discount period. So one, for example, you would like to shop for something you at least have this image in your mind that, you know, Walmart should be like, offering like good offers. So you know, discounted products, et cetera.
So I think this let's say value proposition of everyday low pricing is the [00:13:00] significantly important strategy when it comes to pricing. So not just actually considering price points pricing only during black Friday, cyber Monday only official holidays, et cetera, but just considering this as a 365 days, let's say strategy.
So Walmart is being a good job at that and I also like some of our clients, for example, we have this Danish customer of ours, which is just run by a single founder and they are doing an amazing job. They are selling sneakers, et cetera. And that guy really relies on automation on every single part of the merchandising yeah.
So for example, he understood the importance of pricing automation in day one. He applied our technology just when I say apply, by the way, I just mean installing it and then just setting it live, not just, you know, terrible, you know, complex integrations. So for example, they are now also doing this in a data driven way.
So as long as you know, not, not necessarily with our software or , as long as you [00:14:00] take this as a, let's say marathon rather than a sprint only taking care of during black Friday, cyber Monday, I think you are in the good direction. As long as you rely on some extent of data, when you are making your, you know, let's say pricing decisions, I think you are in the right journey.
And Walmart is in the journey. And like I said, many, like recently let's say awakened, Shopify merchants are also doing it in that way.
Callum: You know, that when you talk about that Danish site, that is, using your solution and they've used it since day one.
Is that founder, is that their first site, or is this their second site? Are they a second time founder? I'd imagine every second time founders should be, using your solution because they know how important it is. And once you've had a taste of the power of it, I'd imagine, second time founders it's on their checklist.
We've got to have this first day one. So he's not calling it. Was he a first-time founder or second time founder? Do you know? Yeah,
I think he's [00:15:00] an exception in that sense. So I totally agree with you on that, but he's, he's a first time founder, but like I said, he's an exception, but I took to the agree with you on, let's say context that pricing optimisation doesn't necessarily come as a priority for most of the e-commerce companies.
So they, they mostly deal with, I don't know, paid acquisition before really optimising their internal let's say pricing process, et cetera. And this is honestly a mistake because unless you really kind of, let's say polish up your web shop and, ideally optimise your internal engine. Um, if you just pull up the gas without an optimised engine, you use mostly burn out money without really noticing.
And you know, that, that actually second time mansion is just actually recommendation of this. Let's say burnt money smell. I think if you know what I mean? So people don't notice that. Okay. I should add this earlier. Not in their second attack. Maybe two years later, et cetera, they prioritise really optimising their internal mechanics.
Not necessarily just pricing, but also their let's say supply [00:16:00] chain. I didn't know, conversion on their storefront. Like, relying on, I don't know, their community collecting enough reviews to be of trust and so on. So they prioritise this type of stuff, built a basis and then start running let’s say the engine and start not burning money, but just, you know, investing some money on their further growth.
One of the things that I'm looking at at reviews at the minute is a referral program. Have you guys looked at anything like that?
Burc: Yeah, actually I did, but you know, the thing is that, being absolutely Frank, our product is priced mostly at the mid to low, and so we recharge on average, let's say 200, $300 per month. And you know, in total, let's say if, if the customer stays with us late, 30 months or so it makes about $10,000 throughout the lifetime of, a customer. And when you do, let's say a revenue share of, let's say 20%, 25%, it makes about 2000, $2,500.
And when we initially started talking to agencies for a [00:17:00] referral program, that amount didn't really look like a very attractive kickback for agencies, you know, obviously.
Callum: Yeah, that's it. That's the, exactly the same problem. We're having exactly the same,
Burc: Frankly, I also found a solution. So maybe that might be useful for you.
So that's understanding made me, let's say focus more on to the personal side of things. So instead of institutions, let's say instead of agencies, I started to focus more and more to e-commerce professionals and particularly the personas who have been in the e-commerce space as employees of. Let's say online retailers off their countries, et cetera, and then switched to let's say freelance consultancy.
Let's say a carrier. I really started to, by the way, I am spending enough time on this, on a daily basis to recreate such partners like referral partners. I know the way I do it is that I simply go to my LinkedIn sales navigator, sorry for the advertorial. And then I, I simply like filtered on people in those particularly important [00:18:00] countries for us filter titles, et cetera, and then try to connect with people, individuals who would benefit from this significant amount of revenue share, which doesn't look significant to agencies.
So that really changed the game for us and in just March we onboarded like nine partners made seven paid clients from the referrals, even in month one. And they also started to make some, let's say passive income, because we only asked for referral that program. So we don't really ask those partners to do the sales support, et cetera, but we only try to utilise their networks trust and so on.
So, so far so good. But we'll see how the, how the electronic,
yeah, that's, that's similar to the program. We're looking at launching very similar. I find it so difficult with agencies unless you're throwing in. Tens of thousands at them, uh, can be difficult to get that relationship.
So where do you sit within, your space? Is it very competitive? The price comparison market you're in.
Again, [00:19:00] looking, things from a platform agnostic wheel, we are in a wildly competitive IT space because you know, the scraping thing looks kind of doable, from the very first part of things.
So as let's say two developers, three developers, you feel like you can build a prototype. You can start acquiring first 1, 2, 3, 4, 5 clients, but then scaling this to hundreds of clients. And like I said, 30 million products. It's kind of rather difficult. So in that sense, we have a lot of long tail local competitors.
Let's say build a, working solution and solve this. Let's say three of their, locally e-commerce company. So we have plenty of such competitors, which is good because they also educate, you know, customers that aren't the importance of pricing optimisation, et cetera. But in the, in the other.
Co-parent I would say we are kind of one of the leading wonders of, of our game. We obviously have some nice competitors in, you know, Europe in US, but particularly in the Shopify ecosystem, that's kind of where the competition is very, very weak. And that's also one of the reasons why [00:20:00] we report.
You know, focus more and more. Our Shopify, we are one obviously Canadian competitor that has somewhat connection with Shopify team. But other than that, we have like two X more reviews than them. We have two X more install, merchants, et cetera. So I would say. At the moment leading, the Shopify app store with somewhat weak competition.
Callum: That brings me on to a topic that I know this I'll pick the word we're trying to cover. We've just launched a product for Shopify app developers that gives them a free account with REVEWS.io and it allows them to, it brings their reviews in from
Shopify into their REVIEWS.io accounts so they can get the reviews onto their page.
I'd love to, you guys to open up a free account. It's totally free. We're never going to charge for it. It's just kind of for us to try and go deeper into the Shopify app developer ecosystem. So we're giving away a free accounts or app developers. So one of the big things that we know is.
Shopify ranks the apps based on [00:21:00] reviews. That's probably the most important ranking factor. What's your, do you have any advice on how brands should collect more reviews from Shopify
Burc: They use something like momentum of reviews. So let's say dramatic reviews in a certain period of time instead of the total reviews, because we already are trying some competitors, not competitors, but you know, other apps in the broader pricing ecosystem with, let's say 300, 400 reviews.
Whereas we currently have like, I think 76, 77 or so. So we already out rank them because in the last few months, we really started to collect more and more reviews
Callum: So it's review velocity?
Burc: Yeah, exactly. Yeah. That's I think the more important part than the total number of reviews, and I think obviously install counts also matter because there are some probably like Logitech ticks where, you know, app developers are getting, let's say free, even some sort of like shady reviews without requiring any install days, et cetera.
So they are, let's say [00:22:00] 30 reviews, but no installs it's also really smart tech because it's really worthless. I mean, 3d doesn't help you, but still people are doing that. I guess if you, if
Callum: you've received that email, the email, that's
Burc: going round every week saying
Callum: they'll get, they'll get you loads of app reviews.
Burc: Uh, you know, the, the bad thing is that, you know, I get that review actually email that additionally, There is also another email sent, by saying that they can also get your competitor down by writing fake reviews to them, which is, which is actually way worse.
Callum: I've seen that one as well.
Burc: It's terrible.
I think Shopify team is really taking a close eye on that. At least that's what I see on Twitter. That's really a hard problem because those people might really look authentic. They might open up Shopify stores, which really looks like a proper Shopify store and then start writing reviews.
So that's a really hard problem to tackle. But I think, I want to be tackled on sleep.
Callum: I think definitely. , if [00:23:00] anyone from the Shopify team is listening to this podcast, I do have a couple of ways how I think you can identify the fraudsters. You can do some keystroke biometrics. On the, a content box. And you can see whether, whether it's copy and paste the content or whether it's typed and if it's typed, you know, nobody types the same.
So you could use some key stroke biometrics. That's how, Whether that person is the person they're pertaining to be, or whether it's the same person writing multiple reviews. But yeah, that, that definitely is a big problem on Shopify. And I think they are taking it seriously.
So I saw one thing that, that made me think. Today, uh, it was a tweet
About if, if , Elon Musk combine Twitter. Surely apple should buy Shopify. Apparently they've got 209 billion in reserves. And um, why are they not doing that? Do you think Shopify will ever be acquired? Or do you
Burc: think by Google, I guess you think by [00:24:00] Google? I really, I really believe in that.
I believe things will get, it's kind of like a, I don't know, a street plate, a, so Amazon and Shopify are sort of started to compete with each other, but Amazon is obviously a bigger child. So they are kind of like bugging Shopify. Dan probably Google will kind of become friends and, you know, acquire she'll be fine.
And then it will kind of become a better, better competition. That's really what I believe in. And I really believe in the strategic value for Google acquiring Shopify, because they don't really have a similar offering. Like to really set up e-commerce et cetera, and then do the X in the market, which is kind of going more and more towards maybe away from Google.
Like if you have heard about, uh, like results of Google they are reported, let's say decreased sales, et cetera. So
Callum: yeah, across the board,
Burc: um, slow growth. Not obviously not the group was, you know, that's also today's today's context. So slowed growth is a bad [00:25:00] sign, obviously. So probably they might, they might benefit from that.
I really believe in that. Not apple, honestly, I don't expect it, but you never know.
Callum: Well, you know, it just sparks a little bit of interest in me because I didn't think it was a very good fit. I think you're making total sense in Google. I think Google, you know, owning a major e-commerce platform, like Shopify is such an amazing move because they can actually, you know, I don't know whether people would leave though.
I don't know whether it's too much data. People don't like Google having that much data. And I think people would be worried that if Google could see how much you was earning. Would they change their ads accordingly to squeeze you even further?
Burc: and you know, I maybe to go one step further, I also believe that if even if Google doesn't really, you know, acquire a Shopify, I believe Shopify become more of an advertiser, but in the sense that they probably have one of the most relevant, e-commerce [00:26:00] audience without me moving or really showing them. So they say 2 million merchants across the world with their all first party data, email addresses, audience, et cetera. And you can really, you know, match that audience with any, let's say Facebook, Google, et cetera, platform to show ads.
So I think kind of centralising this whole shopper audience. Has a lot of value. Either Shopify might do this themselves. Or like I said, if Google acquires them, Google might really offer, let's say e-commerce audiences, let's say April shoppers, shoe shopper. Yeah. I actually believe that this will come through in a year or so either just independently by Shopify partnering up with Google.
I don't know, Facebook or via an acquisition. If this happens, please share this. I
Callum: will, I will. Burc's called at first. Yeah, we'll definitely get you back on the podcast if that does come true.
Do you, I know you're not meant to do this, but maybe I'm crossing the line here. We might have to cut this bit out, but do you say if one of your competitors [00:27:00] comes in, sorry, one of your customers comes in and says, Hey, my competitor is Amazon.
What's their pricing. Do you go and look at Amazon's pricing? Does your pricing go and look at Amazon's
Burc: pricing? Yeah, we couldn't. We couldn't monitor any pricing online. So as long as there's actually an online listing, which can be accessed by you and me, like are a Google Chrome. And if that's public information, we can also collect data from Amazon.
Callum: You might have this ever loop because Amazon changes their price. So often that every time you go back to it, they're changing their pricing. You're changing. I mean, Amazon changed their price. So we know that and, and that's obviously, I, I think what you're doing is really.
Yeah, you're changing the price up as, as often as you are changing it
Burc: down, I'd imagine more than more than down actually. So about 70% of our automated price changes are price increases because you know, we are also capable of, let's say, noticing and highlighting that our merchants are under-pricing themselves.
Let's say one competitor let's say goes out of stock for a [00:28:00] more competitive offering. Then the cheapest price kind of becomes the second cheapest option, which is maybe higher than our merchants price. So then we actually have time to increase their prices maybe to a point where they are still, let's say 1%, one pounds, $1 cheaper than the second cheapest.
So thankfully they, they make more margins without really damaging their sales volumes, et cetera. And also just to, just to this, let's say close new parts. We also have kind of like small but important functional tests such as limiting the amount of automated price changes recommended. So some merchants might prefer just to apply automated changes if it's significant enough.
So if it's more than 2%, 5%, $10, some merchants don't really like to change their prices three times a day by just 5 cents and 4 cents up and so on. So we also have to avoid that if they like.
Callum: So you put controls in place to avoid the ever changing of the price. Yeah, it is. It's such a fascinating [00:29:00] industry what you guys are in. I think it's brilliant. Almost. It's very, you know, data science.
Burc: I am biased, but I agree. I agree with you.
Callum: Such an interesting space. Thank you so much for being on today's podcast Burc I'm going to wrap things up because we've now had our time.
If you would like to follow Burc, I'm going to drop, his Twitter @ symbol in the notes below, and also definitely give him a follow on LinkedIn. He's very vocal. He posts some really intelligent posts and is well worth a follow but thank you so much for being on today's podcast. And we'll definitely have your back when someone buys Shopify, Google buy Shopify.