Hey folks. Welcome back. Today, I am delighted to interview Kaus Manjita. She is an award-winning founder and serial product builder. With over 16 years experience in the tech industry as the current CPO of Get mason.io. Kaus is spearheading the introduction of ai. To stores worldwide with a view to generating sales.
She's also a passionate customer evangelist, so let's listen to see how her AI powered engine works, the logic behind AI and successful use cases of AI live in the e-commerce industry. Kausambi, how are you? I'm super happy and excited to be here today more than anything else, and I'm good too. It's, it's very warm.
I'm in Bangalore right now. It's a little warm, uh, but yeah. But overall, a pretty good day. So it's 2:30 PM Irish time, so it's 7:00 PM with you. Mm-hmm. So, apologies for eating into your evening. Uh, you know, it's a great way to spend your kinda ease into the weekend with a, with a great conversation for It is.
It is, it is. Friday. Zambia, it's great to have you. I have been following your product for a while, and I'd say that you're sitting back with a smile on your face considering that you were thinking of AI before chat G p t was ever, ever launched. So I'm intrigued by what you're going to say. Well, I guess for me for a while it has always been about how do we leverage technology, but to bring something meaningful for someone on the other side who's gonna use that product.
Right. And very early on, my co-founder, um, actually, you know, notice that the kind of solutions I would say that we could add value to in retail, uh, couldn't leverage data, couldn't leverage machine learning, could actually do good with a lot of automation in place. And, uh, a great way to kind of reduce the decision fatigue that brand owners and founders have, and eCommerce managers and marketers have.
Right. And, um, I mean, online it's tons of data. You have to kind of keep looking at it to take decisions on how to, you know, sell to your customer how to increase sell through, but. The, the information's changing every single second. And, uh, AI was a great, I guess, way to automate that decision making, to make decisions in a more intelligent way, uh, without missing out, uh, you know, on data pockets, on patterns with human biases, right?
And, uh, so yeah, so that's how it started. But it was very interesting now that you say Keith, because. Initially we didn't really wanna save AI company. Cause you know, you go out to customer, they don't care like you, you're running a brand, Hey, you use ai, you use whatever. Like, what am I getting out of this?
Right? So that's the question. And for us, we never really wanted to kind of like hype. We learned it the hard way. I'm a second founder. My first startup didn't work out, so learned it the hard way that, you know, no matter how much technology you put at people in the end, they're like, What do I get outta it?
So we kept ai, no code or automation or ML and all of that under the hood because we're like, we help you sell better. Right? But, but it was very interesting that this year as Chad just took over, you know, the world actually, now you have brand owners asking you like, do you guys use it? I be like, Hey, yes, let's explain.
So, yeah, yeah. I do have a little bit of a smile. I, I agree. Yeah. But you mentioned two really important points. I've said this quite a few times. I won't repeat myself in every episode, but the amount of data even that a Side Hustle Shopify store is producing. Mm-hmm. Data in Google Analytics, data in the Shopify dashboard, data across social channels, orders, data, data in your email platform, Clavio or MailChimp, whatever email platform you're using.
I actually think it's become physically impossible for some people to understand all of that data. Would you agree? Yeah. Yeah. It's quite crazy. And then there are signals. Also from what people don't do on your store or what products they're not engaging with or what are, what are those things that people don't wanna do on your good points, on your right?
So, so there's data, there's missing data that's giving you some insights, and then there's data that's giving you insights, right? So, so yeah, absolutely. We, I guess more in retail, but it's true everywhere else, right? I mean, end of the day, all of us are not data scientists. We don't see the art behind the numbers.
Um, and there's a lot of times when we are just lost in number crunching, when actually we should be thinking about what are the insights and now what do I do with the insights, right? Like, what's next? I, it reminds me, Keith, of this like one of my favorite all time movies, finding Nemo. I just can't get over it.
Like, I love that one. And there's this like part at the end when all the little fishies are like in indoor, in their little. Water and they jump out of the aquarium and they're in the open seat, but they're still in their siloed little packets. And they're like all there and they look at each other and they're like, now what?
And I think that's what's, that's what's happening with data. You're looking at all silo data and you're like, now what? So what you need is actually insights and actionable insights, more importantly. So, yeah, I totally agree with it. It's pretty, it's pretty crazy up there. Your, your, your point about what people are not doing is actually interesting.
People, people obsess about this, the products that people purchase and then the experience after in a store, after they make that purchase, getting the order to them as soon as they can, communicating with them. But you just mentioned something really interesting, which I, I, I haven't heard it very often focusing on what people aren't doing.
So if you have a busy e-commerce store and something, a product isn't selling well, maybe. There's some data there that you could actually use to actually maybe not stock that product again. Is that the kind of direction of travel that you're kind of, you're looking at in terms of e-commerce and that people, what people are not doing?
I'll give you another fun example.
Customer calls. I, I love getting into customer calls, by the way. And I think these 17 years have just flown by working in product because it just goes by when you're like talking to people and you're listening to them because there's so many interesting insights that come out if you listen and not talk.
But there's this, uh, team, uh, it's a pretty big brand. I don't wanna name them because I didn't take their permission today, so I, I wasn't aware this conversation will come up, but, They're pretty well known offline brand now, getting online, um, over the last couple of years and, uh, like, like the rest of the world.
And you know, they, they're of course figuring out this whole e-commerce game and, you know, it's very different from running something on Amazon. It gives you your reports and then you have your own D to C store and you are like, wait, I don't just have my D to C score. I have like search and homepage and, you know, PDPs and checkouts and list pages and collection, like there's a bunch happening in there.
So it's not just like a very simple black box anymore. Right? And they have this very interesting nav in your homepage and a bunch of us too. Like you land your, introduce your new customers to your categories or subcategories on a homepage in a very nice and visual way, because they're home and furnishing.
And specifically for them, it's a lot of stainless steel furnishing, right? So one of their subcategories happens to be home letters. And, you know, they have, it's a fast selling, like people love that they're, they're well known in the LA home letter space, but their problem was that nobody clicks on my homepage now.
Like, what's happening? Why are people not clicking on my homepage now? Right. And the interesting thing over there, like, they just ignored it. They're like, you know, they're, they're doing tons of other optimization and we realize, like, over that call, I like, my quick question to them was, How are people searching for your ladders and how do you present them on your homepage and nobody knows what's a three step or a four step ladder?
No, I, I can't visualize the anything outta that. Like even if I have an eight step ladder, like, okay, sure. Like is a five step better. Like, I need to put something in my kitchen. Is five step the one the way to go or it. And so just that fact of people are not clicking on something in the homepage. How are people searching for your ladders?
Right? What are the search terms that are not any. Right. And they changed by the way. They, they analyzed and people think about it as more as kitchen ladders or library ladders or, or you know, like pantry ladders and stuff like that. And they changed their, uh, entire nav, uh, for the ladder category and shoot up.
People are really using and finding the ladders and buying more of it now. So yeah, that's an example of. What's not happening in your store? It's amazing the perception that some business owners have about their client. I often say that emotion takes over. Somebody probably decided that the navigation should be built a certain way when an actual fact it should be built on data, which is, yeah, again, uh, it's all about, I suppose, time to analyze and if you're using Hot Jar time to watch video, you know?
So let's chat about Get Mason with all of your experience. You mentioned 17 years. Eventually you create Get Mason. So for the e-commerce store owner out there, what does get Mason do? Very simple. We are promised and we've learned to distill it over the years. You know, a lot of times in technology we overcome complicate what we do, right?
We talk about headless or composable or we talk about APIs and, I don't know, web books and whatnot. But what, honestly speaking, what we do is very simple. As a brand owner, as a business owner, you need more sales. You need people to shop. You know your products, and we're a shopping engine. We sit on top of whatever store or platform you have, and we help you.
One, understand your customers, the data or lack of it, right? And we give you actionable insights on what to do next. It could be something as simple as changing, for example, uh, you know, your nav or something as complex as, hey, you need to have better frequently bought together algorithm, right? So we give you all these actionable insights within the product and a lot of it is very simple for you to use.
You can just. You can get it out there, uh, some of it might need, you need us to step in and help you out, but in the end, what it does is that it helps you get more people to shop. So our goal is to, you know, connect the brows to my journey today. It's all about how do I better understand my customers and get them to shop more on my stores over the next, you know, five years.
We also see that as we learn, as AI learns more, we are gonna be hopefully, help your customers shop better no matter which channel you are on. It could be Instagram and you know, Facebook or TikTok or even Amazon. But today we're, we are focused on helping you help your customers shop better in your store.
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Get your first month for free by simply replying to your signup. Email zombie. You mentioned headless. Okay. And you also mentioned ai, but is Get Mason is that two different products that do two different things? Can you ex, I suppose, explain the differentiator between the two? Yeah. And. We just have like one simple product.
They're very, it's a platform. So there's the whole shopping engine. It's Mason is a shopping engine. That's it. Now, under the hood, of course, right there are, if you are talking about shopping today, there are different ways that you can get your customers to shop. With you, right? Uh, when it's a new customer, it's a lot about, you know, how can I help you discover products faster?
How can I help you understand why you should buy my product over others that are out there? How can I showcase to you that this is not a, like a brand new brand? There are, they have been, we have had customers before, so we do have best selling products or stuff like that, right? For a returning customer, it can be, Hey, you left something in your card.
Right? Can I drop an offer and maybe, you know, excite you enough to buy this time? Right? Uh, can I show you, not just this specific t-shirt you're looking at, but maybe the trouser and whatever else that goes with it. Like the bundle, right? So, so there, they're different, different kinds of, I guess, micro apps I would call them.
So their entire platform has all these different apps and they're all shopping apps. Uh, they, again, you can, you get access to the entire platform depending on where your customers are not interacting or not shopping or dropping off in your store. Um, you know, bunch of these things get recommended to you and you can use it and, you know, see better returns.
We've seen customers who've got, um, you know, SMB segment actually doubled their revenue in just six weeks, and we've had, of course, more scaled out teams. Who've got 40 to 50% uplift in their total revenue and orders over six months. Right. And ka samie is, is that through something as simple as automated merchandising, or is it when store owners have started to use your product, have they made fundamental changes to the store based on.
The insights that you're giving them or I, is that as a result of simple installs of your app that just begin to work the minute they have enough data gathered? Yeah, that's a great question. And that's where the question that you asked me about, is it what's head, how headless an AI come into the picture.
Right. So it's headless because it actually connects to, let's say you're on top of Shopify, so you know, you just install it and it, it, it's, there you are on top of who or Magenta. It's very easy for you to just get it connected over there. You store maybe your, a lot of your customer behavior data in ga, right?
Yeah. Google Analytics. Yeah. One click you connect it. And so it's not just your orders or your, uh, you know, uh, product data, but also your customer behavior data quickly. One click you're connected. So that's where the headlessness of it comes, is essentially at the, you know, um, uh, under the hood there's.
All these APIs and you can quickly, you know, one click login, one click connect. If you have engineers and you have more complicated systems, you can actually get them to very easily use these APIs and open APIs and disconnect, right? The AI comes in the more important part, I guess the second important, important part, which is one.
All these different signals that you're getting, they need to lead to something, right? So the first question is, what is the decision that I need to take based on, again, all this different data signals that I'm getting? And then can I actually execute the decision? So for example, if I'm seeing that, you know, there's a cohort of customers, Are engaging with a product, uh, but they're kinda like hovering over the price and they're not buying it and they're dropping off.
Take, uh, keeping the margins in, in course UHC margin your product, dropping a 10. You know, get them to buy. So that decision making is also something that the AI helps. That the AI does, right? So you depending, so, cause you actually have a solution for that, don't you? You, you have a price drop app that has the ability to drop the price based on that interaction.
Isn't that right? Absolutely. You nailed it. And so that's, that's definitely one of the most, you know, it's a very recent drop, but we see like great results with customers and there's a lot of, of course, decision making based on. Different signals. And again, price drop is the interesting thing that I find about the Price Drop app and how we built out the Garth behind it, is that sometimes it's also about the intent, right?
Right. Where if it's a heavy weekday, no matter how much of impulse and like I'm dropping the, you are in the middle of a workday right there, it's more about trying to, um, make you understand why you should buy it remaining top of mind, right? So it's actually all these behavioral, uh, you know, insights.
The engine has been able to look at over the past couple of weeks and do better and better decision making. So yeah, price drop is one of the examples. So a bunch of these like sales, uh, engines, pricing engine, dynamic pricing engine, all of that of course also come into picture and the data that you're using for that.
Let's say we have a Shopify store that's doing a half a million dollars. The chances are that store has, you know, 15 to up to 25 apps, and we always recommend that people don't install apps unless they're absolutely really, really required. But are you plugged into as many of those apps as possible? Like are you plugged into their analytics account?
Are you plugged into their Klaviyo account? Like what is the source of your data besides obviously the Shopify api, all of the Shopify information, are you plugged into all of those other external sources for your AI engine then to make better decisions? Because obviously, The more data you have access to, the more data you have access to, the more sense that price drop suggestion will make.
Yeah. And, and, and yes, we do. We can, as I said, it's headless so we can, but also, I'll also step back and remember I mentioned we help our customers, our merchants understand that customers better, right? And one of a bunch of our discovery and engagement related apps actually come into, so there's like quizzes, there's, you know, product finders, there's your welcome incentive.
All of those, uh, you know, engagement or discovery apps also form a very integral part of understanding. So it's zero party data. So yes, the, the information that you're, there's third party data. There's first party data, which is essentially what's happening when you're stored, but there's also zero party data that's you are creating when you are deploying some of these, uh, you know, product finders or quizzes or stuff like that.
And you're getting to understand your customer even more deeply. The beauty is that today you might be doing that, maybe you have a spin wheel, right? But you're not doing anything with that data. You're just collecting a phone number, right? Yeah. But imagine if you could utilize that information, like what did, how did the people react?
Did the person click on a, uh, you know, uh, you know, something versus something else that was there on the spin the wheel. So all that nudges and information that you get, now imagine if you can package that and use it for. Or you can use it for a price stop. It just becomes such a more connected, better ecosystem where you're selling across your funnel better.
So we, you know, of course we connect with Clavio or Google Analytics as I mentioned, or your store in fact, any kind of CDP that you might be using for little bit of scaled out teams. Of course, they ha use their own CDPs and we, you know, as I said, we're headless, so you can connect it to the cdp, but you can also generate a lot of zero party data.
So customer signs up that you're given the dashboard. So are they given the option? Do you alert them to say, here's maybe a frequently bought together bundle that might work better for this particular product, and do you give them the option to automatically push it or do you send them an email to say, here's some new suggestions?
How does the, what is the customer experience from the dashboard point of view as to as to utilizing all of the decisions that. You can potentially make and potentially push? That's a great question. And you know what? That's also something that we learned over these last few years is on one side, I guess it's, it's human behavior When you're first interacting with something new, right?
It's something that you have newly encountered. You want to understand, you wanna feel a little bit more sense of control. And what we've seen is that usually, you know, our new customers, our new merchants, right, they definitely want to have a little bit more control. Over the system, which means that, you know, I want to know when you know, a price drop will be activated.
I wanna know when to activate a sale. Like questions like that, right? So we have full control. You can literally do bunch of these manually. Recommendations will come to you purely on you, whether you wanna go live with it or not. But what we have also seen is that as they continue to use it and they see the value and they trust the system more, and that's human behavior again.
Um, we have had requests where, hey, I don't wanna take this decision anymore. I know that decision's good. And so we also, that's where our shopping engine, I guess the pure, pure engine starts coming in. You just switch it on and you don't have to worry about it because it'll do, of course, based on your.
Scope, like you have to set your margins. That's very important. You don't want, you know, your cogs to be impacted. So you do wanna set like boundary conditions like that, but once you trust the system, it can actually run on its own too. Great stuff. Great stuff. This, this is a great conversation. Is there anything that you want to say that you haven't said?
Any particular area or any particular, actually you, you've made me think about it and goes back to, You know, this conversation I was having with our, with our team last week, one of our a, as I said, I, I kind of managed the product team, right? And a bunch of product and product marketing and all of that worked very closely with me.
And, you know, one of our sales team members actually was asking like, why do we keep saying that, Hey, first we help you understand your customers and then sell. Like, why, why is that core so important? Right? Can I ask a question then? So, Kabi, is it correct to say then that your service involves a consultative sale?
Like you're helping the customer get to know their own customers, but you have to get to know the customer before your solution makes sense? That's actually a good question, and it's not necessary. Because what we have seen, of course initially, yes. Right? Because three years back when we started, um, when we first launched a version of our app on the Shopify store, we are learning with our customers.
We are learning a lot from them. Right? But the beauty of. You know, the digital world is that, and especially when you add AI into the loop, the beauty is that the ai, the system and the engine starts learning too. So what we've, that outta the or Shopify customer actually just installs the product. On their store.
Right? The first thing that happens is that the system knows, hey, this is a fashion. It's about doing this much of orders maybe, and seeing these drops in the funnel. You know, like people are probably bouncing off the homepage and I understand. Over these last three years I've seen that when something like this happens, these sort of playbooks and apps really help, right?
So you can start seeing, you know, the uplift and the impact and the ROI of having a shopping engine with you on your side from day one. But the shopping engine, of course, keeps getting smarter because it's your own shopping engine. And so over time it keeps getting smarter and helps you do even better.
But yes, like, you know, it doesn't need to be that on day one there's has to be a, like a ton of analysis before you can even find value. Yeah, yeah. Um, there's a lot of learning that this AI bring. I love the fact that it's an application that that helps improve store sales. There's a only a small minority of apps that can actually stand over that, you know, at Zabi.
It's been an absolute pleasure talking to you. I really, really like the product. We'll put all of the links to your good self in the show notes and listen. Thank you very, very much for your time. Thank you for having me, and I look forward to coming back again. Thanks for listening. All of our episodes are available on Spotify, iTunes, and Google Podcasts.
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