The D2Z Podcast

AI Pricing Optimization to Increase Conversion & Profits - 130

• Brandon Amoroso

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In this episode of The D2Z Podcast, Brandon Amoroso interviews Noam Szpiro, co-founder and CEO of Monocle, an AI-powered incentive platform for e-commerce brands.

What if you could revolutionize your e-commerce brand's promotional strategy with the power of AI? Join us as we uncover the secrets behind Monocle's groundbreaking incentive platform with Noam Sphero, the visionary co-founder and CEO. From his beginnings in the Israeli Navy to his pivotal role in Silicon Valley, Noam's journey is nothing short of inspiring. At Lyft and Instacart, he discovered the art of optimizing promotions through machine learning and causal inference. Now, he's focused on helping e-commerce brands grow sustainably, ditching traditional discount methods for AI-driven incentives that preserve brand integrity.

Prepare to have your perspective on e-commerce promotions challenged and transformed. Noam shares how Monocle is educating brands to rethink their promotional spending, offering smarter alternatives that integrate seamlessly with existing platforms like Klaviyo. We delve into the strategic decision to specialize in a niche, addressing specific pain points before considering broader expansions. This approach not only meets immediate needs but also positions Monocle as a leader in AI-driven promotional optimization. Tune in for insights that could redefine your approach to e-commerce marketing and set your brand on a path to sustainable growth.

Here's what you'll learn:
📈 Understanding customer behavior is crucial for effective promotions.
💰 Promotions can significantly drive customer engagement and retention.
📦 It's important to validate business ideas before launching.
💸 E-commerce brands often lack awareness of their promotional spending.
🚀 Future expansion should focus on comprehensive promotional solutions.
💼 Finding the right co-founder can impact business dynamics.
🤖 Integrating with existing tools can ease customer onboarding.

Timestamps:
00:00 Introduction to AI-Powered Incentives
02:31 Noam's Journey: From Ride-Sharing to E-Commerce
05:59 Understanding Promotions and Customer Behavior
10:10 Building Monocle: Lessons from Previous Ventures
14:05 Navigating the E-Commerce Landscape
18:06 Customer Education and Market Fit
22:01 Future Expansion and Integration Strategies

Noam Szpiro:
LinkedIn - https://www.linkedin.com/in/noamszpiro/
Monocle - https://usemonocle.com/

Brandon Amoroso:
LinkedIn - https://www.linkedin.com/in/brandonamoroso/
Web - https://brandonamoroso.com/
Instagram - https://www.instagram.com/bamoroso11/
X - https://twitter.com/AmorosoBrandon
Scalis.ai - https://scalis.ai/

Speaker 1:

Hey everyone, thanks for tuning in to D2Z, a podcast about using the Gen Z mindset to grow your business. I'm Gen Z entrepreneur, brandon Amoroso, founder and president of retention as a service agency Electric, as well as the co-founder of Scaleless, and today I'm talking with Noam Sphero, who's the co-founder and CEO at Monocle, which is an AI powered incentive platform that generates profits for high growth e-com brands. Thanks for coming on the showcom brands. Thanks for coming on the show. Of course, thanks for having me. So, before we dive into the world of AI-powered incentives, can you give everybody a quick background on yourself and sort of your founding journey here?

Speaker 2:

Yeah, happy to. So I'm from Israel, originally Went to the Navy there a really long time ago, then studied computer science in Cambridge in England. After that I decided to move to the Valley, kind of worked on for a few startups there, eventually started my own company in the ride sharing industry. I thought it was a good idea at the time to compete with Uber and Lyft Turns out it's not a very good idea. So about a year later or so I ended up getting acquired by Lyft. So I joined the Lyft team there, worked a little bit on a few different products there, but most of my time there was around passenger growth and a lot of what we did there was around promotion optimizations basically. So that's maybe where you can see the theme of the conversation of where we'll go, but at a high level.

Speaker 2:

What we found at Lyft was promotions are super valuable for people and if you're using it right, it's a great tool for growth. And so what we did initially was we said, hey, let's give everyone a coupon who hasn't taken a ride in the last few weeks and let's see what happens. Ends up being super profitable. People come back when you give them discounts and take more rides, but eventually they stopped using the service. So what we really wanted to find out was how do we target the right people to give them discounts, not only the people who will just come back and use the coupon, but ones that will use the coupon and then stay on and ones that will otherwise not use the service, basically. So really trying to find out, dissect those people who are very promo sensitive and the ones that we can make them change their behavior essentially. And so that's where we started investing a lot of effort into this and we built a sophisticated system around machine learning that really uses what we call causal inference, so really investigating the cause and effect of promotions for different individuals and then only targeting those people who have a very large effect, essentially. So you don't want to give a coupon to someone who will take a ride anyway and will use the coupon. You want to give it to people who are unlikely to take a ride unless you give them that coupon.

Speaker 2:

And so when we started using causal inference, we saw massive gains and we basically increased the ROI by about 50%. So with the same budget, we were able to get 50% more rides. Essentially so super successful ended up doing that same thing over for the driver side of the business, thinking about it more generally, around uh incentives and not necessarily promotion. So, uh, for drivers we have similar stuff where you know we might give uh a bonus if they've taken five rides in a row, something like that. Uh, so use the same technology over there. Uh, after lyft ended up joining Instacart. So we worked at Instacart for a few years. I was a director of engineering there working on conversion optimizations, basket size optimization, so kind of similar stuff on a really large scale essentially. And then about close to two years, I almost started Monaco, raised a large seed round at the beginning of last year and then off to the races after that.

Speaker 1:

Got it. That's cool. That's something that was a thought in our mind at the agency for a while. When, know, when you're sending out all these campaigns and promotions and they're sort of just you know one-to-many versus being one-to-one, and you know there's definitely a lot of brands that we've worked with in the past who would then become over-reliant upon you know, discounting and you know sort of hurting the, you know the brand reputation along the way and getting customers too comfortable with waiting for that code versus you know them shopping and if they had not gotten that, that code, um. So how did you, how did you sort of transition into um, the, the Shopify ecosystem from, uh, you know, ride sharing and then into into Instacart and then and then e-com?

Speaker 2:

Yeah. So I think, uh, in general, you know, general, I think there's a lot of similarities between Lyft, instacart and generally the Shopify ecosystem. They're all about basically getting people to place that order book, that ride, essentially. So it's fairly similar in that sense. The difference is it's a little bit of a different scale for, uh, a lyft, uh, uber, all the ride sharing uh and services like that, and then instacart as well, uh, so for e-commerce it's a little bit different.

Speaker 2:

Um, it's the industry, and in shopify is interesting because you can really get to massive scale with almost no, no team or maybe a 10-person team. Sometimes you see brands do over 100 million in sales basically, and so obviously that would never happen for a startup like Lyft and Instacart, things like that. They would need much bigger teams. And so when I was looking at that, I saw, okay, well, uber, lyft, all those they have massive teams around them that help them really figure out what is the right pricing, how do you do discounts, all of that. So lots of talent there around machine learning, data scientists, people like that, and you know, for the Shopify ecosystem, you know it's really hard to do it yourself, really hard to do it yourself.

Speaker 2:

Basically, you have to either hire a bunch of people, invest a lot of time, or you maybe have some tools out there today, but they're not very advanced in terms of that and typically the tools in Shopify, or a lot of the tools in Shopify, are basically tools.

Speaker 2:

They're not really working on optimizations or basically going beyond that, just providing tools but actually implementing the solution essentially. So that's where I realized, okay, there's a little bit of a gap here where, with my background and the people I've worked with in the past, I think we can build something that could help tailor it for basically all the Shopify stores that are out there and would save them the effort of actually building these things themselves, but at a high level. Yeah, we looked at how people do promotions on Shopify and you saw there are a lot of similarities, like initially they're just doing simple segmentation, like you mentioned, essentially. But I saw that there's a lot of opportunities for improvements here, because it's mostly around maybe simple A-B tests, things like that, but nothing around personalizing discounts, really all the way to the end, essentially.

Speaker 1:

Are you able to utilize the data from multiple brands? For, let's say, one customer shops at five of the companies that are using Monocle and then you have a six company that starts using Monocle and I go to that website and am also a customer of that. Is it possible to leverage the way that I respond and engage with the discounts from the other five to inform sort of the sixth, or is it much? Is it more siloed, you know, for that particular brand and that particular customer?

Speaker 2:

Yeah, so. So right now it is siloed Basically. So each brand I kind of we look at them as a unique brand and figure out what, uh, how do promotions work for them? And you know there's some. I agree that there's some notion around people being a little bit more price sensitive and maybe some people just generally need coupons to purchase. Uh, what we found is that it's not entirely true. Basically so the way people actually interact is more it depends on the interaction with the actual brand. Essentially. So there are some purchases, uh, that you know you just want to make that purchase and you're not waiting for a coupon because you need this item, basically, and it doesn't really matter if you're generally you like receiving discounts or not. What really matters is okay, how did you interact with the brand? How many times have you visited the site? And through that we typically have a much stronger signal on how are you likely to purchase basically, or how likely is it that a coupon will change your behavior.

Speaker 2:

Essentially, so we don't really do any cross-store matching. What we do do is try to understand what are the type of features. So for each user we build some sort of profile. Essentially that's unique to the brand. But what we find is those features tend to be fairly similar between the brands.

Speaker 2:

So, for example, one that we typically look at that's a very strong indicator is how long your session has been. So if you have a really short session, promotion is unlikely to change your behavior, basically, if you have a really long session, conversely, you might have already made up your mind and a discount is not going to change that, basically. So that's also not an ideal person to give a discount to. And the people in the middle that are kind of on the fence still, those are the type of people that you typically want to give discounts to, and so we find that that is fairly similar between brands. But what is the definition of a short session or long session is vastly different between brands, and that's why we don't have, right now at least, a model that basically looks at everything and decides for every user. Let's do this, but rather for this specific brand. Here's what it looks like and here's how it might be best to represent these sessions, basically, Got it.

Speaker 1:

Okay, that makes sense. On the side of actually building and growing the business, are there any sort of lessons or sort of gotchas that you took from the first business that you started that you kept in mind when going at it for a second round here?

Speaker 2:

Yeah, good question. Yeah, I think two things. One is just the people you work with is super important. I think hiring a right team is critical for the business. Finding the right co-founder is also super important.

Speaker 2:

I personally, like I know a lot of people, tend to say you know, co-founders need to complement each other. Make sure you have complementary skills. I don't necessarily agree with that statement. What I think is you need to find someone that you just like to work with, even if your skills are fairly similar. That's okay.

Speaker 2:

The goal of having co-founders at least you can bounce ideas off each other, talk to them. Sometimes things don't go right and your co-founder is the one that's helping you, maybe pulling you up or telling you OK, here's maybe one other way we can look at this situation or save this deal, or anything like that. So I think people you get along with and people it's fun to work with I think is more important than complementary skills. Basically that's my opinion with. I think is more important than complimentary skills. Basically that's my opinion. And then it is fun to just you know, have, make sure you have a good team that you're excited to go to work with. And then we we tend to work in in person. So it just the energy is different and making sure you have those people who are who like that energy of bouncing ideas off each other, building things really quickly. I think that's super important.

Speaker 2:

So that's in terms of people learned uh over time. Is that? Uh? Before I started monica, I said, okay, I'm not gonna start another business until I know. Okay, this is uh a business that I know can explode, basically. And so before we uh we hired anyone, before we wrote any line of code, uh, basically we talked to, I want to say like 50 brands or so and kind of interviewed them around how they do promotions, all that stuff Different segments, also in the e-commerce industry and then, right before we even had a product, we started doing some manual analysis for them. And then, once we did that and we saw that they were excited by it, that's when I realized, okay, this is a good area to dive into and take this thing to the next level. So I do think, before jumping into things, making sure you're in the right industry with the right idea, basically.

Speaker 1:

Yeah, not building a ton and then launching it without having the initial customer discovery. Yeah, exactly, that makes sense. Interesting on the co-founder note, though, I think people probably do prioritize some things beyond just the basics. Beyond just like the basics. Like, do you actually even like this person and you know having to go to work with them every day and having some sort of camaraderie, whether you're complimentary or not, you know, do you actually want to show up and be a partner with that person?

Speaker 2:

Yeah, and like, wherever you end up choosing, you're gonna it's not always going to be easy Like you're always gonna, or you're inevitably going to argue about certain things. And I think the important thing is that you know you respect each other and you know you can argue a little bit, but then you take that to the next level, basically, and solve that argument and and and build on top of that, rather than you know, maybe not talk to each other than for the next few weeks, yeah, how do you think about breaking into you?

Speaker 1:

know for the next uh, a few weeks. Basically, yeah, how do you think about breaking into uh, you know the ecosystem with a with a product that you know there's not a lot out there when it comes to what, what you're doing, whereas you know if you had launched a reviews app I don't know in like 2019 or 2020? You know there's, like you know, hundreds of review apps that are out there, but brands are also more familiar with what that is. How have you gone about the customer education and then followed through with actually getting them to sign on?

Speaker 2:

Yeah, good question. In general, I really like there's a product market fit framework that Sequoia published a while back. So the way they think about it is they split it into three areas. There's the hair on fire, hard fact and future vision. Hair on fire is kind of what you described as like the reviews app, so something everybody knows they need. It's a matter of building the best solution out there. Essentially, hard fact is basically what we're doing where people don't know there's an alternative to the status quo, essentially, so the biggest competitor we have is just using what you're doing today and sticking with it. This future vision is, you know, maybe you know, building flying cars or things like that, essentially, uh, or a store that, uh, you know markets itself, or something along those lines uh so with you know, with our area, our, our specific uh product market, fit it.

Speaker 2:

It is a little. The challenges are a little bit different. So it's not about, you know, talking to a customer and then convincing them, hey, like you should move off this platform and onto our platform, but rather, you know, when we talk to brands, it's about more education. So, basically understanding, okay, how much money have you spent on promotions in the last year? Most brands don't really know because in a way, it doesn't really matter, because they just look at the bottom line basically. And when you're thinking about promotion, sometimes you don't even see it in your P&L, basically because it might just be the actual cost is baked into the actual discount is baked into that cost. So there's a little bit more education around that. So there's less competition for us.

Speaker 2:

When we talk to brands, we have to tell them hey, there's a huge opportunity here and we have to sell them on the vision a little bit, that promotions can just be something that an AI can manage on its own and optimize and adapt over time to trends and seasonality, all that stuff basically. But the idea is that in this specific area, once you've done enough education in the market, then, because there's no competition, you become a leader really easily. So right now we're, I think, in the beginning of people understanding, okay, there are a lot of AI tools out there and brands are now looking to expand into that and figure out, okay, where should they add AI or machine learning into their store? And this is kind of one area that we see that brands Kind of always think about what are the different ways to innovate in that?

Speaker 1:

area essentially.

Speaker 2:

So it's interesting. The other thing I would say that we're doing that helps is basically, we didn't want to get people to migrate onto our platform, so one thing we could have done, which was easy. So, in general, when we look about, when we think about promotions, we split it into a few different categories, but one category is basically the delivery mechanism. So how are you actually informing the user that they have a discount on their account? So that's the delivery mechanism.

Speaker 2:

We decided not to touch that delivery mechanism because there's just so much competition there and there's so many great tools out there essentially that do this. So for pop-ups, it might be Amp, it might be Klaviyo, postscript all of those brands, all of those products have great pop-ups, basically, and there's no reason why we should build another one. That is more or less the same. Rather, what we decided is we're just going to plug into those tools, essentially, and then we're going to basically essentially be powering the pop-up, or the brains behind the scenes of the sides. When is the right time to show a pop-up, what should the discount be? All that stuff basically. And the advantage there is that now, when we are onboarding a new brand, we don't need them to off-board from Klaviyo onto us. They just keep the same UI elements that they have there and then we just plug into that to really decide when and what to show basically to the user.

Speaker 1:

Got it. No, that makes a lot of sense and probably makes the process significantly easier, not having to deal with migrating anybody off of anything. But I know there's a lot of companies that are out there right now that are building product that already exists, but they're getting wider with sort of what they're offering is, as it feels like a lot of a lot of businesses are started doing. It was going for that sort of like HubSpot approach, where there's a bunch of different products underneath sort of one platform. What are your thoughts around going that route versus being a very specific sort of Swiss Army knife for a particular use case, which is effectively I guess you guys are doing with when it comes to like the, the pricing optimization, because I don't think it works all the time, because you can't do that with like reviews, because reviews have now been commoditized. So how do you, how do you think about that?

Speaker 2:

yeah, um, yeah. So I think when you're starting a company, uh, in my opinion, the best way to get it off the ground is to be that Swiss army knife or not exactly the Swiss army knife, but really finding that one specific pain point and really solving that really well.

Speaker 2:

Basically, and that's a really great way in where you know, you're talking about a pain point that brands have, you're solving it, they're coming to you for that specific thing and then ultimately you want to expand and then provide more solutions to other pain points in that same specific area. Now I think Yotpo is a great example of a lot of different products in different kind of in different categories. So reviews is a little bit different than you know, sending emails, for example, or sending SMS but it makes sense to expand into that because that's another product that brands really want For us. I don't like we'll never expand into reviews, for example, but for us, expanding into different areas that have promotions in them is very natural for us, for example. So right now we typically control I wanna say with some brands about 50% of the promotional spend. So that's through pop-ups, emails, on-site deciding when people should receive discounts. Basically, we sometimes trigger when a user should receive a discount in a win-back campaign, things like that, and that all accounts for about 50% of the promotions. We want to also tackle the other 50%, so that a lot of times is through strikethroughs, so just items that are on sale, for example, or bundle offers, things like that. So those are areas that we haven't gotten into and that's kind of the area that we want to expand to.

Speaker 2:

I know, once you have control over all the promotional spend, that's where there are great interaction effects, where you know, if you know this item is on sale and someone has it on their cart, maybe you can give them an even larger discount, for example. Or maybe there's a bundle offer for three items. The user has two of them. Maybe you can give them an additional discount and tell them, hey, like, add this item and get this additional offer. But once everything is connected, it's much easier to play around with it.

Speaker 2:

For example, black Friday is coming up right now. It's a little tricky to get to a point where everything is synced, so a lot of brands just decide to shut down their emails, maybe turn on something new. The idea is, with Monocle, in the future, you're just going to be able to say, well, I just want to give 40% off for everyone, and then you'll do it from one platform and we'll update everything. So all of your email marketing platforms, all of the pop-ups, everything on the site basically will update everything. So all of your email marketing platforms, all of the pop-ups, everything on the site, basically.

Speaker 1:

So you don't need to go and manage everything independently, essentially Got it. That makes sense. Well, I really appreciate you taking the time and coming on. I think it's a huge need and it makes a ton of sense. So definitely a lot of value that e-com brands can get out of their customers and I think everything's moving towards that. You know one-to-one personalization versus the general, like you know, segmentation and whatnot. But before we, before we wrap up, can you let everybody know where they can, you know, find you guys online and how they can connect with you if they, if they want to learn more?

Speaker 2:

yeah, sure, so our site is. Use monoclecom. There's a book demo link there. Feel free to fill it out and we'll reach out Awesome.

Speaker 1:

Well, again, I really appreciate you taking the time for everybody listening. As always, this is Brandon Amoroso. You can find me at brandonamorosocom or scalistai. Thanks for listening and we'll see you next time.

Speaker 2:

Thanks, Brandon.