Marketecture: Get Smart. Fast.
00:02:56 · Ari Paparo, Sreenath Reddy
[00:02:56] S0: It it is hard running running a retail business, I'll I'll tell you. A lot a lot of different components. So, like, what is example, like, of of an insight that is a common thing? You you said the new budget. Like, how would I figure out, you know, how to spend $250 if I didn't have it yesterday? [00:03:12] S1: Yeah. That's a great great question. I think ultimately, you are trying to figure out what is the most incremental way to deploy those dollars. Right? So figuring out what products are running at an efficiency where I can add more to them. Right? Figure out what campaigns or what keywords. Where would I pull back? Right? If the question is, hey, I need to take money out. Right? So I think, you know, in order to address that question, you need a combination of you need all the underlying data stitched together and available and the data should have meaning and then that data should have a layer of what's called ontologies which is there's a certain hierarchy to advertising accounts. The system should know that and then once you ask the question you go and process by each dimension where is a potential incremental opportunity, how do I divvy up. That's how that will work.
00:03:12 · Sreenath Reddy, Ari Paparo
[00:03:12] S1: Yeah. That's a great great question. I think ultimately, you are trying to figure out what is the most incremental way to deploy those dollars. Right? So figuring out what products are running at an efficiency where I can add more to them. Right? Figure out what campaigns or what keywords. Where would I pull back? Right? If the question is, hey, I need to take money out. Right? So I think, you know, in order to address that question, you need a combination of you need all the underlying data stitched together and available and the data should have meaning and then that data should have a layer of what's called ontologies which is there's a certain hierarchy to advertising accounts. The system should know that and then once you ask the question you go and process by each dimension where is a potential incremental opportunity, how do I divvy up. That's how that will work. [00:04:05] S0: Right. Right. So you might be looking at things like your inventory and your margin and, you know, where you're not selling as much as you'd like and what the top sellers are and all those sort of things. So it's a mixture of availability, advertising stuff. And then your system, Intentwise, is... Can be used for analytics, but it also could be used to actually run new ads or to change settings and things like that.
00:04:05 · Ari Paparo, Sreenath Reddy
[00:04:05] S0: Right. Right. So you might be looking at things like your inventory and your margin and, you know, where you're not selling as much as you'd like and what the top sellers are and all those sort of things. So it's a mixture of availability, advertising stuff. And then your system, Intentwise, is... Can be used for analytics, but it also could be used to actually run new ads or to change settings and things like that. [00:04:25] S1: Correct. And in fact, like, they go hand in hand. Right? So our observation is, like, 70 to 75% of a ad manager's time actually goes into analysis. Yeah. Right. That's a lot. Right. Yeah. They can't really be so especially in a marketplace world. Right? It looks like you have experience from like the Google and Meta world. The marketplace world is a little different, right? [00:04:50] S0: Right. [00:04:51] S1: Where ads are influenced by so many other factors like content, pricing, do you own the buy box or not, inventory, so on and so forth. And that leads to a lot more time being spent on analyzing what's going on because there's a lot more drivers. So to us, edge and analytics are not really separate, but they evolve as two separate stacks pre Gen AI, but Gen AI is converging them together which is super exciting by the way. Yeah. I bet. So so yes, advertising and analytics
00:04:51 · Sreenath Reddy, Ari Paparo
[00:04:51] S1: Where ads are influenced by so many other factors like content, pricing, do you own the buy box or not, inventory, so on and so forth. And that leads to a lot more time being spent on analyzing what's going on because there's a lot more drivers. So to us, edge and analytics are not really separate, but they evolve as two separate stacks pre Gen AI, but Gen AI is converging them together which is super exciting by the way. Yeah. I bet. So so yes, advertising and analytics [00:05:24] S0: combined. So yeah, so let's talk about AI because it's obvious use case for AI. And, also, you'd recently done some case studies and integrations with the Amazon MCP server that we wanted to talk about. So take me through what are your clients? What did Amazon announce? What did you... What was your integration like? And then what are clients doing with this stuff? [00:05:43] S1: Yeah. So I think there's a few different things. Right? So when it comes to ad management, obviously, Amazon has sponsored ads, which is ad search for open search and then display advertising. Right? So Amazon opened up MCP capabilities several months back around just ad management, creating campaigns [00:06:02] S0: Right. [00:06:03] S1: Optimizing campaigns, so on and so forth. We are fairly tightly integrated into that. And so we went from being a read only MCP where people could analyze, build dashboards, and maybe automate some workflows to, oh, now I can take action too. Right? [00:06:17] S0: Right. Right.
00:06:17 · Ari Paparo, Sreenath Reddy
[00:06:17] S0: Right. Right. [00:06:17] S1: So the the use case I just talked about earlier, which is, like, classic because inventory management is often done separately by maybe a separate team and a separate function from the one that runs ads, oftentimes they don't talk to each other. And imagine having and a as the catalogs get large that problem gets more complex. But now you can go ask the analytical question, hey, what are my products where I don't have enough weeks of cover? And by the way, where am I spending ad dollars? And then I can turn around and say, go for the ads on those products. Right there. Yeah. That's an example. That's an example. So that's that's one part. Right? The other part is Amazon launched what's called Amazon Marketing Cloud. Are you familiar with what it is Ari? [00:07:01] S0: Yeah. I think I I think they talked at our last conference but yeah. Okay. [00:07:05] S1: So I mean, you know, you know, for for... If folks are listening to this and don't know what it is, I'll just give you a quick Sure. Fifth... Fifteen second primer, which is if you think about bra... Of a brand and your exposure to shoppers, all the way from an impression to click to conversion and everything in between like add to carts, engagement with the reviews or gift list, every one of those events is now captured within Amazon Marketing Cloud at an individual shopper level. So it's clean room. [00:07:34] S0: Right,
00:07:34 · Ari Paparo, Sreenath Reddy
[00:07:34] S0: Right, [00:07:34] S1: right. So what that makes possible which is not possible otherwise is a deep understanding of shopper journeys including things like lifetime value, repeat purchase behavior, and this ability to create really fine grained fine tuned audiences for your brand. So deep shopper insights and the ability to create audience, that's what AMC is. Yeah, so the other announcement was and historically because it's a clean room, there are some pre built insights and audiences, but to get very specific around use cases that are unique to your brand, you have to know SQL. Have to write SQL statements. [00:08:10] S0: Yeah. Yeah. Sure. And I never... Since AI came around, I I said I will never write SQL again. [00:08:16] S1: But it takes some time for natural language conversion to SQL to be accurate. Right? Like Okay. Yeah. So I think that's the other announcement is around Amazon Marketing Cloud they launched in beta MCP around that too where I can get new insights as well as create audiences just using natural language. I don't need to be a SQL guru to do that. [00:08:35] S0: So do your clients know when they're using, say, the Marketing Cloud versus some of the other APIs, or do they just kind of put in a query like, tell me who's most interested in my product and and you figure it out? [00:08:48] S1: It's a spectrum. Right? Yeah. There are a small minority of clients that know each of the systems very well. Yeah. Okay. Right? [00:08:57] S0: Small minority, yeah.