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Maximize Your Profits Using Amazon Data Analytics with Sreenath Reddy · Selling on Giants: The eCommerce Marketplace Podcast

• 0:08
  SPEAKER_03: Welcome to another episode of Selling on Giants, the podcast where we explore the cutting-edge strategies to help e-commerce brands succeed on major marketplaces.
• 0:18
  SPEAKER_03: Today we're diving into the world of Amazon data analytics with Srinath Rede, the founder and CEO of IntentWise.
• 0:26
  SPEAKER_03: IntentWise is an advertising optimization and analytics platform for brands and agencies operating on Amazon and Walmart.
• 0:34
  SPEAKER_03: Srinath brings over 20 years of experience in digital advertising and data analytics, making him the perfect guest to guide us through how brands and agencies can maximize their growth by leveraging the wealth of data that Amazon provides.
• 0:48
  SPEAKER_03: In this episode, we'll explore the specific types of data Amazon is now sharing, how to effectively utilize this data to optimize your business strategies, and the evolving role of AI and PPC optimization.
• 1:01
  SPEAKER_03: We'll also discuss common challenges brands face when dealing with data and how to overcome them.
• 1:07
  SPEAKER_03: By the end of this episode, you'll have actionable insights to take your Amazon strategy to the next level.
• 1:13
  SPEAKER_03: Now let's dive into these key takeaways with Serenath Reedy.
• 1:17
  SPEAKER_03: In this episode of Selling on Giants, I sat down with Serenath Reedy, CEO of IntentWise, to dive deep in how sellers can harness the power of Amazon data analytics to fuel their growth.
• 1:29
  SPEAKER_03: We explored essential strategies that every seller should consider when working with data.
• 1:35
  SPEAKER_03: Here are some of my key takeaways from my interview with Serenath.
• 1:39
  SPEAKER_03: First, we discussed the importance of clearly defining the critical questions that your data needs to answer.
• 1:47
  SPEAKER_03: This approach helps focus your efforts on what truly impacts your business.
• 1:51
  SPEAKER_03: Serenath emphasized the necessity of owning your data, ensuring that it's collected, organized, and accessible in a way that enables you to make informed decisions without dependency on external providers.
• 2:07
  SPEAKER_03: We also covered the value of integrating advertising and retail data to gain a comprehensive view of product performance as well as the growing role of AI in analyzing unstructured data like customer reviews and marketing trends.
• 2:24
  SPEAKER_03: For any seller looking to stay competitive, understanding and utilizing these data strategies is no longer optional.
• 2:31
  SPEAKER_03: It's essential.
• 2:32
  SPEAKER_03: Now let's dive into my full conversation with Srinath so we can uncover how you can apply these insights to your business.
• 2:39
  SPEAKER_03: Let's dive in.
• 2:40
  SPEAKER_03: Hey everybody, welcome to the podcast.
• 2:42
  SPEAKER_03: I'm excited to have Srinath here with IntentWise, and we are going to dive into some data analytics.
• 2:47
  SPEAKER_03: But before we get started, Srinath, you've been in the digital advertising and data analytics space for over two decades.
• 2:54
  SPEAKER_03: How has the landscape of e-commerce data evolved over the years?
• 2:59
  SPEAKER_03: And what pivotal moments have shaped your approach to leveraging data for business growth?
• 3:05
  SPEAKER_00: Great question.
• 3:06
  SPEAKER_00: You know, just a little bit of personal background.
• 3:08
  SPEAKER_00: So before starting the intern wise business, I used to work at a large consumer internet company called Orbits, the online travel company.
• 3:16
  SPEAKER_00: So I was super deep in the weeds on Google Ads, you know.
• 3:21
  SPEAKER_00: And my my own personal entry into the Amazon ecosystem was a little bit accidental.
• 3:26
  SPEAKER_00: But the fundamental shift we uh I already went through switching from Google advertising to Amazon advertising is the fact that on Amazon, you know um, once you someone clicks on an ad, the experience that the shopper has is not controlled by the brand too much.
• 3:47
  SPEAKER_00: I mean, yes, you control the content, but that PDP page is all controlled by Amazon.
• 3:51
  SPEAKER_00: As simple as that sounds, that fundamental difference has huge implications on how you manage ads.
• 3:57
  SPEAKER_00: In the case of Google, you click on an ad, you bring them to a landing page that you controlled entirely.
• 4:02
  SPEAKER_00: You could experiment with it, you could do a bunch of stuff with it, but in the Amazon universe, that's not the case.
• 4:08
  SPEAKER_00: And that also leads to my next point, which is ads or ad optimization in the world of Amazon, is like searching for a key under a lamp, you know.
• 4:19
  SPEAKER_00: Uh, you know, there's just a lot more outside ads that impacts ads, like retail factors like pricing, inventory, so on and so forth.
• 4:29
  SPEAKER_00: So I think it's retail media as we call it, which is on uh Amazon ads, Walmart ads.
• 4:34
  SPEAKER_00: I mean, that's all new, but the dynamic is fundamentally very different from any of us that have been in online advertising prior to retail media taking flight, you know?
• 4:45
  SPEAKER_03: Yeah, that's beautiful too.
• 4:46
  SPEAKER_03: And it's amazing how many uh advertising and data people I meet that were on Google first and then somehow ended over on Amazon.
• 4:54
  SPEAKER_03: It's almost like Google's the gateway drug to all us e-commerce and Amazon guys.
• 4:59
  SPEAKER_03: What when did you make the transition and what what kind of led to the trend?
• 5:03
  SPEAKER_03: Like, how did you get into Amazon?
• 5:04
  SPEAKER_03: Did you have a client, a brand?
• 5:06
  SPEAKER_03: I mean, being in travel seems a lot different than than doing e-commerce.
• 5:09
  SPEAKER_00: So I so I was in the in my previous job for about 10 years, running our data teams and then running our online marketing teams, and it's a public company.
• 5:17
  SPEAKER_00: So I have a lot of battle scars from doing those two things and answering my CEO and questions prior to earnings calls.
• 5:25
  SPEAKER_00: So the the that's the background I came from.
• 5:28
  SPEAKER_00: Uh and then I wanted to be an entrepreneur.
• 5:30
  SPEAKER_00: I left that job.
• 5:31
  SPEAKER_00: Um, first I you know tried my hand at doing something in the travel space, it didn't go too far.
• 5:37
  SPEAKER_00: Um because I knew Google Ads really well, uh, me and my co-founder actually launched a Google Ads focused agency, but for companies that have sizable spends helping with bid optimization and a few other things.
• 5:52
  SPEAKER_00: So, like a tech-enabled agency is what we were.
• 5:55
  SPEAKER_00: Yes, uh, but all along looking for a product opportunity to double down on because we were at our hearts product people, right?
• 6:02
  SPEAKER_00: We are not like, you know, we we always thought about how to build products, how to build tech platforms, not necessarily services, which are also great businesses, is just not where our minds went.
• 6:12
  SPEAKER_01: Yeah.
• 6:13
  SPEAKER_00: And then I ran into a customer I was having lunch with her at a suburb in Chicago.
• 6:18
  SPEAKER_00: I used to live in Chicago, by the way.
• 6:19
  SPEAKER_00: I'd moved to San Diego three years ago.
• 6:21
  SPEAKER_00: But uh, and she she was like at the end of the conversation like, Srinath, I like you all.
• 6:26
  SPEAKER_00: Uh, but you know what?
• 6:28
  SPEAKER_00: I'm moving all my money to Amazon ads.
• 6:30
  SPEAKER_00: Wow.
• 6:30
  SPEAKER_00: And my reaction, this is late 2017.
• 6:34
  SPEAKER_00: My reaction was, what?
• 6:35
  SPEAKER_00: Amazon does ads?
• 6:39
  SPEAKER_00: So, so anyway, I shy, I I that was our first customer.
• 6:43
  SPEAKER_00: They're still a customer of ours.
• 6:44
  SPEAKER_03: Wow.
• 6:45
  SPEAKER_00: Um, yeah, I mean, uh, I shadowed, I went to their offices, shadowed their teams a little bit, and understood that some dynamics, a lot of dynamics were very similar to the Google uh ads, dynamic search ads, but there is a number of them that were different.
• 6:59
  SPEAKER_00: So uh we were excited about Amazon's own growth and the problems that had to be solved, and that's when we actually completely pivoted, gave away a bunch of business.
• 7:10
  SPEAKER_00: Uh, you know, it was a hard call to make, but it's really hard to build a product company and a services company at the same time.
• 7:16
  SPEAKER_00: So we made those hard calls back in 2018.
• 7:18
  SPEAKER_03: That's amazing.
• 7:19
  SPEAKER_03: And what a great, and I I bet, especially early on, like the insights from the service side must have really informed your strategy and like what actually drives value uh to your clients on the product side.
• 7:32
  SPEAKER_03: Um, last question before we jump into the main topic.
• 7:35
  SPEAKER_03: What was what was the hardest part about the transition outside of giving away some business, moving from something service-oriented to something product-oriented?
• 7:44
  SPEAKER_00: Yeah, no, it's um, you know, we've we we are a bootstrap business.
• 7:49
  SPEAKER_00: We still we even though we're a SaaS platform now, you we're probably unique in the sense that we have still not raised institutional capital.
• 7:57
  SPEAKER_00: We have raised some friends and family capital five years ago.
• 8:00
  SPEAKER_00: So when you have a reasonable services business, that's good cash flow, right?
• 8:05
  SPEAKER_00: Yeah, and we are sitting at a point in time saying, we are gonna give up this cash flow.
• 8:11
  SPEAKER_00: I'm gonna take some help from friends and family to go build this product, and we're making this choice because we are making this gut call that uh the time and attention that we can give this product is the most valuable asset we have, and we're gonna do whatever it takes to preserve that.
• 8:30
  SPEAKER_00: So that was a hard call.
• 8:32
  SPEAKER_00: It was a gut call, right?
• 8:33
  SPEAKER_00: Like, is that right or wrong?
• 8:34
  SPEAKER_00: I I don't think so, but that was a hard call to make to kind of give away some like cash coming in, stop doing that, make that switch.
• 8:43
  SPEAKER_00: Uh that call was just tough, but we had to make it, and I'm glad we did.
• 8:48
  SPEAKER_03: Yeah, it seems like you guys are in a really great position.
• 8:50
  SPEAKER_03: And uh, I have a business coach that I meet with regularly, and uh like a typical entrepreneur where I have a ton of ideas and uh I can't pursue them all.
• 8:58
  SPEAKER_03: And he's always like, if you can't put 80% of your time towards something, don't pursue it because it's it's almost like the pumpkin plan.
• 9:05
  SPEAKER_03: If you ever read Michael Mikalowitz, you start getting all these little pumpkins, it's gonna take away from your big idea, your main pumpkin, your main business.
• 9:12
  SPEAKER_03: So it sounds like you lose that and the proof is in the pudding because uh Intenwise really is a great software, and you're doing some really great work on the data analytics side.
• 9:23
  SPEAKER_03: And on that note, let's jump into the main topic.
• 9:25
  SPEAKER_03: So maximize your growth using Amazon data analytics.
• 9:29
  SPEAKER_03: So, first and foremost, walk us through specifically like what types of data Amazon is sharing uh that we're able to use as sellers or agencies.
• 9:38
  SPEAKER_00: Yeah.
• 9:38
  SPEAKER_00: Uh great uh great uh great question.
• 9:41
  SPEAKER_00: I think um I'll I'll start with the with the point that we really have seen an inflection in the last two years, right?
• 9:50
  SPEAKER_00: So if I were to dial back, let's say three years, what you're looking at was you got sponsored ads data, maybe some DSP data DSP was a little bit earlier, three years ago.
• 10:00
  SPEAKER_00: And then you had you remember the word MWS API to get seller central stuff.
• 10:05
  SPEAKER_00: And by the way, there's no API for vendor central stuff, right?
• 10:08
  SPEAKER_00: And there is no stream, there is no Amazon market, none of that, right?
• 10:12
  SPEAKER_00: But over the last two and a half to two to two and a half years, what has happened is Amazon, uh there is more data from ads coming our way.
• 10:20
  SPEAKER_00: There is more data from seller central now, which is called selling partner API.
• 10:24
  SPEAKER_00: Seller Central and vendor central that is coming our way, they've actually made the API infrastructure a lot more robust.
• 10:31
  SPEAKER_00: I don't know if you remember this, but getting access to MWS accounts or different sellers, what a pain it used to be.
• 10:37
  SPEAKER_00: Oh yeah.
• 10:38
  SPEAKER_00: So not only is the ability to access these APIs become easy, each of these APIs now share a ton of data as well.
• 10:45
  SPEAKER_00: Now, just to put a frame on the question you asked, like what are the types of data?
• 10:50
  SPEAKER_00: You've got the regular data sets from uh sponsored ads, DSP, uh seller central, vendor central.
• 10:56
  SPEAKER_00: That's that's let's call it like operational data, like what happened, right?
• 11:01
  SPEAKER_00: Um batch mode, you get daily grain of data.
• 11:04
  SPEAKER_00: Typically, you're pulling it once a day if you're doing any reporting.
• 11:07
  SPEAKER_00: So that's one set of data.
• 11:08
  SPEAKER_00: And then Amazon started to share more and more real-time data.
• 11:11
  SPEAKER_00: So marketing stream for ad data, yeah, rapid retail analytics for retail sales data, real-time data, and especially, I mean, a lot of your audience may be 3P sellers, but like if you were a if you if you're a one P uh uh brand listening to this conversation, there were no APIs.
• 11:28
  SPEAKER_00: Your ad data in the vendor central or your sales data in the vendor central console is often three, four days late.
• 11:35
  SPEAKER_01: Yeah.
• 11:35
  SPEAKER_00: But guess what?
• 11:36
  SPEAKER_00: With rapid retail analytics, you can actually get hourly data.
• 11:38
  SPEAKER_00: So there's a lot of hourly data coming our way.
• 11:42
  SPEAKER_00: And then with Amazon Marketing Cloud, this is like unique shopper level granular data where like each shopper is assigned a user ID, and you can actually see what actions they are taking and measure performance and efficiency of ads and a number of other things in ways that you just couldn't do before.
• 12:01
  SPEAKER_00: It's a clean room, it's a different kind of data set.
• 12:04
  SPEAKER_00: How you approach it is different.
• 12:05
  SPEAKER_00: So I'd say regular operational data, hourly data, shopper level uh data from Amazon Marketing Cloud.
• 12:13
  SPEAKER_00: Uh, and then of course, around all this in the ecosystem, there's a lot more competitive insights we are able to get, not necessarily from Amazon, but whether it's external platforms or companies like us.
• 12:24
  SPEAKER_00: And you put these pieces together, uh, there's a lot of rich data that didn't exist two to two and a half years ago, and the accessibility is a whole lot better.
• 12:33
  SPEAKER_03: That's amazing.
• 12:34
  SPEAKER_03: And you know, we can see it on our end as an agency too.
• 12:37
  SPEAKER_03: And I would say our biggest pet peeve, you're right, uh, three years ago, and what we heard a lot from uh investors and brands who did advertise, for example, it's like, what's the lifetime value?
• 12:48
  SPEAKER_03: If we were doing something upper or mid-funnel, it's like, how can we measure that?
• 12:53
  SPEAKER_03: Because it's not being showcased in ROAS.
• 12:55
  SPEAKER_03: And Amazon was always kind of a black box.
• 12:58
  SPEAKER_03: It was like, you know, the flywheel works, this is what we're seeing, but we didn't have all those connections.
• 13:04
  SPEAKER_03: So it's great that Amazon's listening to its agencies and it's listening to its software partners, and we're able to kind of put this data together to build the story of like what's actually going on with your investments, well, whether it's operationally or from an advertising perspective.
• 13:21
  SPEAKER_03: And on that note, can you tell us a little bit more about you know, diving into some of the analytics?
• 13:26
  SPEAKER_03: So let's let's play a game like role-playing if I'm if I'm a mid-sized brand and I'm looking to leverage data to make informed decisions about my competition, like what would that look like on the platform?
• 13:39
  SPEAKER_03: And what do we have access to now that maybe we didn't have access to uh three years ago?
• 13:43
  SPEAKER_00: Yeah, great, great question.
• 13:45
  SPEAKER_00: Um I think let me frame it this way, right?
• 13:50
  SPEAKER_00: And I and this is one of the things we'll talk about further in this conversation, I think, is if I'm a brand or a seller, the number one question I'd ask myself is do I have a solid list of 10 questions that I want to have answers for that could really help me manage my business and drive growth?
• 14:10
  SPEAKER_00: That's the number one question I have for every seller or brand, right?
• 14:14
  SPEAKER_00: And if you don't, I'm not talking about a three-month exercise to build one.
• 14:18
  SPEAKER_00: Grab the three to four people who are in the weeds of your business, grab some coffee or pizza, sit around for 30, 45 minutes, frame the 10 10 questions that you really want to know.
• 14:29
  SPEAKER_00: And they and I have a frame for those the categories of questions, and I put them in three buckets.
• 14:34
  SPEAKER_02: Sure.
• 14:35
  SPEAKER_00: Uh basic operational questions.
• 14:38
  SPEAKER_00: Do I know what is happening to the business?
• 14:40
  SPEAKER_00: And let me peel give you some examples.
• 14:42
  SPEAKER_00: What's going on with my ad spend and ACOS?
• 14:46
  SPEAKER_00: That's not difficult.
• 14:47
  SPEAKER_00: I can go into the ad console and see it if I have to, but that's a basic question.
• 14:52
  SPEAKER_00: Do you have a clean view of tacos down to the product level?
• 14:55
  SPEAKER_00: Now you're getting a little bit more complex, right?
• 14:58
  SPEAKER_00: Uh a lot of people have it, you can close it together, whatnot, but that's like step two, right?
• 15:03
  SPEAKER_00: But you are bringing advertising data and retail data together at a product level.
• 15:09
  SPEAKER_00: You've got to do that to get to the tacos view, right?
• 15:12
  SPEAKER_00: Let's take it one step further.
• 15:14
  SPEAKER_00: Do I have a view of profitability by week, by product, or by day by product?
• 15:21
  SPEAKER_00: One notch up, right?
• 15:23
  SPEAKER_00: Yeah, so we can bundle all these into what's called operational.
• 15:26
  SPEAKER_00: What's my profit looking like?
• 15:28
  SPEAKER_00: What's my sales?
• 15:29
  SPEAKER_00: What is my efficiency?
• 15:30
  SPEAKER_00: A cost and tacos, just basic operational things, just watching what happened, right?
• 15:35
  SPEAKER_00: That's those are the operational questions.
• 15:37
  SPEAKER_03: Those are amazing.
• 15:38
  SPEAKER_03: I can't tell you how many brands I work with and some pretty large established brands that don't have a pulse on profitability on the product level.
• 15:47
  SPEAKER_03: So, you know, what you're saying, people are like may sound crazy, like you don't know your profitability, they don't, and they're not measuring it accurately.
• 15:54
  SPEAKER_03: So uh let's dive in the bucket two.
• 15:57
  SPEAKER_00: Yeah, but and and may perhaps I'll add a couple more examples.
• 15:59
  SPEAKER_00: The most common things that come up in bucket one, right?
• 16:04
  SPEAKER_00: Does do my inventory levels align with ad spend?
• 16:09
  SPEAKER_00: Right?
• 16:09
  SPEAKER_00: Like and oftentimes they don't.
• 16:12
  SPEAKER_00: Like, why are you accelerating sell through of a product that you're gonna run out of inventory on by pumping ads on it, right?
• 16:18
  SPEAKER_00: Like, so uh so we can go on and on.
• 16:20
  SPEAKER_00: Um that's bucket one, which is operational, right?
• 16:23
  SPEAKER_00: The second bucket, which is diagnostic, and if there's agencies on the call, uh, I find I you know, I've had many conversations, and you are an agency owner, so you can correct me if I'm wrong here, but like 60 to 70 percent of an agency team's time goes into analysis, yeah.
• 16:44
  SPEAKER_00: Right, whether you're auditing a prospect's account or you're troubleshooting a performance on an existing account who's saying, dude, why is my guys, why is my ACOS up 20%?
• 16:54
  SPEAKER_00: Right, you you're doing that, or maybe strategic, right?
• 16:57
  SPEAKER_00: But you're spending a lot of time doing diagnostics, yeah.
• 17:01
  SPEAKER_00: And my point with back to the question about those 10 questions is uh what are the questions you want to you want to have good answers for very quickly?
• 17:11
  SPEAKER_00: Why is my ACOS up?
• 17:12
  SPEAKER_00: And I have a standard rule on this in less than 15 minutes, whether you're a brand or an agency, you should at least be able to isolate the key drivers of ACOS optics.
• 17:22
  SPEAKER_00: 15 minutes, but that requires you to have brought together some data and have a process around it.
• 17:28
  SPEAKER_00: But that's the question I would say uh I would have under diagnostics, right?
• 17:32
  SPEAKER_00: ACOS changing, sales changing, year over year, numbers changing, prime day of this year not looking as good as prime day of last year.
• 17:40
  SPEAKER_00: Why?
• 17:40
  SPEAKER_00: Why why, right?
• 17:42
  SPEAKER_00: That's diagnostics.
• 17:43
  SPEAKER_00: Yeah, and the strategic bucket is things like who do you think your competition is?
• 17:49
  SPEAKER_00: And this is one of the questions most brands do not give me a good answer because in their minds, uh, competition is the four or five brand brands they know, right?
• 18:00
  SPEAKER_00: May share self-space with, but you know this on Amazon.
• 18:04
  SPEAKER_00: Competition is not at a brand level, competition is at a individual product level, right?
• 18:09
  SPEAKER_00: So, um, who is my competition?
• 18:12
  SPEAKER_00: Who should I be product targeting in terms of competition?
• 18:15
  SPEAKER_00: What is my share of voice?
• 18:17
  SPEAKER_00: How do I expand?
• 18:18
  SPEAKER_00: Those are all strategic questions.
• 18:19
  SPEAKER_00: Do I have real differentiation against the ICP I'm going after?
• 18:23
  SPEAKER_00: Should I price higher price?
• 18:25
  SPEAKER_00: These are all strategic questions.
• 18:26
  SPEAKER_00: So operational diagnostic, strategic.
• 18:29
  SPEAKER_00: And I'm not talking about 100 questions, like come up with 10.
• 18:32
  SPEAKER_03: Yeah.
• 18:33
  SPEAKER_03: And those are really great questions.
• 18:34
  SPEAKER_03: And too, uh, it's so funny you mentioned the uh the competition on the product level.
• 18:39
  SPEAKER_03: It's so I can't tell you how many brands we work with that maybe they sell a lower price point item, or they're just a small business and they're like, who are your top competitors?
• 18:48
  SPEAKER_03: They're like Nivea or Instapot.
• 18:50
  SPEAKER_03: That's like, no, no, those are not your you're not competing against them.
• 18:54
  SPEAKER_03: But obviously being able to use that data for storytelling is a big part of it.
• 18:59
  SPEAKER_03: And I I tell my my employees that work for me, like storytelling is a big part of your job.
• 19:05
  SPEAKER_03: Uh, and to your point, because uh most of our job is reporting and analytics.
• 19:10
  SPEAKER_03: It's you know, probably 20 to 30 percent execution, and the rest of it is like, what were the effects?
• 19:15
  SPEAKER_03: Where diagnosing and doing the strategy is is a huge part of what we do on the advertising side or on the agency side, excuse me.
• 19:24
  SPEAKER_03: Um, but on that note, so these these three buckets of questions, like how um, so I'm coming to work with you, we're we're an agency or a brand.
• 19:34
  SPEAKER_03: Yeah after we uncover this, like what are the next steps now?
• 19:38
  SPEAKER_03: So I have my 10 questions that align.
• 19:40
  SPEAKER_03: It's it's operation, it's uh it's diagnostic, and it's strategy.
• 19:45
  SPEAKER_03: What what's next?
• 19:46
  SPEAKER_00: Yeah, so uh I'm I'm I'm gonna switch to data language here, right?
• 19:50
  SPEAKER_00: So you've got your questions, right?
• 19:52
  SPEAKER_00: Like and by the way, like we've been doing this long enough where like we can suggest some of those questions too, right?
• 19:58
  SPEAKER_00: But we can accelerate that process.
• 20:00
  SPEAKER_00: You got a list of 10 questions.
• 20:02
  SPEAKER_00: The next step is to map it back to where does the underlying data reside so that we can bring it together and answer the question, right?
• 20:11
  SPEAKER_00: So basically data sources.
• 20:13
  SPEAKER_00: Can I get to all these questions by just getting my sponsor ads and DSP data and seller central data, put it together, I'm done.
• 20:20
  SPEAKER_00: Uh, or do we need more than that?
• 20:22
  SPEAKER_00: Right.
• 20:22
  SPEAKER_00: So just establishing where do you need to get the data from?
• 20:25
  SPEAKER_00: Um, and by the way, someone like us, we have automatic connections to all these data sources.
• 20:29
  SPEAKER_00: So uh once you establish that, then you just have to agree on okay, what visual makes sense, right?
• 20:36
  SPEAKER_00: Hey, I want ACOS and tacos trended on a line chart on a weekly basis.
• 20:42
  SPEAKER_00: That's the precise definition you can get to, right?
• 20:44
  SPEAKER_00: Uh, or I want a table where each row represents an ASIN, and I want ad spend, total sales, all the fees, profits, uh, and uh let's call it instead of row as or acos, let's call it profit over advertising spend, maybe POAS is enumerative.
• 21:00
  SPEAKER_00: Whatever these columns are.
• 21:02
  SPEAKER_00: Come to conclusions on visualizations on each of these questions so that the report or a dashboard can just be built out quickly.
• 21:11
  SPEAKER_00: In fact, the hard part is just framing up the visual that you require.
• 21:15
  SPEAKER_00: And by the way, what's gonna happen is some of these questions you want answers on a daily basis, weekly basis, monthly basis, repeated stuff, right?
• 21:24
  SPEAKER_00: You want to automate.
• 21:26
  SPEAKER_00: But some of these things are ad hoc, where the real important thing is to have access to data in a way that you can actually analyze.
• 21:33
  SPEAKER_00: Yeah.
• 21:34
  SPEAKER_00: Right.
• 21:34
  SPEAKER_00: Um, so uh uh uh operationalized automated uh views, which are reports, right?
• 21:41
  SPEAKER_00: Uh, and then uh the ability to answer ad hoc questions.
• 21:44
  SPEAKER_00: Now, to answer ad hoc questions, depending on you know what type of brand or agencies you are, um you want to own your data.
• 21:53
  SPEAKER_00: Yeah, uh what does ownership of data mean?
• 21:57
  SPEAKER_00: Uh, I know we'll talk about pitfall.
• 22:00
  SPEAKER_00: False data, but I'll just state one already.
• 22:02
  SPEAKER_00: So many brands today work with service pro service providers where if they decide to change that service provider, they lose the data.
• 22:14
  SPEAKER_00: You have to take ownership of your data.
• 22:17
  SPEAKER_00: Now, ownership may mean your data is sitting somewhere in a database, let's say an internalized platform database that you're paying some sort of a fee for because you own it.
• 22:27
  SPEAKER_00: It doesn't go anywhere, it's right there for you.
• 22:29
  SPEAKER_00: You can access it, whether it's through SQL or you connect your Excel spreadsheet to it.
• 22:34
  SPEAKER_00: Or if you are, as we we work some of the larger sellers and agencies that have their own data infrastructure, like a database and things like that, we can you know get all that data piped into your data store so that A, you own it, B, you can do ad hoc analysis as needed.
• 22:50
  SPEAKER_00: Because a lot of times what happens with data is you look at a report and it raises three more questions.
• 22:56
  SPEAKER_03: Yeah.
• 22:56
  SPEAKER_00: Yeah.
• 22:57
  SPEAKER_00: So, but you want to be able to answer those two quickly.
• 23:00
  SPEAKER_03: Yeah.
• 23:00
  SPEAKER_03: So true.
• 23:02
  SPEAKER_03: And what I hear too is so owning your data is absolutely important.
• 23:05
  SPEAKER_03: And when we take over from accounts from an agency perspective, sometimes it's painful if they've been using DSP, for example, and then the previous agency isn't going to share that.
• 23:15
  SPEAKER_03: And we're like, okay, yeah, we got to start from scratch.
• 23:18
  SPEAKER_03: You know, the reports you're sharing aren't really that helpful, um, which is really interesting.
• 23:23
  SPEAKER_03: And the visualization, I find that that is a big piece of evidence missed.
• 23:28
  SPEAKER_03: It's one thing to say, you know, we're seeing year-over-year growth or we're seeing this growth, but to actually see it mapped out on a chart uh will actually ease the minds of some of the brands.
• 23:39
  SPEAKER_03: Uh, I can think of several times where we're growing, we're seeing growth, and until they see a picture and they're like, oh, we are growing.
• 23:46
  SPEAKER_03: This is great.
• 23:47
  SPEAKER_03: It goes a long way.
• 23:48
  SPEAKER_03: How much emphasis do you put on visualization of data when you're working with brands or agencies?
• 23:54
  SPEAKER_03: Like, do you think every brand should be trying to visualize every aspect, or like, are there specific components that have a bigger impact?
• 24:02
  SPEAKER_00: Yeah, no, a great question.
• 24:04
  SPEAKER_00: I think that I have a point of view on uh visualization and reporting because like I've been doing this for 15 years.
• 24:13
  SPEAKER_00: Uh for any age, a brand or an agency that is continuing to ask interesting questions, uh, there's an expiry to each report because all of a sudden you have at a level of sophistication that the previous report is not answering, and you want to go to the next thing.
• 24:29
  SPEAKER_00: So, I to me, the collection of visuals and reports is a living, breathing thing, and you have got to evolve.
• 24:35
  SPEAKER_00: That evolution will happen because you are asking more interesting questions, or because Amazon just introduced a new campaign type which is not factored in, and then you have to.
• 24:44
  SPEAKER_00: So, I think we have to treat this as it's not a one and done.
• 24:48
  SPEAKER_00: Uh, you you put in some level of upfront work, but then after that, you uh and I don't think you should boil the ocean.
• 24:56
  SPEAKER_00: The last thing you want to do is run a one-year project that doesn't see the uh light at the end of the tunnel anytime soon, and that that's just a bad idea.
• 25:04
  SPEAKER_00: I'm talking about like small incremental executions and just continue to get better every week, every month, right?
• 25:09
  SPEAKER_00: So it's not one and done, but I can I go right back to those questions uh we were talking about.
• 25:14
  SPEAKER_00: Yeah, frame and it may not even be 10 questions.
• 25:17
  SPEAKER_00: Let's start with five questions, right?
• 25:19
  SPEAKER_00: I want to know my profitability, uh uh tacos, acos, and down to the product level.
• 25:25
  SPEAKER_00: That that maybe that's that's starting point if you don't already have one.
• 25:28
  SPEAKER_00: And you can slowly continue to mature that and get more sophisticated.
• 25:33
  SPEAKER_00: Um, so that's how it weird.
• 25:35
  SPEAKER_00: And then on the topic of visualization, I mean, look, like there's some standard tools, right?
• 25:41
  SPEAKER_00: There is Google Data Studio that doesn't charge you anything, there is Power BI that has a little bit of a charge, and there is Tableau.
• 25:48
  SPEAKER_00: I mean, you could start anywhere, you're not gonna be there.
• 25:52
  SPEAKER_00: There are nuances and differences depending on what you want to do.
• 25:55
  SPEAKER_00: For example, like if you are an agency that wants to build reports that are shareable to a bunch of clients, same report being shared to different clients, and when a client login, they only see the data that they're supposed to see.
• 26:08
  SPEAKER_00: Like something like Google Data Studio doesn't support that.
• 26:11
  SPEAKER_00: Right?
• 26:11
  SPEAKER_00: So there are some nuances, but any of these industry standard tools are just fine.
• 26:16
  SPEAKER_00: Uh the real important thing is actually the quality of the questions and just visualizing, okay, what is the view you want to see?
• 26:25
  SPEAKER_00: Because once you have those two, the actual execution is not that complicated.
• 26:30
  SPEAKER_03: That makes a lot of sense too.
• 26:31
  SPEAKER_03: And you've mentioned so many uh Google Data Studio, for example.
• 26:34
  SPEAKER_03: I feel like a lot of agencies eventually come to the point where like we need to do something and it's the most cost-effective way, but then you realize, you know, maybe you get some competitor intel and you're like, wow, this is what professional reports look like, and you can see leveling up.
• 26:49
  SPEAKER_03: And I think at some point, what I notice is either an agency is either going to build their own, which is very expensive, or they're gonna outsource it to intent-wise or other similar uh software solutions because you guys do it professionally, and you have a database of you know agencies and brands, and you know, these questions, for example, is a perfect example of when you go to a data expert, what insights they'll be able to lend you and the opportunity for you to be smarter in the decisions you make around your business.
• 27:20
  SPEAKER_03: Um, this was really fantastic and love the visualization aspect of it.
• 27:24
  SPEAKER_03: What you brought you alluded to it earlier, so I want to bring it up now.
• 27:28
  SPEAKER_03: What are some common misconceptions or mistakes brands or agencies make when they're leveraging data and they're building out some of these systems?
• 27:36
  SPEAKER_00: Yeah, I think the number one thing I'll say is that like people fall into two camps.
• 27:44
  SPEAKER_00: Some look at data and like they're all in, they're in the weights, they're comfortable, you know, they don't mind pulling stuff into a spreadsheet, messing with it, running pivots, running regressions and all that.
• 27:55
  SPEAKER_00: But there is the others who are like, oh, data, like I don't want to deal with it, right?
• 27:59
  SPEAKER_00: So there's these two camps.
• 28:00
  SPEAKER_03: You could put me in that camp, by the way.
• 28:03
  SPEAKER_00: But I'd say to the to the first camp, it's like, look, if if you're someone that really wants to get it, you'll find a way to get it.
• 28:10
  SPEAKER_00: Now it's just a matter of making it efficient so that other people on your team uh can use it, other parts of the organization can use it.
• 28:17
  SPEAKER_00: But I think the number one thing is not to be overwhelmed when we talk data.
• 28:22
  SPEAKER_00: And the way to not be overwhelmed is worry less about the noise and the jargon, like AI and this and that and the other.
• 28:31
  SPEAKER_00: Worry less about that.
• 28:33
  SPEAKER_00: Worry a lot more about I go back to the what I call roadmap, the list of questions you care about.
• 28:39
  SPEAKER_00: Uh, because once you have that, cut the noise out, talk to a consultant or a teammate or whoever, and all you're holding them accountable for is look, I want these questions answered.
• 28:51
  SPEAKER_00: I don't care how sophisticated, how fancy, how not fancy this is.
• 28:55
  SPEAKER_00: I want these questions answered and operationalized, right?
• 28:58
  SPEAKER_00: I think that's how the non-data people can think about their role because ultimately the quality of those questions is what determines how much value you're going to get out of that data.
• 29:10
  SPEAKER_01: Yeah.
• 29:11
  SPEAKER_00: Right?
• 29:12
  SPEAKER_00: So I would start there.
• 29:14
  SPEAKER_00: Um, so back to the question about pitfalls.
• 29:17
  SPEAKER_00: Stop thinking about this as some complex, big, large project.
• 29:22
  SPEAKER_00: Yeah, focus on the questions you care about.
• 29:24
  SPEAKER_00: That's point number one.
• 29:26
  SPEAKER_00: Point number one two.
• 29:27
  SPEAKER_00: We sorry, go ahead.
• 29:28
  SPEAKER_03: No, metrics that matter most.
• 29:30
  SPEAKER_03: I like that.
• 29:30
  SPEAKER_03: And I also found the larger the organization and the more senior the person you're reporting to, they don't really care about all that jargon.
• 29:38
  SPEAKER_03: They're looking for the, to your point, the data that answers that, like the KPIs that matter most.
• 29:43
  SPEAKER_03: So uh some sage advice for our listeners.
• 29:46
  SPEAKER_00: Number two, and we talked about this data ownership.
• 29:49
  SPEAKER_00: It doesn't cost much to store, and today it doesn't cost much to process.
• 29:54
  SPEAKER_00: You don't have to build the API connectivity, like you can subscribe to one uh and certainly house all your see what happens today with the seller central data, vendor central data is like even if you didn't have historic data, uh, I can call APIs and get like two to three years worth of data, pull down two to three years worth of data.
• 30:15
  SPEAKER_00: But that's not the case with advertising data, right?
• 30:17
  SPEAKER_00: So um the point I'm making here is that make sure you're owning your data.
• 30:23
  SPEAKER_00: Look at all your existing service provider relationships.
• 30:26
  SPEAKER_00: Make sure that you there is no data loss just because you stop working with somebody.
• 30:31
  SPEAKER_00: And yes, you should absolutely own all your data, right?
• 30:34
  SPEAKER_00: Yeah, that's point number two.
• 30:36
  SPEAKER_03: And perhaps uh really great point on the advertising data, didn't mean to cut you off, but I would say for brands taking over accounts and when you're getting into it, Amazon's a pay-to-play, so is Walmart.
• 30:47
  SPEAKER_03: So the ability to go in and say what works and what doesn't, 90 days is just a screenshot and it doesn't really give you enough uh for anything actionable.
• 30:56
  SPEAKER_03: So owning your data is a really good point, Serena.
• 30:58
  SPEAKER_00: Yeah, and and the grain, right?
• 31:00
  SPEAKER_00: Like what's the like you can pull down daily data from seller central, total sales, but if you don't have daily grain data on the ad side, how are you going to join those two at a product level to get profitability by day or by week?
• 31:14
  SPEAKER_00: It becomes hard.
• 31:15
  SPEAKER_00: So storing data at the grain that is currently available and owning it is important, right?
• 31:20
  SPEAKER_00: And then the last thing is as much as I mean, we can spend three days talking about data, but the mistake to avoid is boiling the ocean, right?
• 31:32
  SPEAKER_00: Like, don't do that.
• 31:33
  SPEAKER_00: Like you have to, if you're if you're executing a data project of some sort, be you're building out reports or whatever it is, right?
• 31:40
  SPEAKER_00: Don't do this boil the ocean six, twelve, six, twelve month projects.
• 31:46
  SPEAKER_00: No, like focus on getting those answers for the questions you raised in the next two weeks, like and incrementally make progress, right?
• 31:55
  SPEAKER_00: Um, so the mistake to make again is like doing big long projects.
• 32:00
  SPEAKER_01: Yeah.
• 32:00
  SPEAKER_00: Uh, I've seen even agencies do this.
• 32:03
  SPEAKER_00: Like there'll be this reporting project on the side that is going on and on and on.
• 32:08
  SPEAKER_00: And before you know it, you're sunk a lot of money, you don't know where it ends.
• 32:13
  SPEAKER_00: So I think avoiding that, don't fall into that trap, uh, would be kind of the third point I would say.
• 32:18
  SPEAKER_00: And maybe the last thing, it's not a mistake as much as it is.
• 32:22
  SPEAKER_00: Uh, you know, um, if you have a team, right?
• 32:26
  SPEAKER_00: You've got folks on the team, as Amazon and Walmart share more and more data, just going through their certifications and being aware of what is coming at you will actually help you think about what questions you can answer that you couldn't answer before.
• 32:41
  SPEAKER_00: So somewhere on the team, somebody or a group of people have to just be aware of what is being shared by these platforms because it's changing all the time.
• 32:52
  SPEAKER_03: All the time.
• 32:52
  SPEAKER_03: To your point, in the last two years, it's it's bonkers, like the amount of data information we have.
• 32:57
  SPEAKER_03: And you know, from an AC perspective, we love it, but I know some brands you just can't keep up.
• 33:02
  SPEAKER_03: It's it's almost like drinking from a fire hose.
• 33:05
  SPEAKER_03: And I also love the comment you made about boiling the ocean.
• 33:07
  SPEAKER_03: I think that's a really good point.
• 33:09
  SPEAKER_03: And I can't tell you, even from the the client side, like some of the reports and the details, it's almost like you're spending more time trying to build these reports instead of adding value doing these other activities.
• 33:23
  SPEAKER_03: So, on that note, how does the accuracy and timelines of data impact decision making?
• 33:28
  SPEAKER_03: And what strategies can brands use to ensure they're acting on the most relevant information to get to those metrics that matter most that you that you've been bringing up as as we have our list the questions we're going off of.
• 33:41
  SPEAKER_00: Yeah, I mean, I think um, you know, uh I think this is part of the reason why uh I I led the entire conversation with kind of the list of questions that matter, right?
• 33:55
  SPEAKER_00: Like, and I think there is some standard ones, and if you talk to someone like me, there I can suggest the top 10 list uh fairly comfortably because we've you're seeing what works, what doesn't work.
• 34:07
  SPEAKER_00: Um I think again, I go back to uh certainly list of questions, uh, and then also just building some awareness of, for example, Amazon Marketing Cloud is a shiny new object.
• 34:20
  SPEAKER_02: Yeah.
• 34:20
  SPEAKER_00: What I find is most brands are unaware of what the what the heck it is.
• 34:24
  SPEAKER_00: Like, what do you do?
• 34:25
  SPEAKER_00: What new questions will it answer for me?
• 34:28
  SPEAKER_00: So just some level of getting educated on what's possible, for instance, from Amazon Marketing Cloud leads you then to say, okay, now I can actually understand lifetime value uh and understand the impact of advertising on lifetime value.
• 34:42
  SPEAKER_00: Now, if you're a three-piece seller listening, you could have pulled down the uh FBA fulfillment reports where there is a hash buyer ID and use that to come up with lifetime value.
• 34:54
  SPEAKER_00: But guess what?
• 34:55
  SPEAKER_00: That data is completely disconnected from what you're doing on advertising.
• 34:58
  SPEAKER_00: Now, Amazon Marketing Cloud can actually connect those two pieces together, right?
• 35:04
  SPEAKER_00: So, but but my point is just awareness of what new things are possible from which data source is actually important.
• 35:13
  SPEAKER_00: And I would say investing a little bit of time in that.
• 35:16
  SPEAKER_00: And I'll list out a few things, right?
• 35:17
  SPEAKER_00: Like just understand the basics of Amazon Marketing Cloud.
• 35:20
  SPEAKER_00: And by the way, we have done a bunch of things around this in terms of webinars and whatnot.
• 35:24
  SPEAKER_00: And uh, it'll be helpful to, and there are uh Amazon has a great certification um around AMC, understanding AMC, understanding some of the new reports coming out of Seller Central as well as ads, just awareness of that, which can then lead to framing the right questions, is gonna be uh, I think critical.
• 35:43
  SPEAKER_00: Uh, I'm trying to think what else I can suggest.
• 35:46
  SPEAKER_00: Um I'll just keep saying, repeating this, uh, which is list of questions, understanding of data sources so that you can reframe the list of questions, and then iteratively building out those reports and visuals.
• 36:00
  SPEAKER_01: Keep an eye on updates, right?
• 36:02
  SPEAKER_00: That's that's right.
• 36:03
  SPEAKER_00: And you know, and we can get very specific about what metrics matter, but like uh, you know, on that part, I would say um one thing that I always see one of the things that's unique in the case of Amazon or Walmart, and you know this very well, is when you look at products, a product's performance, it is influenced by so many factors at once.
• 36:28
  SPEAKER_00: Right?
• 36:28
  SPEAKER_00: So the important part here I think is to keep moving the puck on looking at a product's performance in a 360-degree view, not just from an advertising lens.
• 36:39
  SPEAKER_00: Because advertising like you could have killer performance and advertising, and suddenly it drops off because you for whatever reason lost the bestseller badge on it.
• 36:50
  SPEAKER_00: Advertising data doesn't tell you that that's what happened.
• 36:52
  SPEAKER_03: No way, yeah.
• 36:53
  SPEAKER_03: Right.
• 36:54
  SPEAKER_03: You got to be in tune to the account too.
• 36:55
  SPEAKER_03: You might miss that just in the general operations of the back end of seller for 3P, for example.
• 37:01
  SPEAKER_00: Exactly.
• 37:02
  SPEAKER_00: Right.
• 37:02
  SPEAKER_00: So the there's a need to what I call like um connecting the silos.
• 37:07
  SPEAKER_00: The silos are there is advertising data and there is retail data.
• 37:10
  SPEAKER_00: This retail data has inventory information, your profitability information.
• 37:15
  SPEAKER_00: You just have to keep like merging these two to get a full uh uh view of the business.
• 37:21
  SPEAKER_00: Like I had a I had a brand the other day, and just you know, they showed up and they're like, hey, can you look at our advertising performance and what's happening?
• 37:30
  SPEAKER_00: I said, sure, it's a my my friend joined that business.
• 37:33
  SPEAKER_00: We're not an agency, but like my friend joined that business as a CFO.
• 37:37
  SPEAKER_00: Just like, okay, fine, like we'll take a look and we look at advertising, like spend is up 60%, ad revenue is up 60%, a cost is flat.
• 37:47
  SPEAKER_00: Like, that's not normal to level up spend by 60%, and A cost stays stays flat.
• 37:52
  SPEAKER_00: That's good, right?
• 37:53
  SPEAKER_03: Yeah, maybe I've missed an opportunity before, that's what it sounds like.
• 37:57
  SPEAKER_00: Exactly.
• 37:58
  SPEAKER_00: But then like okay, let's look at uh top line and tacos.
• 38:02
  SPEAKER_00: Top line is flat year over year, right?
• 38:06
  SPEAKER_00: First half of this year versus last year, and top line is flat and holding up there only because they have spent up more on ads.
• 38:12
  SPEAKER_00: So they're really dropped off an organic ranking.
• 38:14
  SPEAKER_00: Ah and then when I was like, okay, let's go take a look at your BSRs, and it turns out that first half of last year, I think the categories and nodes they were listed in, and the BSRs against them is very different from where they are now.
• 38:28
  SPEAKER_00: So my point is that we just have to be on a path of continuously integrating advertising data and retail data sets.
• 38:38
  SPEAKER_00: And again, you don't have to do it all at once, but slowly progress down that path.
• 38:43
  SPEAKER_00: Because um, this is kind of a unique thing about marketplaces where it's not just one factor, it's a lot of factors at once influencing performance.
• 38:53
  SPEAKER_00: Uh, and you just need to build that sophistication over a period of time.
• 38:57
  SPEAKER_03: Yeah, and that's your comment earlier, like what's nice about Amazon is you're pretty much working within a template.
• 39:02
  SPEAKER_03: You can't put any bells and whistles on there.
• 39:05
  SPEAKER_03: But to your point, understand you also don't get access to all the data.
• 39:08
  SPEAKER_03: So leveraging these software solutions that are connecting these pieces, because to your point, the 60% sales and advertising, great.
• 39:16
  SPEAKER_03: Uh, flat line top.
• 39:18
  SPEAKER_03: Okay.
• 39:18
  SPEAKER_03: And then you mentioned the category.
• 39:20
  SPEAKER_03: Like we've seen Amazon drop categories and subcategories.
• 39:23
  SPEAKER_03: And if you're not on it, you're gonna miss it, and then you're gonna, you know, you're not gonna be able to catch up, or you're gonna miss an opportunity that your competitors may be jumping on, which really resonates.
• 39:34
  SPEAKER_03: Uh, and it does happen.
• 39:35
  SPEAKER_03: Amazon will change things without saying it because you know it's their ball and they can go home whenever they want, pretty much.
• 39:40
  SPEAKER_03: So it is what it is.
• 39:42
  SPEAKER_03: But that's right.
• 39:43
  SPEAKER_03: I want to ask one more question before we dive into intent-wise, because I do want to talk more about the the software company and the SaaS solution that you guys have.
• 39:51
  SPEAKER_03: But before we do that, can you talk about AI and the integration and data analytics?
• 39:55
  SPEAKER_03: Like it is a hot topic.
• 39:57
  SPEAKER_03: So I'd love to get your perspective on on really how is it changing how you guys do business?
• 40:02
  SPEAKER_03: And what are you seeing uh in in the uh in the landscape that that's making you think?
• 40:09
  SPEAKER_00: You know, great, great question.
• 40:11
  SPEAKER_00: Um I mean this whole thing took off about at this point 20 months ago, which is November of 2022, when uh Chat GPT launched, I think.
• 40:23
  SPEAKER_00: Or it's November 2022.
• 40:25
  SPEAKER_00: I think um I quote this uh famous uh, I think it was a scientist, his name is Amara.
• 40:32
  SPEAKER_00: It's called Amara's Law, by the way, and it stay it says um we tend to overestimate the impact of technology in the short run and underestimate it in the long run.
• 40:45
  SPEAKER_00: And I see the exact same thing happening with AI, right?
• 40:48
  SPEAKER_00: We had a huge spike in the noise and marketing and the fluff around it, and I think things are settling down, and we are also people seeing noise like messaging going the other way.
• 40:59
  SPEAKER_00: Oh, AI is not that useful, useless, this, that.
• 41:01
  SPEAKER_00: Like we're seeing the whole like up and down of this curve.
• 41:05
  SPEAKER_00: Uh my point of view on this is the following like the what has happened, AI has been around us a long time.
• 41:11
  SPEAKER_00: Like, you know, when you hear text messaging, the auto suggestions, the predictions by weather, these are all machine learning and AI-driven things.
• 41:18
  SPEAKER_00: The fundamental change that has happened, in my opinion, is the ability to, and that uh by the way, previously it all existed and operated well on structured data, like numeric data that is very structured.
• 41:29
  SPEAKER_00: We have we have been doing AI stuff on it, all of us have been doing this for a long time.
• 41:33
  SPEAKER_00: What's new is AI as applied to unstructured data, text, images, videos, you know, generation of them, interpretation of them, uh, all that is new, right?
• 41:47
  SPEAKER_00: That's the new that that's what we get excited about, right?
• 41:50
  SPEAKER_00: So um, I mean, I I pay 20 bucks and I'm on a subscriber to Chat GPT.
• 41:55
  SPEAKER_00: Uh I use it all the time.
• 41:58
  SPEAKER_03: Yeah.
• 41:58
  SPEAKER_00: So I think my take on this is uh it's there's a any use cases around AI where the output is directly getting into the hands of an end customer without verification are going to be very difficult.
• 42:14
  SPEAKER_00: Like for example, I don't think we will ever get to a place where you auto-generate listing content and upload it without verification.
• 42:20
  SPEAKER_00: That's we are very far from that, right?
• 42:22
  SPEAKER_00: Yeah, but there's a number of use cases that you know don't need to be where the output is not delivered to an end customer, but for your internal purpose.
• 42:32
  SPEAKER_00: So I'll tell you in our case, we have a live chat support on our platform.
• 42:36
  SPEAKER_00: We are taking all live chat conversations, pushing it into a large language model, and asking questions like, hey, which rep stone could be better?
• 42:46
  SPEAKER_00: Which conversation had a negative connotation, right?
• 42:49
  SPEAKER_00: Um, you could do the same with uh review content.
• 42:52
  SPEAKER_00: Like you can grab a whole bunch of reviews for the last one year and say, show me the five things, specific product capabilities that people are talking about that's good or bad.
• 43:02
  SPEAKER_00: So you're starting, you're able to get some insight that you could never get before uh from these large language models.
• 43:08
  SPEAKER_00: So processing of text, generation of text, images, and video.
• 43:13
  SPEAKER_00: This is where I think most of the action is today.
• 43:16
  SPEAKER_00: Um and I do think that there'll be a lot more value extracted from behind the scenes support use cases versus some magical AI thing delivered to an end client.
• 43:28
  SPEAKER_00: I mean, Amazon is trying, you've got Rufus, AI assistant.
• 43:31
  SPEAKER_00: There's a number of other things they'll keep doing, uh, but the accuracy and getting it right is going to be hard and that's gonna take some time.
• 43:39
  SPEAKER_00: And I would bet my money on a lot of let's call it assistive use cases.
• 43:43
  SPEAKER_03: Yeah.
• 43:44
  SPEAKER_00: Right.
• 43:44
  SPEAKER_00: So yeah, that's it.
• 43:46
  SPEAKER_03: I think you hit it out of the park, seeing the same thing.
• 43:48
  SPEAKER_03: I actually used Rufus for this past Prime Day to do some shopping, and it was it was good, you know.
• 43:53
  SPEAKER_03: It able it was able to make some pretty good recommendations, and I did make some purchases based on that, but look at like the Titan update and Of the other things that are in the pipeline.
• 44:02
  SPEAKER_03: Like to your point, it's it's suggestive, like it's good ad making recommendation, but it's not great.
• 44:08
  SPEAKER_03: And I do think to some degree there's going to be a human needed in order to give it direction and also to verify is this actually accurate based on the data we're putting in.
• 44:19
  SPEAKER_03: So I think we're evolving as a community, but it is pretty exciting.
• 44:23
  SPEAKER_03: You know, it definitely saved me a lot of time, as I'm sure it does for you and your team.
• 44:27
  SPEAKER_00: I I mean, I like, you know, I use it to uh uh you know rewrite content, I use it to ask like um the other day there's about five large public companies, and I wanted to understand like, hey, what are their market caps relative to their revenue and e-bitter and all that?
• 44:45
  SPEAKER_00: It was like a three-line prompt, and this thing came back with a beautiful table for all the top agencies uh with all the metrics in two minutes, right?
• 44:55
  SPEAKER_00: So, anyway, I I use it all the time.
• 44:58
  SPEAKER_03: Amazing.
• 44:58
  SPEAKER_03: Yeah, same here, same here.
• 45:00
  SPEAKER_03: But let's jump out to TedWise.
• 45:02
  SPEAKER_03: I want to talk about you and and the software, the service, because you are building some world-class software, you have a great reputation within the community.
• 45:10
  SPEAKER_03: So, on that note, for those of our listeners who don't know, what are your core services and solutions for brands and agencies?
• 45:17
  SPEAKER_00: Yeah, uh great question.
• 45:18
  SPEAKER_00: So uh I'll preface by saying like whatever technology we are building, we have a singular goal, which is uh, as we have talked about on this call, the likes of Amazon and Walmart are sharing more data than ever before.
• 45:31
  SPEAKER_00: And almost everything we do is about helping brands and agencies make the most of all this data, right?
• 45:37
  SPEAKER_00: So, with that as a primary goal, uh, our tech platform is made up of three pieces.
• 45:43
  SPEAKER_00: The foundational piece is uh called Intentwise Analytics Cloud.
• 45:47
  SPEAKER_00: This is the solution that uh where we have automated all the data collection from all the APIs, Amazon, Walmart, and so forth.
• 45:54
  SPEAKER_00: We automate the data collection, we allow brands and agencies to enrich the data.
• 45:58
  SPEAKER_00: For example, every brand may have its own way of categorizing data.
• 46:02
  SPEAKER_00: Brand may be in multiple geographies, so you need currency conversion.
• 46:05
  SPEAKER_00: So collection, enrichment, and we have all kinds of visualization templates, templates for your standard reporting tools like Google Data Studio or Power BI, we even have embedded visualizations.
• 46:17
  SPEAKER_00: So the full stack of reporting, collection to better organization to visualization is all packaged into this solution called International Analytics Cloud.
• 46:26
  SPEAKER_00: And the flexibility of it, where we can fit into an environment where you're a Google Data Studio user or a Power BI user, or you're sophisticated enough where all you want is a data pipe from us into your into your database, we do that too.
• 46:38
  SPEAKER_00: So that's internalized analytics cloud that forms the core foundation.
• 46:42
  SPEAKER_00: On top of which sits our ad optimization platform.
• 46:46
  SPEAKER_00: Um, we have a number of brands and agencies um, you know, leveraging our platform.
• 46:51
  SPEAKER_00: We are hitting close to a billion dollars of ad spent going through our platform.
• 46:55
  SPEAKER_00: And and what what makes our ad platform unique is is uh fundamentally a couple of things.
• 47:01
  SPEAKER_00: One is um we don't box you into a AI-only-based bidding man bid management or a rules-based bid management.
• 47:10
  SPEAKER_00: We have been the only platform for the last five years that allows you to choose between rules-based bid management or AI-based bid management down to the campaign level.
• 47:20
  SPEAKER_00: So that flexibility is unique to us.
• 47:22
  SPEAKER_01: Yeah.
• 47:23
  SPEAKER_00: Um, and then the second thing I'll add is that, like we discussed earlier, 60 to 70% of time around ad management goes into analyzing stuff, right?
• 47:34
  SPEAKER_00: We have built a number of capabilities to dramatically shrink your analysis time so that you understand and find problem areas very quickly.
• 47:42
  SPEAKER_00: For example, there's a feature called what changed.
• 47:45
  SPEAKER_00: You go in there and you put your two time frames, and this thing comes back and tells you the biggest change drivers with an impact score against each change.
• 47:54
  SPEAKER_00: Like here is five keywords, 10 campaigns, and the eight products you should worry about if you're comparing those two time frames.
• 48:01
  SPEAKER_01: That's amazing.
• 48:02
  SPEAKER_00: So I would say flexibility around bid management, deep diagnostics capabilities built natively into the platform, and all that packaged under like a really strong report infrastructure.
• 48:14
  SPEAKER_00: Like we aim for uh response times on our live chat to be under four minutes.
• 48:18
  SPEAKER_00: Um, but yeah, so analytics, ad optimization, and then a complement to add optimization is the third component, is we have a solution that sits on top of Amazon Marketing Cloud.
• 48:29
  SPEAKER_00: Amazon Marketing Cloud, as we discussed earlier, is this phenomenal data set, but a little painful to use.
• 48:34
  SPEAKER_00: You need to know SQL to go against it.
• 48:37
  SPEAKER_00: So we've built a wrapper solution on top of it to help you uh answer questions, build audiences much, much more quickly than you would otherwise do.
• 48:46
  SPEAKER_00: And I can't say much about this, but very soon you will see a much tighter integration of Amazon Marketing Cloud and ad management, even if you're just doing sponsored ads.
• 48:56
  SPEAKER_03: Wow.
• 48:57
  SPEAKER_03: That's amazing.
• 48:57
  SPEAKER_03: It sounds like there's some fun uh updates and features in the future, which is great.
• 49:02
  SPEAKER_03: On that note, so how does IntentWise differentiate itself from other analytics platforms?
• 49:07
  SPEAKER_03: So if I'm in the market and I'm considering a few options, like why should outside of what you just shared, which is amazing, what are what sets you guys apart from other data, data uh analytics solutions?
• 49:19
  SPEAKER_00: Yeah, I will I will frame this from the standpoint of the pain points that brands or agencies have, and uh what are we doing about those, right?
• 49:29
  SPEAKER_00: So there's like I I boil them down into there is a data collection problem if you want to own the data, because you got to set up this infrastructure to collect all this data.
• 49:38
  SPEAKER_00: There's a data organization uh and better data management problem, which is each brand has their own product categories, has their own profit margins.
• 49:46
  SPEAKER_00: Uh, you want to customize that data.
• 49:48
  SPEAKER_00: There are constant data quality issues.
• 49:51
  SPEAKER_00: We know this.
• 49:52
  SPEAKER_01: Yeah.
• 49:52
  SPEAKER_00: You download data, reports are understated, overstated reports are missing.
• 49:56
  SPEAKER_00: You have to deal with that, right?
• 49:58
  SPEAKER_00: Uh, and then lastly, like reporting and visualization can consume a lot of time.
• 50:02
  SPEAKER_01: Yeah.
• 50:03
  SPEAKER_00: We are the platform that has taken a very domain-centric view to the problem and solved all four problems uh in a way that reflects a lot of deep domain expertise, right?
• 50:16
  SPEAKER_00: Um, people want to know at a product level, ad performance, sales performance, and 20 other things.
• 50:23
  SPEAKER_00: If you want to do that on the raw data, you're gonna you're gonna have to join 20 to 25 tables.
• 50:28
  SPEAKER_01: Good luck.
• 50:28
  SPEAKER_00: But because we better organized it, you can get it all done in one from one table, one view.
• 50:34
  SPEAKER_00: And because of that, any dashboards that sit on top of that also load much faster.
• 50:39
  SPEAKER_00: The point is we have attacked all aspects of the data problem in a very domain-centric way.
• 50:49
  SPEAKER_00: And why should anyone care about this?
• 50:51
  SPEAKER_00: We believe we are the fastest path to you getting value from all the data you have on the market.
• 50:56
  SPEAKER_00: We don't just solve one part of the problem, we don't just give you canned dashboards that you can log into, and that's all you have.
• 51:04
  SPEAKER_00: As an agency, you want to tell your own unique story, you want to manage your the client's business a certain way, you want to tell those stories in your reports.
• 51:12
  SPEAKER_00: So we are providing the fastest path to you being able to tell your own stories.
• 51:16
  SPEAKER_00: In fact, in our platform, if you're an agency or even a brand, we have a white label option where on a domain, your own domain and very uh uh new age looking dashboards can be delivered to your clients if you want to go down that path.
• 51:32
  SPEAKER_00: And the library of dashboards keeps growing.
• 51:34
  SPEAKER_00: So your time to build a dashboard is also much smaller.
• 51:36
  SPEAKER_00: So it's like a comprehensive solution with a lot of domain Amazon and Walmart domain expertise baked in.
• 51:44
  SPEAKER_00: And in the end, it's like the you know, the most efficient way to own and build your data infrastructure and the fastest way to get there, and just stay competitive in the market, whether you're a brand or an agency.
• 51:55
  SPEAKER_00: Yeah.
• 51:55
  SPEAKER_03: Date is key.
• 51:56
  SPEAKER_03: The story around data is everything, and it sounds like the your guys' solution is top notch.
• 52:01
  SPEAKER_03: You guys are covering a lot there.
• 52:03
  SPEAKER_03: For all our listeners, so you know, uh, intend why is the website and Serena's information is in the show notes.
• 52:09
  SPEAKER_03: And with that being said, we have a little tradition here on the podcast.
• 52:13
  SPEAKER_03: We like to pull in our crystal balls and get your guys' opinion, uh, our guest opinion on the future of e-commerce and some technology trends, although we did cover a lot already.
• 52:22
  SPEAKER_03: But on that note, as e-commerce continues to evolve, what do you see as the next big trends in data analytics that brands should be preparing for to stay competitive on platforms like Amazon?
• 52:34
  SPEAKER_00: Yeah.
• 52:35
  SPEAKER_00: Uh great question.
• 52:36
  SPEAKER_00: I think that I mean, we already talked about AI.
• 52:40
  SPEAKER_00: A has been AI has been uh one of the big game changes that we have experienced in our lifetime, to be honest.
• 52:46
  SPEAKER_00: Like it's one of those things, it's like the cell phone, right?
• 52:49
  SPEAKER_00: Like I do believe it's that transformational.
• 52:52
  SPEAKER_00: I agree.
• 52:53
  SPEAKER_00: Um, but one thing I will say is that it is also going to become a commodity.
• 52:58
  SPEAKER_00: You already saw, like since ChatGPT, Google has launched, Meta has launched, everyone has a large language, it'll get cheaper and more accessible and more accessible.
• 53:07
  SPEAKER_00: Uh, but for brands or agencies to be able to make the most of it, the core ingredient that makes AI work has to be in good shape, which is your data.
• 53:19
  SPEAKER_00: So so it's it's not a trend as much as how do you leverage the trend that is already underway, pay a lot of attention to your data.
• 53:28
  SPEAKER_00: So that's going to be a must.
• 53:30
  SPEAKER_00: Um comprehensive, clean, well-connected, accessible, owned, right?
• 53:36
  SPEAKER_00: So those are all kind of the words I would use.
• 53:38
  SPEAKER_00: Um the other thing I will say in terms of uh trend is like I just feel like these ecosystems, whether it's um Amazon and Shopify or Amazon and Meta and Pinterest and TikTok, these are the lines are getting blurred a little bit.
• 53:56
  SPEAKER_00: I mean, you saw the recent partnership of Amazon and TikTok, where from the ad someone can execute a purchase right there, right?
• 54:03
  SPEAKER_00: And then you have buy with prime enabled on Shopify.
• 54:06
  SPEAKER_01: Yeah, right.
• 54:07
  SPEAKER_00: So these worlds are merging a little bit, and I think future state is perhaps one where like more and more brands have to think about omni-channel, and there certainly will be data that can help you see the picture in an omnichannel way.
• 54:22
  SPEAKER_00: So I think that's another trend that's underway.
• 54:24
  SPEAKER_00: Like whether you want to call it social commerce or whatever commerce, I think there is um merging of these ecosystems that we continue to see happen.
• 54:35
  SPEAKER_03: That's a really good point.
• 54:36
  SPEAKER_03: And two surprising ones was like Shopify merging with Amazon through the Bioware Prime, which uh frankly blew my mind.
• 54:43
  SPEAKER_03: I was my my crystal ball from a few years ago was like Shopify was gonna do their own thing, and they pretty much came back and said, no, we do websites, great, we're gonna stick with that if you want to use Amazon, and then the TikTok integration with all the uh should it be allowed to stay and all that fun stuff, and the fact that Amazon's buying in and you can have that cohesive experience from TikTok to purchase, uh, says a lot about consumers' faith in uh these marketplaces, how trusted they are, but also how you know where it is now and what's it gonna be in five years is gonna change a lot.
• 55:19
  SPEAKER_03: So I think those are some tremendous uh prophecies that'll be coming our way.
• 55:25
  SPEAKER_03: And if anybody hears it here in a couple of years, you know you heard it here first.
• 55:28
  SPEAKER_03: So thanks for anybody.
• 55:30
  SPEAKER_00: And I'll I'll just add one other thing, right?
• 55:32
  SPEAKER_00: Like imagine today on the TikTok or meta ad, that's an ad run by Amazon.
• 55:36
  SPEAKER_00: It's not run by a brand or whoever, right?
• 55:38
  SPEAKER_00: It's an ad run by Amazon today.
• 55:41
  SPEAKER_00: But what stops Amazon from opening up an option for brands to say, okay, I want to spend this much money, I want to fund part of that ad that you're gonna show on TikTok.
• 55:54
  SPEAKER_00: Yeah, right.
• 55:55
  SPEAKER_00: So I I think that's where this is gonna go.
• 55:57
  SPEAKER_00: It's it's it's it's it's uh it'll all blend together a little bit.
• 56:01
  SPEAKER_00: Yeah, um, and then again, the importance of data just continues to uh grow.
• 56:06
  SPEAKER_03: So it's everything.
• 56:08
  SPEAKER_03: I'm amazing.
• 56:09
  SPEAKER_03: Well, hey, thank you, Srinath, for sharing your your invaluable insights and expertise with us today.
• 56:14
  SPEAKER_03: It's been a pleasure having you on the show.
• 56:17
  SPEAKER_03: Before we wrap up, could you let the listeners know where they could find you and if you have anything else to add or you'd like to share about any upcoming projects?
• 56:25
  SPEAKER_00: Yeah, I mean, um, so yeah, I mean, I'm very active on LinkedIn, so you can find me, Srinath Reddy, your CEO Intendwise.
• 56:33
  SPEAKER_00: Uh, follow me, and I'm pretty prolific with my content, and I try to keep it educational.
• 56:38
  SPEAKER_00: So just hopefully you can get some value there.
• 56:40
  SPEAKER_00: So that's that's one way.
• 56:41
  SPEAKER_00: And of course, intentwise.com.
• 56:43
  SPEAKER_00: And in particular, of course, would love for you to check out all the products we offer, but there's a resources section on IntendWise's website where I think just a lot of people show up just for their own educational purposes, whether you want to learn about AMC or SQL.
• 56:56
  SPEAKER_00: There's a lot of free stuff out there that you can leverage.
• 56:59
  SPEAKER_00: So that's how you can find us.
• 57:00
  SPEAKER_00: In terms of just updates, I mean, we're gonna be we'll we'll have our booth at Walmart Seller Summit, accelerate, and then unboxed.
• 57:08
  SPEAKER_00: Um, but what I'm most excited about, uh honestly, is um you know, bringing Amazon Marketing Cloud, sponsored ads, and retail data sets more and more together.
• 57:20
  SPEAKER_00: Uh and we actually revamped our website very recently, and you can see that like we have really going down a data-centric path, which which because I think that is a path forward to stay competitive.
• 57:32
  SPEAKER_03: Absolutely.
• 57:33
  SPEAKER_03: And I'm gonna plug your newsletter.
• 57:34
  SPEAKER_03: I subscribe to that and I get them whenever you push them out with some really top-notch information, not only from like a data perspective, but like strategic implementations you can use based on the data that's available on Amazon.
• 57:46
  SPEAKER_03: So uh a lot of that will be included in the show notes.
• 57:50
  SPEAKER_03: And Srinath, I can't thank you enough.
• 57:51
  SPEAKER_03: I appreciate you taking the time to be with us here today.
• 57:54
  SPEAKER_00: Well, thank you so much.
• 57:55
  SPEAKER_00: Well, and I uh I hope to see you now.
• 57:57
  SPEAKER_03: Thank you, Sreenath, for sharing your invaluable insights on how brands can leverage Amazon data analytics to drive growth.
• 58:04
  SPEAKER_03: It's clear that with the right approach, the data available today can unlock significant opportunities for growth.
• 58:11
  SPEAKER_03: For our listeners, if you want to learn more about IntentWise and work with Sreenath and his team, be sure to visit their website at intentwise.com and connect with them on LinkedIn, which is in the show notes below.
• 58:23
  SPEAKER_03: As always, thank you for tuning in.
• 58:25
  SPEAKER_03: And don't forget to like, follow, and subscribe to stay updated with the latest episodes of Selling On Giants.
• 58:32
  SPEAKER_03: I'm your host, this is Mr.
• 58:33
  SPEAKER_03: Wills.
• 58:33
  SPEAKER_03: Signing off.
• 58:34
  SPEAKER_03: Stay classy, people.