#353 – Scaling Ecommerce: Data-Driven Solutions with Krishna Poda

#353 - Scaling Ecommerce: Data-Driven Solutions with Krishna Poda Speaker 1: Welcome to episode 353 of the AM PM podcast. In this episode, I'm speaking with Krishna Poda. Krishna runs a company that consolidates data for larger sellers across All the platforms, they tie into like 100 plus different APIs and systems where they can bring all of your data into one place. And data is crucial for analyzing your business, especially once you get to that 1 million plus mark. Having all your data in one easy dashboard where you can analyze everything, get true P&Ls and true picture of what's happening is so critical. And it can be complicated when it comes to running on different marketplaces, different advertising platforms. We're going to be talking about that and more in this episode. Enjoy. And don't forget this summer, I'm debuting the Billion Dollar Sellers newsletter. It's 100% free for listeners of this podcast. So be sure to go to BillionDollarSellers.com and put in your email address and name to get on the beta list so you can be one of the first to get this brand new newsletter. It's gonna be chock full of advice and tips and strategies and hacks for e-com and Amazon sellers. BillionDollarSellers.com. Unknown Speaker: Welcome to the AM-PM Podcast. Welcome to the AM-PM Podcast, where we explore opportunities in ecommerce. We dream big and we discover what's working right now. Plus, this is the podcast where money never sleeps. Working around the clock in the AM and the PM. Are you ready for today's episode? I said, are you ready? Let's do this. Here's your host, Kevin King. Speaker 1: Krishna Poda, welcome to the AM-PM Podcast. It's an honor to have you here. Speaker 2: Kevin, great to be here as well. Looking forward to the chat. Speaker 1: Now we met not not too long ago back in in the spring I think it was at an event in Austin like an Amazon seller meetup and I think Leron maybe actually came and introduced us and I'd never heard of what you done but we started talking I was like man this is this is pretty fascinating this is pretty cool. Let's tell everybody a little bit about your background you come from the IT world correct? Speaker 2: Yeah, IT and analytics. So I've graduated back in India in 2005 with a degree in computer science, migrated to the US about 16 years now and worked with companies like National Instruments and Oracle before Setting up Cyrus Analytics. I was an enterprise architect at Oracle before I decided to set up the company. Speaker 1: What does enterprise architect mean? For those that aren't in the IT world, what does that mean? Speaker 2: Great question. An enterprise architect is somebody who understands business objectives and lays out a technology roadmap that enables a business to achieve those stated business goals. Broadly, I would say that is their responsibility. A good enterprise architect would have a great sense for a business and business goals and the objectives they're trying to achieve, would have a good understanding of different technologies and how they work together. And also have a good understanding of how a different set of technologies can be stitched together to achieve these goals. Speaker 1: You're more like, you're like a movie producer or something. You're not the guy down in the weeds coding everything, but you're the guy bringing all the parts together and putting all the pieces together to help whatever the client is or the business or the goals of that piece of technology. Speaker 2: Yeah, I used to do that for about 12 plus years before taking on more of an enterprise architecture role and being more like a director or producer, if you want to call it that. Yeah. Speaker 1: So enterprise architecture is the next level up above that. Speaker 2: Yeah, an enterprise architecture is taking a bird's eye view into, like I said, the goal systems, the technologies, and optimizing the tech landscape to achieve business goals, both in terms of technology performance, but also in In terms of cost and also keeping in mind people's capabilities and how those capabilities sort of play into the usage of technology. Speaker 1: You grew up in India. You came to the US to get, I think, like a master's or a PhD or something like that. And then you decided, hey, I'm going to stay here. You took some jobs working for these big companies. Did that for, like you said, 12 plus years. And then when did you start your current company? You went out on your own and started the current company. When did you start that? Speaker 2: We are actually coming up on seven years now, next month. Speaker 1: 2016. 2016, that's right. And how did you, were you just tired of working the corporate job or did you see an opportunity to do this or do you have a buddy that was maybe messing around in ecommerce or something like, hey, I need a solution for this. You're like, I can help you out and then just kind of snowball from there. How did that process work? How did that evolution work? Speaker 2: Great question. When I was doing my hands-on work, I was moving data, building dashboards, doing analysis, making different systems talk to each other. And at my role at Oracle, I moved into an enterprise architect role, and my responsibility over there included talking to many CXOs at companies trying to understand their business goals and like I said doing whatever an enterprise architect would do. I did that for about four years. Incredible experience I must say. Learned a few things along the way. We were working with small to mid-sized companies. Companies making less than 250 million in revenue. We used to call them small to mid-size. And one of the common themes that came across is a lot of these companies that I spoke to and I would have easily spoken to about 2,000 companies over a period of four years and got into deep deep conversations with many of them. And one of the themes that commonly emerged is hey we have the tech but we don't have the people to utilize that tech and deliver business results. We have the people but the tech is expensive. And ultimately due to some of and they they set off on their data initiatives for example But those initiatives have to be abandoned, either because the people who have started it have left the company. Keep in mind, these are small companies, they're not necessarily having an army of people running these projects, right? There's usually a two, three, four member team. And even if two people leave, now suddenly you're handicapped significantly. So this sort of was a repeat pattern in a lot of my customers and I also noticed very closely that they were spending a lot of money but not succeeding in their initiatives. So that's what led to the genesis of Saras Analytics as a company. The broad idea was how do we make data easy for small to mid-sized businesses. When I say data easy, it is at the end of the day data is a means to provide decision support to stakeholders. But there are a lot of processes and systems and people that enable that to happen and that sort of was the genesis. Speaker 1: They say what can't be measured can't be improved or something along those lines. So data is critical and especially when it comes to ecommerce. There's so many people that are just flying by the seat of their pants or doing something just with Excel spreadsheets. And maybe that's okay when you first start out and you're just doing a few thousand or $10,000, $15,000, $20,000 or something. But once you get into the level that some of the listeners here are, they're doing millions or tens of millions or even in some cases hundreds of millions of dollars. The data and the way you're processing data for your business is crucial and tying together In this business, there's so many different systems from the Amazon system, the Shopify system, the logistics systems, the advertising systems, there's so many different things and they're all written in different, some of them are written in PHP, some of them are written in Python, some of them are written in, you know, some other Ruby on Rails, whatever it may be. And tying all those together can be a super challenge, right? Speaker 2: It is indeed a challenge. In fact, when we started the company, we had a much broader objective, which is making data easy for small businesses. But after spending a couple of years working primarily in the e-commerce industry, e-commerce slash digital industry, we decided to narrow down and solve specific pain points for this particular vertical. And like you said, If you take a seller who is on Amazon, they might not just be selling on Amazon US, they might be selling on Amazon UK, Amazon Mexico and they might even be selling in Amazon in Europe and Japan as well. And they have inventory sitting in all of these different places. Amazon is rolling out ad products than a confectionery store can produce cookies or candies. And they're encouraging sellers to spend a lot of money on various advertising products, right? So if you just take a seller who is on Amazon, they have data in each marketplace and data in each of these advertising systems. So unless somebody can consolidate all of this data, Getting meaningful insights in terms of how their business is actually performing, identifying opportunities to, you know, improve their business, you know, Business outcomes can be more challenging and time-consuming. Now if the seller decides to let's say start selling on Walmart or Target or set up their own Shopify stores, they are just amplifying the problem statement because now there are more and more data silos. So our product and we can talk about that later, but the first problem is consolidating all of this data into a single place. And then stitching all of this data together so that the business can then visualize and understand how they can benefit from quickly, quick to use, readily available data, which is up to date. Hourly, so that they're not spending valuable time doing that on their own. Speaker 1: Yeah, that can get extremely complicated really, really fast. I mean, I know there's some off-the-shelf programs like Centel and there's several others out there that help, you know, if you help you manage marketplaces so like you can upload, you know, your listing to one place and then kind of spread it out through the APIs to other marketplaces, but there's nothing really that consolidates all these different types of reportings and all this different type of stuff into one cohesive dashboard. So instead of having a lot, like as you're expanding, if you're a big seller on Amazon, you have to log into multiple systems to get reports or you get managers logging in, printing out reports or sending you PDFs or whatever. And it can be It's daunting, but if you can have one dashboard that basically has everything, if you want to drill down, you can easily drill down. That's basically what you guys do, right? It's like on one master dashboard and then, so if I'm running, I'm not running my business, I'm running my business, not in my business, as you should be if you're at this level. You shouldn't be the guy, you should be running the business, not in the business. You can log in really quick and see the master. You can play God basically and see the master overview of everything. Is that correct? Speaker 2: Yes. So that's one of the major outputs that gets generated through our work, which is like you said, a business owner should be on the business, not in the business. I myself, over the last seven years have done a lot of working in the business, right? Instead of having one of our engineers fix a problem, I try and go and fix the problem myself. But what that means is I'm not spending enough time reaching out to people, meeting new potential new customers and trying to focus on how to grow the business rather than getting very detailed and trying to solve problems that perhaps are better suited for somebody else to solve. And that realization took a lot of time. I wouldn't say I'm perfect at it, but it's a learning curve. And we have invested a lot in productivity softwares over a period of time, so on and so forth. And because I've seen the evolution of myself as an entrepreneur over the last seven years where I had to take on different roles and at each role, I had to figure out okay what is my responsibility in this particular role and what are the responsibilities that in an ideal world I should be delegating and expecting outcomes on so that I can focus my efforts and my leadership team also can focus their efforts on the strategic aspects of the business rather than running the day-to-day. Speaker 1: You're here in the U.S. is any the rest of your team here in the U.S. or most of them in India? Speaker 2: We have a small portion of the team here in the US but I would say for the most part we are an India based company. Speaker 1: So that means you're working some strange hours. You're from Austin, you're in Austin so it's a 10 and a half hours time difference I think to India. So that means you're up late at night or early in the morning. Speaker 2: It's actually both. So, it's actually both the, I guess the only downtime I get is in the afternoons and that is if I don't have any customer calls on that day. But yeah, it's been pretty rough but exciting at the same time. Speaker 1: How big is the team in India? Speaker 2: We are roughly 160 teammates spread across software engineering, product management and consulting. Speaker 1: Why did you decide to actually base most of the team in India versus in the US or Philippines or somewhere else? What are the advantages to having most of the team in India despite you having to work odd hours to go into meetings and stuff with them? Speaker 2: Great question. One is familiarity with the ecosystem back there. Second is we are a bootstrap company. We have been since day one. And what that meant is every dollar we earn, we have to be very judicious about how we spend it and figure out how to get the most value out of the dollar that we are spending. So India also happened to be a cost effective way to achieve that. And the third and. And equally important aspect of it is we work with the small to mid-sized businesses, right? And for them, especially on the consulting front, it becomes unviable or in most cases unviable to provide the same level of service and support and capability having a US-based team at a price point that makes sense for the smaller businesses. So that's also a part of the driver for building a team in India. Speaker 1: And Indian programmers are talented. I mean it's a specialty of you know the training and everything over there is really good. So I've got a couple of my businesses that we use programmers based in India to do a lot of everything from just website stuff to database stuff to whatever because like you said it is more economical and they do a good job. They know what they're doing. Totally understand on that side. So what What are some of the things that you see when people start to scale their ecommerce business? Some of the big pain points that they're having that you guys help solve. What are some of the things that when you take on a new client that comes to you and you're like, oh my God, this is just a mess over here or you're not paying attention, you haven't been paying attention to this and we're gonna show you like, holy cow, this is eye opening to the seller. Like I had no idea this, this and this. What are some of those things that come about when that happens? Speaker 2: Yeah, when you say ecommerce to me, it means a few things. It could mean that a seller is selling on a marketplace like Amazon or Walmart. It could be that they are also selling in a store like Shopify or BigCommerce. They have their own direct-to-consumer presence and they might also be offline in retail. So now there are some products that are better fit for selling in marketplaces like Amazon. There are some that are more brand-oriented where An ecommerce platform like Shopify or a direct-to-consumer model might be better, so on and so forth. We have customers that span all of these, right? We have only sellers who are on Amazon. We have brands that are on Amazon and Shopify. And I would say the needs of them at a high level are very similar, yet the complexity of fulfilling those needs can be a little challenging. One of the first things that I was quite surprised over the last few years when I looked at it was Profit and loss statement, an automated profit and loss statement that accurately tells the business how much money they are making each day, how much they are spending and or if they are losing money, how much they are losing, right? Not having a P&L statement, especially in a market where you see interest rate rising and investors are asking about profitability, so on and so forth, it's quite challenging. So that's one area where customers work with us quite closely on. And if you talk about a P&L statement, there are a bunch of inputs that need to go into, right? Marketing spends, cost of goods sold, sales data, on-hand inventory. So essentially you're If you look at the pyramid where at the bottom of the pyramid you have a bunch of different sources and applications that you're using that are actually generating data, your P&L sort of sits at the peak, which is your ultimate output. And that output has to be generated through inputs coming from all of these systems. Your COGS might be in a spreadsheet. Your marketing spend is in Amazon and Facebook. So consolidating all of this and getting to a P&L has been an exercise that customers have asked us to solve quite extensively. A lot of customers also want to understand their customers more deeply. Granted, Amazon doesn't share a lot of the customer, personally identifiable customer information, but it's not difficult to get repeat customer purchases. How many new customers are you acquiring? So that sort of information around lifetime value, customer acquisition costs, so on and so forth, are another area where we've been doing quite a bit of work lately on. Speaker 1: Your system, I think you told me, you tie into something like 120 APIs or something like that? Speaker 2: We currently have support for 120 different sources. Currently we have the capability to add a new source in a week's time frame or maybe even less. So I guess for all intents and purposes, wherever customer has their data, if that platform has a mechanism to share their data, we have the capability to ingest it. Speaker 1: If they don't have a mechanism to share it through an API or other means, do you have the capability to scrape it? Speaker 2: We don't get into scraping. What we ask the customer is normally those platforms have some other mechanism, right, where they can schedule a report and say, I want the scheduled report to be delivered to an email. And customers can set up an auto forward rule on their email to send that file to our platform and we process that data and ingest it. So that could be one mechanism. Our customers can manually download the file and put it into a Google Drive or something like that. We read the file from the Google Drive and we move it to that consolidated place. Speaker 1: You've got to tie into a lot of different systems. I'm selling on Amazon and Shopify. You're tying into those two systems. You're tying into my QuickBooks or my Xero or something like that. You're tying into maybe my payroll HR software or perhaps Tying into, I guess, any kind of shipment or if I'm using a freight forwarder that has some sort of a digital automated platform, you're tying into all that. That can be, that's not a one size fits all kind of thing. So you're basically having to customize. I mean, you probably have some templates and some base, you know, starting points, but you're really having to customize for every single client. Is that true? Speaker 2: Yes, so we do have templates which serve as a fast start for the most common use cases but at the end of the day we are of the opinion that every business is unique and so are their business intelligence or analysis requirements, right? So although we start off with the base templates, customers typically Analyze their business in their own unique way. And that unique way may not be captured by templates. And that's where having a tool that cannot be customized limits customers because now they're using a tool already that's giving them some data, but then it is not solving their needs. So they download that data into spreadsheets. And again, they're going back into the spreadsheet where they're massaging the data or finding insights with whatever processes that they like to follow. Our approach is slightly different. We give turnkey solutions to customers who are on a budget. For customers who have a little bit more of an expandable budget because they need that customization, we make it cost affordable for them to have a customized, very unique setup that is unique to their business. Speaker 1: What size business in the e-com or slash retail, I guess you're doing like you said you're doing both, what size business would be, should I be at before I consider integrating all my data and information systems into one place? Should I be at $100,000 a month? Should I be at $50,000 a month? Where's that point where you suggest that people move off of their spreadsheets and their basic stuff into a more advanced sophisticated system like this? Speaker 2: Yeah, over the last seven years and prior to that in my previous 15 years of experience as well, there's one metric that I've sort of arrived at, how we can debate whether this metric is right or wrong, but it's something that we very closely believe in, which is brands. I would strongly encourage brands to spend one to two percent of their annual revenue on data initiatives. Speaker 1: One to two percent of your gross revenue and your revenue on data initiatives. So that means software programs or customization, anything? Speaker 2: Anything. So it could be software, it could be, you know, people to customize it, so on and so forth, right? So yes, if I'm a 10 million dollar company, then one percent is about 100k. That's what I found. Speaker 1: That's what you would spend, but that's what you would spend is about 100k if you're a 10 million dollar company. That's what you would budget. But at what level should I be at before I consider doing this? If I'm a brand new seller just starting out, should I get these systems in place or should it's really not effective or worth the trouble till I get to 50,000 or 100,000 dollars in monthly sales? Where's that number? Speaker 2: Yeah. I'd say 1 million in annual revenue is a good place to start to get some tooling in place so that people save time. Most of our customers are perhaps in the 5 million or above range. 1 to 5, we do have some customers. We do less customization work for them. 5 to, I guess, 100, 200 is fair game. So 1 or above, in short. Speaker 1: You're not just doing this for sellers. I mean, I think you have some clients that are like service providers or PPC agencies or they're something like they're aggregating a bunch of data from, you know, they got three or four hundred different accounts that they're managing and you're aggregating all that data into like one master dashboard or something. So they're not actually selling, but you can do that kind of stuff as well, right? Speaker 2: Correct. Yes. And the beauty is it's the same platform. It's just that the scale is different. And we have made a conscious effort over the last four years of development to build a platform for scale. So let's say for a brand, we are running 20 connections. For an agency, we might be running 20,000 connections because they have so many customers or sellers that they are managing. So yeah, so agencies have been good customers for us and we've been able to drive a lot of value for them and so are sellers as well. Speaker 1: There's a couple other software tools out there that kind of do this and there's one I think out of Australia and there's a couple others but how are you guys different than a few of the other people that may be on the marketplace? Speaker 2: Yeah, so one I would say is being able to handle scale is not easy. Things do tend to break at scale so I'm not sure how our competitors are able to manage scale at this point in time but we made a conscious effort from the beginning not to build a point solution but to build a platform that can actually scale. The second is We have unique capability within the product to be able to add new connectors quickly. So if a seller let's say is starting on Amazon, six months later they decide to go into Europe and start selling into a European marketplace because it's profitable for them or set up a direct-to-consumer store on Shopify and start selling on them. Unless the platform has the ability to scale to the demand of all of these new connectors, customers are often dealing with multiple tools. So not only do you have multiple tools at the application layer, so you have Shopify and Amazon, but you're also ending up using multiple tools at the reporting and analytics layer where you're probably getting Amazon reporting in one tool, Shopify reporting in another tool, retail reporting in another tool. It's the same problem all over again, right? And the true opportunities get lost in these silos. So we have our approach basically enables customers to start small. They could be a single store in US in Amazon and it's a vital product and now they have a direct-to-consumer brand. They can grow with us over a period of time and we've seen that happen over the last few years. Speaker 1: How's the big boom in AI affecting what you guys do? Speaker 2: We are very, very excited about it. We're very excited about it. At the end of the day, AI models only work when customers have their data consolidated. So there is another reason why customers should, I believe, take their data seriously. Because once the data is consolidated and they have access to that data, AI models can be unleashed on that data and interesting insights and applications can be developed or built on top. Speaker 1: I can see how that would be super powerful to have all that data aggregated and, like you said, unleash an AI on it to analyze it and it's probably going to create some eye-opening gaps or opportunities. Speaker 2: Correct. Think of it this way, right? So you can ask into a chat screen, hey, what are my top performing products today, rather than looking at a dashboard. You know, and have that delivered to you and more intelligently, right? And you can engage with that part. So I'm super excited about the possibilities. We're doing some work there internally, but hopefully they'll see light of days later this year. Speaker 1: Do you just assimilate the data and create reports or can I actually manage my business from it? Can I manage like All my customer service, so if I have Shopify site, Walmart.com and Amazon US and Amazon Europe, can it bring that data in, all the customer service data so it's in like one master dashboard or do I still have to manage that separately? I know you bring in the spend, the sales, all that kind of stuff, but can you bring in that kind of data as well so I can have one place to do everything? Speaker 2: Yeah, so we have built a system that will enable customers to have, and again, we are only focused on business intelligence, analytics and machine learning right on the data space. So we are not necessarily going out there and building a software that will respond to a review on Amazon. That's not our focus area. But Any data that you want to report and visualize and analyze is fair game. We have, for example, for customer support, if you're a Shopify customer, you have a service known as Gladly or Gorgias, which are very popular services in the Shopify ecosystem. Now, customers can integrate that data into the dashboard through our tooling. and see how their customer support is performing along with the impact that that customer support ticket might have had on retention of that customer. Let's say a customer has had a bad experience and the customer churned at the end, you know, soon after that interaction, you can correlate that information and maybe use that information to coach your support team, so on and so forth, right? So yeah, and if customers are using a service or a customer support system that we don't support at this point in time, we're more than happy to just add that into the system. So in a nutshell, yes, everything that a customer might want to report and visualize on, we are able to support. Speaker 1: You don't have the system to actually answer those customer service, but you can analyze the data by tying into these other systems where it says this is how long it took to respond, this is the impact it made. So it's really the data analysis, not the actual interaction. Speaker 2: Yes, it is. It is both. So let's say, let's look at the scenario, right? And I have this problem internally as well. We use a service called as Fresh Chat and Fresh Desk for our customer support. And we have an internal database where we are seeing Customer activity. All right. Now, for me to understand that, okay, here we have a customer who is in our enterprise plan. How many tickets have they created in the last six months? And how is that ticket volume trending over a period of time? There's no way for me to look at it other than taking each customer one by one, going into these other systems and then plugging those details and then looking at the report in a different, so I'm going back and forth, back and forth. Now, if I want to tie that with, okay, this enterprise customer, how much did they pay over the last six months? Now I have to go to a different service like Stripe or something like that, where we are using the credit card to bill. So that's a different service that the support system doesn't have. But today I have an internal dashboard where I have all of these things tied. So I just go to one location and I see, okay, here is my, these are my top, let's say 100 customers. These are the challenges that they're having. And that enables me to have better conversations with the customer support team and train them better, have better conversations with the engineering team and drive more sense of urgency in resolving these issues. Speaker 1: So can you tie into some of the other existing tools that are out there? You know, some of the keyword research tools like Helium 10 or some of the other, you know, tools that manage PPC and that kind of stuff that are already out there on the market that people have developed. Are you able to bring that data in so I can almost overlay that? Like if I have a keyword research tool and I have my PPC, I can almost create my own little custom script or have the AI when you get to that point, you know, analyze between the two and see what I'm missing, that kind of stuff. Are you able to do something along those lines? Speaker 2: Absolutely. As long as the PPC tool has a mechanism to share data, whether that is through a file export or an API, it's fair game. We can build that connector into a platform and start shipping that data. Speaker 1: Okay, awesome. You work with some of the biggest aggregators in this space, right? And what are some, when they come to you, I guess you're kind of under the radar, so you're not really out there advertising or sponsoring stuff. I had not heard of you guys until I met you a few months ago. So it must be like word of mouth that's getting around for the most part, but when they bring you on, What are some of their aha moments? What are some things that you see where they're like, holy cow, this is so awesome, and now I had no idea about this, this and this. What are some big difference makers that you see, big wins that they get right away? Speaker 2: Yeah, I would say the biggest win for an aggregator especially is time to value. For example, we have one of the most robust support for Amazon's SP API and Amazon Advertising API, Amazon Marketing Streams, and we are soon launching support for Amazon Marketing Cloud as well, right? So if I was an aggregator and I have let's say 40 or 50 brands and I want to consolidate all of this data from you know 40 or 50 different Amazon marketplaces if they're only selling in US or hundreds of marketplaces. Then they would normally would have to spend and hire six or seven developers just to build support for this API. And it would probably be a year, one and a half year project because Amazon's constantly improving their APIs, adding new capabilities, so on and so forth, right? So it'll probably take them like a seven or eight member team to just get this entire thing up and running and maybe a year, year and a half of development and iteration. We reduce that to days. And that's the benefit, right? It's really the time to value is what we offer for all of these ideators where they can bring the credentials to their systems, plug it in into our platform and boom they have All the historical data extracted and loaded into their systems. And most of these aggregators have internal data analysts or data scientists. So they just use us to get the data from a bunch of different systems. We deliver the data to them and they build intelligence on top of it that we don't have privy to or access to. So they build, in other words, their own custom solution that is unique to their business and we enable them to get there faster. Speaker 1: You don't have data scientists on your team. You're the aggregator of data. And then the aggregator of Amazon accounts can layer their own technology or their own stuff on top of that. Speaker 2: Correct. In the context of an aggregator, they don't use our consulting services, which has data scientists, but they don't use us typically for those sorts of exercises. But they just use, like you said, for aggregation of data. They use the product. Speaker 1: So are you looking to get to expand beyond ecommerce? I know some of your ecom people also do retail, you said, but do you see any other applications or other industries out there where you might be able to expand this type of technology? Speaker 2: I feel like we could. I mean, we also have customers that find us online and sign up. We have some software companies that use our product. We have some. Manufacturing companies who use QuickBooks come and use our product etc but from our focus area standpoint there is so much to do in ecommerce, so many problems to solve that we're going to stay in this in this area for a few more years and get to the bottom of it and you know simplify like I said make data easy for as many customers as we possibly can. Speaker 1: What are like, if you had to give advice to an e-commerce seller, what are like the top three to five data points they need to truly pay attention to that a lot of them maybe don't? A lot of them know their gross sales, a lot of them know how much is in their bank account, those are the obvious ones, but what are some of the big ones that most people don't pay attention to that they should be? Then when you aggregate the data, it just makes it crystal clear for you. Speaker 2: Yeah, I would recommend that every business owner have a strong sense for the KPIs, right? So there are tier 1 KPIs, tier 2 KPIs, tier 3 KPIs, right? In my business also, there are sales and there are costs which are tier 1 APIs, but there are so many tier 2 and tier 3 APIs and optimization really happens there. For example, reducing customer ticket resolution time will improve stickiness and provide better retention of customers. Right. So that will in turn have an impact on revenue. So I would encourage sellers to think about their KPIs. I'm pretty sure everybody knows their tier 1 KPIs one way or the other, right? Otherwise, it would be difficult to run their business. But I would encourage them to start also thinking about this tier 2, tier 3 KPIs across the different departments that they have, operations, inventory. You know, supply chain, customers, marketing insights, etc. and see whether the current systems that they have are actually answering those Tier 2, Tier 3 KPIs well or if they find themselves using a bunch of spreadsheets to get that information. The second key call-out that I would have for sellers is the frequency with which they are checking this Tier 2, Tier 3 KPIs. They can get to tier 2, tier 3 KPIs using a spreadsheet, but if going through a spreadsheet means they are getting that visibility into those KPIs like once a month or once a week, then maybe that's not ideal. And they're probably doing it once a month or once a week because there's a manual effort. They just don't have time to put in that effort. So it's just kept getting delayed. So if they wish that you know what I wish I had access to this information faster more automated and I would like to do this more frequently and they don't today I would say is another signal and the third one is focus on as a bootstrap company this is critical for me there's almost in our DNA focus on Customers and customer happiness, you know, repeat purchase rates so on and so forth for businesses that lend themselves to repeat purchase rates is important and also profitability. Stay on top of your finance metrics so that at the end of the month when bills are due you're not stressing yourself out if you're a seller. Speaker 1: Does your tool allow you to go the other way? You're importing all this data, but do you allow export too? Like if I'm consolidating all this data, can I export that to my QuickBooks to create more robust PNLs and not have to manually enter all this data from all these different places? Speaker 2: Yeah, so today the PNL that we are building might reside in a tool like Google Data Studio or local studio like this is called now or Tableau or Power BI, etc. But we don't necessarily push that PML to QuickBooks per se. The industry term over there is called reverse ETL. Although I don't like that term, we prefer to call it feeds or activation. We will have some of that capability later this year, but to specific use cases that are relevant. So for example, I can take my customer data and send it to If I'm on a direct-to-consumer store, right, let's say I'm using Klaviyo as my email automation service, I can have a unified customer record in my warehouse or customer 360 and push that to Klaviyo so that my campaigns can be run in a much smarter, more granular way. And we'll have some use cases there for Amazon sellers as well later this year. Speaker 1: This all sounds pretty expensive. It's a lot of brain power behind building out these systems and they're pretty complicated. What am I looking at if I want to implement this in one of my businesses? Speaker 2: It's not expensive. Like I was mentioning at the beginning of the podcast, we started off with the goal of helping small to medium-sized businesses. And there are three P's, as I want to call it. There are people, process and price. So price is an important element of the tripod, which has to be lower. So if you are a seller, if you're looking for automated reporting, The cost would be maybe a couple hundred bucks a month or something like that to get things out of the box from a reporting standpoint. Speaker 1: A couple hundred bucks a month, is that plus a big setup fee or is that just get in a couple hundred bucks a month and you'll tweak everything to work with my systems? Speaker 2: So usually the setup fee is only charged when we have, let's say, a ton of customer profiles that have to be set up and let's say P&L, right? So P&L, some customers might say, hey, I have my own way of capturing P&L and that is in this spreadsheet that I created that doesn't sit with our template. So it depends, I would say it depends in some cases there is a set of fee we assess it with the customer and some cases it doesn't. But for the most part, especially if it is purely a seller, not necessarily an agency because they have a different set of problems, we try to avoid the set fee. Speaker 1: That's awesome. It's really affordable to do something like this. I would think this would be, if you go to Oracle or somebody like that, they're wanting, what is it? 10 grand a month plus $50,000 a month or some crazy number to have a dedicated engineer. It's crazy like enterprise level pricing but that's since you like you said you're targeting the small to medium-sized businesses. They don't have that kind of money. That's not normal to them. They don't have government money where they can just make it up out of thin air. So you're really catering to them and providing something that's I think desperately needed and a lot of people just aren't doing. Speaker 2: They're not doing, maybe some are not thinking that it's important, but we believe that data ownership is critical for long-term success of a business. So if I'm a seller or a brand and I'm focused on building a strong presence in the market for a long period of time, in my head it is imperative that they have ownership of their data. And if they don't, then, and normally, I was so surprised actually, I've met a lot of sellers who have the data backed up on their laptop, like they would run a report on Amazon ads and save that report on their laptop in a CSV file and have that backed up over a period of time. But if that laptop crashes, then they probably lose that data. Or they're using a third party tool and if you decide to cancel a subscription of that tool, I don't know what the terms and conditions for the tool might be, but it's possible that they might lose some valuable business performance data if they're not taking ownership of it. And that's where our approach is to help brands take ownership of their data in an affordable manner so that they can look at historical performance, what worked, what didn't work and use that in their decision making going forward. Speaker 1: You tie into all the social media platforms as well for people that are running ads on like Facebook or TikTok or Instagram or any of that kind of stuff? Speaker 2: We have all of those plus Pinterest, LinkedIn, Twitter, Snapchat, a bunch. Speaker 1: I agree with you. Data is one of the most valuable assets of any company. A lot of people don't realize that. I talked to somebody the other day that said they had 1.8 million email addresses that they've just been capturing from insert cards and different methods and they've never emailed them. They're afraid to email them. Why? That's a goldmine right there. But when you can consolidate, like I remember when I was selling on Walmart, I'm not selling on Walmart right now, but I was selling on Walmart for a while, Amazon, Shopify, through the mail, and I was getting all these leads and I was having to manually update my master database of customers and names and email addresses. Your system will do all that automatically tag them. And that that right there is worth the price of a mission alone, just to have all that in one single place. And when you have that data, it's If something goes wrong on one of these platforms, you have it. Like you said, it's there and you can leverage that and you can use it in a lot of ways. It's so important, not just from the analytics point of view, but from just the having it point of view. Unknown Speaker: Correct, agree. Speaker 2: So, that's what we are trying to enable and we are trying to enable in a cost-effective manner, a friendly manner. We love to retain our customers and in a manner that will deliver long-term success for the sellers, brands that work with us. Speaker 1: Awesome. Well, if somebody wanted to reach out, Krishna, and find out more about you guys, how would they do that? How would they find out more about what you might be able to do to help them out? Speaker 2: So we are available on sarasanalytics.com, S-A-R-A-S, analytics.com. So feel free to reach out and hit the contact us button and leave your details and we can be in touch. I'm also on LinkedIn. Speaker 1: So, saras, S-A-R-A-S, analytics.com or you can look up Krishna Poda on LinkedIn. Awesome. Krishna, I know this was your first time to ever appear on a podcast. You did an excellent job. I know you're a little bit nervous, but great job man and you guys are doing a really good thing here. I hope some people are able to take advantage. Speaker 2: Thank you, Kevin. This was a breeze. So thanks for making it easy and looking forward to chatting with you again soon. Speaker 1: Data and analytics are the backbone to the success of any business. What you can't measure, you can't analyze, you can't improve. So doing something like what Krishna was talking about, where you bring everything together from all these different platforms can just make the analysis so much better. And combining that with where the advances in AI are going right now, it's almost a no-brainer, almost it, even if you're below that 1 million threshold that he said. So I hope you got some good information from this episode and it enlightened you on some of the things you may need to be thinking about if you're a beginning seller or if you're already established and doing well. This is something that I think you should definitely to look into doing, whether it's with a company like Krishna's or with somebody else. We'll be back again next week with another great episode. But before we leave, I've got some words of wisdom for you. This is from actually Mary Kay Ash. Mary Kay Ash, the famous cosmetics company founder. She says, don't limit yourself. Many people limit themselves to what they think they can do. But you can go as far as your mind lets you. What you believe, remember, you can achieve. Don't limit yourself. Many people limit themselves to what they think they can do. But you can actually go as far as your mind lets you. What you believe, remember, you can achieve. See you again next week. Unknown Speaker: Thank you.