Cyber Media Research & Services Limited (CMRSL) Earnings Call Transcript & Summary

A very, very good afternoon to CMRSL investors. I also want to extend warm wishes for the Navratra -- ongoing Navratra that are going on, and I hope you all are enjoying the festive season. Today's call is, of course, not something that we do regularly. Today's call is different from the 6 monthly investor calls we do. And the reason we set it up was because there were quite a few investors who reached out to us. And also we had, of course, spoken about and promised that we would share a demo for CMGalaxy with the investors and sort of showcase what are some of the technology that we have been working on, which is an important part of the future of the company. So with that, let me share my screen. I also want to mention that, in terms of today's call and today's session, the focus for us will be on talking about the technology side of things, right? So we're going to be emphasizing on what's the product about, what's the technology behind the product, where we have come forward. And I -- in case you do have questions regarding sort of performance and how quarter 2 is going or how H1 is looking, my request is that please hold those till we are able to, of course, announce our results sometimes towards middle of November, right? So today is going to be more about technology and sort of not so much about specific numbers, okay? So this is the website, cmgalaxy.com. And I'll give you a walk-through on it, and I would encourage all of you to please go to cmgalaxy.com and check out the website. But let me straight away jump into the account, right, and to the demo account. And once you log in, this is a quick overview of what you would see inside, right? Now what we are trying to do with CMGalaxy is that in terms of advertisers -- today, advertisers have a very large number of platforms on which they will spend. So let's take for the example of e-commerce. In the case of e-commerce, they would be spending on, of course, Google, Meta, but also on places like Amazon, LinkedIn, x.com, Pinterest and many more, right? So managing across all these dashboards can become a big challenge. And more often than not, most organizations are using a very, very manual approach to managing these dashboards and taking out the reports and sort of trying to do any decision-making on that. This is an extremely slow process. This is a very well-established pain point in the entire marketing industry. CMOs who have been surveyed have constantly spoken about how technology and automation is something that is a challenge for them. And now with AI coming into the picture, having the accurate data starts to become even more and more critical, right? So what we did is that we embarked on this journey to build CMGalaxy, where all your marketing platforms and the data associated with it can be aggregated in one place, right? So this, first and foremost, starts to make reporting not just automated, but in fact, pretty much real time, and it takes away the manual effort that needs to go into managing many, many, many dashboards. So for example, the spends that you see here would be spends as an example, across all the platforms that you are currently working on. Similarly, impressions, clicks, CTRs, average CPCs and so on, right? Spends by campaign. This allows the customer to easily understand where they are putting in their money and also see where is the product-wise spend. Now this is a great -- product-wise spend is a great example of where a lot of our heavy data engineering comes into the picture because this is something that is not easy to do. There are quite a few campaigns that don't necessarily aren't set up product-wise. But if they have provided targeting or if they have shown an ad specific to a particular product, then we are reverse engineering that data to showcase this information. Traffic source-wise spends, region-wise spends. So this is, again, very easily available. Then campaign performance across all my platforms is available in one place. And I can start to see which -- where am I getting better clicks from, where am I getting better cost per click CPCs from and accordingly change my budgets, right? And also, most importantly, source-wise performance, right? Where are the orders coming from, right? So how do we track the orders? And I think this is something that we will talk about a little bit later in more detail. But this snapshot is what is crucial in being able to take very quick decisions on what to do with your marketing budgets. Let me jump into the Google performance snapshot. Now here the drop-downs change, right -- so sorry, just let me come back to the overview. And this incidentally is a platform that has been built in the latest [indiscernible] technology. So we keep on upgrading it. And we'll talk about the technology in more detail in a little bit, but this is in the very latest versions of various technologies, right? Now here, we have provided these drop-downs and let's say, I want to understand what's happening in my top few campaigns, I can very quickly use the drop-downs, do a permutation combination, select that and the data starts to get populated in terms of what's happening specifically for those particular campaigns, right? So we've also tried to make it very dynamic so that it's easy to not just look at the overall snapshot, but if you need to do a drill down, if you need to look at something specific, then you can easily do that, okay? Coming now to the Google dashboard. Here, the drop-downs change, right? So what you saw in the overall snapshot, this is now a much deeper drill down as far as Google information is concerned. So again, campaigns which are Google specific, but also ad groups region-wise and so on, right? And this data is giving you now a snapshot in terms of what's happening as far as the Google-specific campaigns are concerned. Even we are capturing keyword analysis and keyword-wise data. And the way this works is that we're not only able to showcase what's happening here, but also enable the right data signals to go back into Google or Meta or the other engines, which then significantly play a part in improving and optimizing your marketing spends, right? Let me also very quickly showcase the Meta dashboard. So again, the information here is an aggregation of whatever is happening across all your Meta spends and what sort of trend. What we have also now done here is that, let's say, I want to understand what's happening in a specific campaign, I can click on that and I can start seeing campaign-specific information, right? So that allows me to ensure that all my analysis and all my -- whatever in-depth breakup I need, I'm able to do that right from this centralized dashboard, right? Let me give another example of that. When I go into ads and let's say, I'm here clicking on the top-performing ad. Now here, this is actually telling me the specific ad creative that is working and what is the spend, what are the clicks, how is it performing, what are the right kind of demographics that are coming against it. And therefore, what I can now do is I can quickly see that which are the ad groups that are sort of performing better. And so my creative outreach and A/B testing from a creative point of view becomes much, much, much better, right? So again, this is a sort of -- I can look at it for Instagram, I can look at it for Google, I can look at it for Meta. And again, currently, the challenge for a lot of creative teams are that they have to go independently into each and every tool and each and every platform to get this information. So now this is all centralized in one place, right? Let me now move on to -- so similarly, by the way, of course, we have a very large number of integrations. We have already done that for LinkedIn, Amazon, Pinterest, x.com. We've also done that for programmatic channels like DV360 as well as PubMatic, Magnite. And that's, of course, dependent on the custom requirement that any brand may have, okay? Moving into the funnel, right? Now this is where the real excitement starts. This is where the real fun starts. Capturing all the data across dashboards is something that you would have found in the market other platforms doing, but that represents only what is happening in top of the funnel, right? The way we define and the industry defines top of the funnel is marketing outreach via omnichannels, where brands can interact with targeted audiences, which basically translates to third-party platforms where ads are running, right? But once somebody clicks on an ad and they come to my website, what is the action of the audience at that particular point of time. And that is where what starts to immediately happen is that the -- for the engagement piece, most brands end up relying on analytics, pre-analytics tools like Google Analytics for, which is a big black box and doesn't help brands truly map user profile and user journey, right? So what we've done is we've built our analytics engine, which is -- effectively replaces tools like Google Analytics. And that helps marry and match the data, integrate the data with whatever, let's say, Google is sending as signals, Meta is sending as signals, et cetera, et cetera, and map that with what's the user engagement, who clicked on the ad and what is the user engagement of that particular cohort, right? And so the data that you start seeing here is specifically for performance marketing, how many people came via performance marketing, how many sessions, how many -- which are the main products that they clicked, what was the engagement in terms of seconds, average pages per session and so on, right? So this might look like sort of basic data, but the fact that we are tracking those users, we are building user journey, that starts to, again, give -- help brands build their own first-party data and reduce reliance on the third-party advertising platforms. Let me move into bottom of the funnel. So the bottom of the funnel is where we also end up integrating not just the marketing data and the CDP data or the analytics data, but also the sales data, right? So this -- we are not a CRM company. We are a MarTech setup and -- but what we do is that we work with additional CRM companies, right? So if there is a company using, let's say, Salesforce or Zoho or from an e-commerce point of view, Shopify, WooCommerce, then what we have done is we have built integrations also on the sales end so that we can genuinely map what was the marketing, what was the engagement and what was the sales that resulted from it, right? So at bottom of the funnel, we are tracking add to cart as well as initiate checkout. And this gives us a much deeper understanding of what's actually happening in my entire funnel. And we are able to do, of course, full funnel attribution. And full funnel attribution is very crucial to reducing marketing wastage and actually making marketing campaigns very, very effective, right? We're also tracking abandoned checkout, returning users, new users and very important data, which is that based on initial checkout, what was the source that ultimately led to that particular checkout, right? So this becomes very, very relevant data again for marketers to see which of their marketing channels is performing effectively. Moving to conversions. Conversions is the actual sales data, right? And in this sales data, what we're doing is we are tracking by source and based on last click attribution, what's happening across the entire channel ecosystem. This is a big, big benefit for a lot of advertisers and brands because what happens is the data is sitting in silos. Facebook data is sitting somewhere else, Google data is sitting somewhere else, sales data is sitting somewhere else. And all that data doesn't speak the same language. The data ends up giving different, different, different kind of pictures. And it is actually what is the real source -- what is the real truth behind your marketing data is more often than not, it's just not clear, right? And it's not accurate. So here, we are helping brands build that out. And that also, by the way, becomes very crucial and very important when we start talking about AI in today's world because data accuracy is such an important baseline to build any correct AI, right? I mean if you don't train AI on the right data, then your AI is also not going to be effective and it's going to become a situation of garbage in, garbage out, right? Now this is the sales data. And if a team wants to go in and track that, they can do that. But what we've also done here is that you can click on a particular user and you will be able to see their details, right? So you'll be able to see what their personal information is, but more importantly, what was their monthly page view, average time spent, also monthly product purchase by value and also abandoned cart versus purchase. So this becomes really, really crucial data because this data is then becomes important in also doing retargeting and also trying to convert clients into loyal customers and therefore, make sure that the targeting is effective and accurate, okay? So this data becomes, again, very important from a retargeting point of view, okay? So this is in terms of the full funnel, right? Now I also want to spend a few -- a little time in terms of sort of how we have made this extremely usable, right? So what marketers today look for is, of course, how can they get this data easily, and for that, what we have done is also built a reporting hub. And this reporting hub is where we are able to provide reports from across multiple platforms, right? So if I go into view all, there are a bunch of standard reports that we have created, which significantly help -- which are very popular and they significantly help clients sort of pull out that, okay, this is the relevant data. Of course, if I want to create a custom report, I can very much do that. And there is a lot of customization that is available for brands when it comes to these platforms, right? So they can really go in and they can play around a lot as far as the data is concerned. We can -- they can obviously schedule these reports. This is an example of how the reports would look. And then if they want to download it, view it, edit it, et cetera, et cetera, then that functionality is very, very easily available. In terms of some other basic functionality, we also have a very robust user management system. So we allow our customers to add as many users as they want. So we don't have a limitation on the number of users. And there is a very dynamic sort of approach. So let's say, I want to give access to a business head. I can still determine that what sort of -- what kind of access do I want to give them; user management should be available; not available with them, do I want to give them access to the funnel or not? So these are the kind of things that are available, and it's very, very dynamic in nature. Now let me take a quick pause and -- actually, let me continue and let me save the questions for right at the end, right? Now that we have all the data in place and tracked -- provided the brands with accurate real-time data, I think the next big question that comes up from customers in today's date is that what's happening with AI, right? And what we have done is that we have been trained an AI engine to give us recommendations, right? And so we have platform-wise recommendations that are available, which give an impact what's the -- what needs to be done, what is the expected change that could come across all platforms, right? And what I can also do is that, let's say, I want to go into Meta and give details, it will give me the reasons why, right? It will give me impact, it will give me suggestions. I can also chat with it. So this starts to now enable brand managers to manage basically adjustments on their campaigns, which is driven through AI, right? By the way, the name of our AI is Lex. So we call it Lex AI. And this recommendation engine is something that we have been working for a while. Some of you who have seen the demo in the past would not have seen this, but we've been working on the recommendation engine, and this is now something that we are very excited about. We're seeing good results. And this is showing that what we are also doing as an AI setup at our end can be really powerful and can make a big difference, right? Continuing on the AI front, we're not just giving recommendations, we've also built Lex as a chatbot as well as a data visualization tool. So -- sorry, let me just take a step back. In order to make sure that the AI is pervasive and it can be used across the board, what customers can do is also just open up this slider on the right-hand side and start using AI for different things, right? So what we have here is you can ask questions specifically or specific to different platforms, you can also say no and then that then becomes across all platforms. And then you can have different kinds of graphs, you can chat your way regarding specific types of graphs or data analytics. And that makes it very easy to -- and makes the entire process of managing marketing very, very fast. And that's the need of the hour today when it comes to AI, right? We also have, of course, a full AI assistant working. So we have a chatbot. The chatbot can give you answers about your campaigns or generic answers about marketing. You can ask it to do a lot actually. You can -- it, in fact, starts to become more and more effective once it's trained on the customers' data set, right? And then it gives you more and more specific answers about whatever type of brand, be it B2C, B2B, e-commerce, it starts to give you answers in line with that. We have also built in a data visualization tool, right? Now this is again something that is very powerful. There are lots of large enterprises that often hire a team of data analysts, right? And the team of data analysts is just responsible for going through marketing data to bring out insights, right? Here, what we can do is that we can select an account. For example, we can say Google performance, I can say, break down my CTR in the past 2 weeks or the vertical bar graph, I can visualize and it will give me an answer, right? And this is like prompting, right? So you just type out whatever you want, and it will give you the necessary data and you can check it and cross-reference it with other data items and so on. What we've also done is we've built an AI bot library, right? And this library is there to sort of different -- help different kinds of marketing processes and really start speeding up things. As an example, what we've done -- I can -- let me showcase you the brand guidelines generator. And in the brand guideline generator, what we have done is that we've -- for example, for CMGalaxy, created -- used AI to create a brand guideline, right? And so this brand guideline has been prepared using our AI. And what it does is it just doesn't give brand introduction, but it gives a tone of voice in terms of what is the right tone that CMGalaxy should be using, what are the details in terms of the logo, usage, dos, don'ts, color schemes, typography and iconography, right? A lot of brands, especially medium SMB brands often don't even have a set brand guideline, right? So the first step with AI is that, look, we're training the data on this AI, your marketing data, but also what's your brand about, what's the right brand guideline and so on. So this is what these kind of -- I mean, this, for example, AI tool uses. And of course, I can go in, I can edit it. This is an AI-assisted workflow. And so once you feed it information, you can hit generate with AI and it will give you -- it will spit out a brand guideline. And then you can go in and edit the brand guideline also. So we've taken care to think about that and ensure that the AI tools are not just giving you an output, but also an output that you can edit and you can improve. Okay. So this is something that we are very excited about as an AI library because in the AI library, we can start to now provide brands with lots of different kinds of tools, which are entirely customized as per what they need to deploy in their organizations, right? So this is what we have been working on with CMGalaxy. As I've mentioned in the past, we are very sort of excited about the product, and we think it is an important part of future growth of the organization. By the way, let me also very quickly come back to the website. So on the website, as a conclusion, we spoke about omnichannel marketing. So omnichannel as in data coming in from multiple channels and assimilating it, making it easily available in a centralized place. We are integrating and stitching that data together to ensure that it's accurate. We are also enriching the user profile and the user data. And that data enrichment is a very core component of what differentiates us from a lot of other companies, other MarTech companies out there. We, of course, very much are working on Lex and on AI. AI is going to become very fundamental to -- once you ensure the data is there, then we are building those assistants. We're building those AI agents that are customized right now. And I don't think it's going to be a one -- from our experience, we are seeing that it's not like a one size fits all. It's going to be tools that will need -- that have to be -- AI has to be trained on the correct data. Once the AI is trained on the correct data, based on internal processes, a customized AI agent or tool has to be deployed, which then brings in that efficiency and brings sort of is part of your workflow, right? Full funnel attribution, this is, of course, the fact that data enrichment is happening on user profiling. So we are not only looking at combining the top-level marketing data, but it's also the engagement data, it's also the sales data. And that's the power of CMGalaxy. Of course, we are integrating with many, many, many systems and products. We are very happy to do integrations with additional different types of tools in the industry. So that's something that we are very proud of. And the architecture of CMGalaxy, the way we have built it, allows for all those integrations to be done. So I invite all of you to go through the website in detail. Each of these things are -- there is sort of more information about how this works, more information about what are the reasons why marketers should be signing up and looking at very seriously at a tool like CMGalaxy because the technology maturity is very, very important to now have -- building a higher technology maturity in your organization, right? And so if you don't have a modern data stack, then you're missing out, right? So how do you really make a high-impact marketing engine that is able to intelligently give you inputs, give you feedback, give you data and then recommend how do you improve on your existing campaign, right? So yes, that's the CMGalaxy. You can also -- and I would also like to request all the investors that are available that there is very much a sign-up page. Brands can go and literally create an account for free and get started up with their Google data and Meta data. And once the CDP and CRM integration is done, then they'll start to get full funnel attribution as well as the AI recommendation. So please share this with other organizations who may be doing interesting marketing, and we'd love to connect with them, and we'd love to get their feedback as well, right? So yes, we'll also share this URL in the chatbot, and that is something that then is available to all of you, and we can accordingly -- and would love to sort of have you help us spread the word, right? And with that, let me stop my share. And yes, let's -- Shikha, let's try and open it up for questions. I think there may be some in the chat already. And if you can -- yes, if you can help us guide us through it, then that will be great.

Yes. There are a few investors questions in the chatbox. If you want, I would read them to you.

Shikha, I think maybe it will be good if you can walk us through the queries and we can address them.

Sir, the first question we have is from Mr. Ramesh Nair. The question is, could you share examples of specific client or use cases where CMGalaxy has delivered measurable business impact? And how is client feedback being incorporated into the product...

Sorry, the second -- how is client feedback be?

The question is how is client feedback is being incorporated into the product road map?

Got it. Got it. So Ramesh ji, thank you so much for your question, and it's a great question to get us started off. So in terms of the use cases, we have some very, very good use cases on the B2C side and particularly with e-commerce, right? So we are working with a lot of clients when it comes to Shopify as well as WooCommerce integrations. And what we've been able to do is that help them, first and foremost, get a better understanding of who are the customers that are coming to their websites and what is their behavior, right? And because you have full funnel attribution, what we are able to do is that we are able to set benchmarks for different types of brands in terms of what should be the CTR when it comes to ads, what should be the engagement when it comes to engagement, what should be the add to cart, what should be the checkout and therefore, solve the places where any specific brand may not be succeeding, right? So that's one very direct example. Also because there is better user understanding and user behavior and user profiling, they are also able to do better retargeting. So one of the things which I, in fact, maybe missed showing is that we also have an in-built push notification system. And that push notification system also allows brands to then send customized push notifications, e-mailers, SMSs right from CMGalaxy, right? Or if we even have a Klaviyo or any of these kind of e-mail marketing tools, they can be integrated in CMGalaxy so that personalized communication can go for a brand to all the customers. So personalization becomes a very, very important, particularly for e-commerce. Quick personalization becomes a very, very important sort of rule and that then will help with conversions. And that, by the way, also includes WhatsApp integrations and so on. So those, I would say, are 2 major things. And then the third is, which is to answer your -- also on the AI front, which is on AI, it is a custom approach that we are deploying right now, right? So we are bringing in that feedback from the clients of what is the data that is important from them -- for them, what are the integrations that will further help them understand what's happening across the platforms. And that is a very proactive thing that we have been doing with all our customers. So that's -- there are product managers, who engage customers in bringing that feedback.

And just to add on to what Dhaval has said. So if you...

Let me introduce [ Agam ]. So Agam is heads our product road map. And he's jumping in with some inputs and he's one of the good -- better product managers in the ecosystem. So we're grateful and lucky to have him. Agam, over to you.

Yes. So glad to be here. And just jumping in a few additional thoughts on the use case side. So I'll take with a very simple example of it. If you are running performance marketing campaign, there is a lot of time when your performance marketer is, we can say, fighting or arguing about which channel is working for you, okay? And we have a typical case, let's say, if a company is using Facebook, Google and other kind of channels, they said our stakeholders want Facebook to go down. And this is a typical case because the conversion, the last click is coming from Google. So they believe Facebook doesn't work for them. But when you go in full funnel kind of analysis, you will understand like all their top of the funnel is coming from Facebook, while the conversion is happening on the Google. And you can see that through CMGalaxy on every touch point of your customer from -- there may be a case where in the single touch point there might be a conversion, but there will be a case where 20 touch point taking even for a very simple e-commerce company. So like first time they saw an ad on Facebook, then month later, they basically purchased through a Google or maybe organic search kind of thing. So these kind of use cases come to us all the time, and that's where like the full funnel makes sense for them and decide like what kind of channel is working, where they need to improve budgets and not. And for the road map point of view, the road map is quite simple in terms of customer life cycle. So we see brand guidelines, it's an input for our ads like creative ads. When we have a creative ads, that become an input for ad sets. Once we have ad sets, that become an input for campaign management, then we'll go towards the path of running ads, recommendation. And based on recommendation, we improve again the same cycle of brand guidelines, creative ads, campaign management, data processing kind of thing. So the cycle is critical for us. We are building a smaller block towards it. And every -- like we generally onboard customers by ourselves. There is a free onboarding also to get those kind of feedback. So yes, like we are building very closely with customers. You will see our dashboard, you will see our product is changing really fast. We are shipping our product features really fast on it. So I would say it's very customer in the centric part kind of thing. I hope this answers your question.

Yes. I want to add more, but I think there are a lot of questions. So let's -- I think, move to the next question, Shikha..

Yes sir. Next question is Mr. Siddanth V. from the question is how is the data capture or tracking impacted by GDPR and other privacy guidelines? Do we need mandatory consent to track this?

Yes. So great question. Today, data privacy is, of course, a very important topic. We are fully GDPR as well as CCPA compliant. We have spent a lot of energy in ensuring that we follow the right kind of brand guidelines and particularly when it comes to international advertisers who operate in these markets where there is a lot of strict action and penalties can be applied, if you don't follow the norms. So those are things that we are -- we have very much factored into how we are collecting data and processing data. We also ensure that the data is actually not accessible or available by anybody. It is entirely anonymized. So even our internal teams don't have access to that data because it is entirely anonymized. Only clients in -- depending on, if they have admin rights, can get access to that data. So data collection, how our pixel works, how Lex works, that does very much factor in that side of things. Yes. Agam, would you like to add anything? Otherwise, we can move to the next question.

Yes, it's like a common question for all the clients whenever we talk about it. So we call it galaxy pixel, which get into the website to track all those kind of things. So it's a part of opt-in and like general consent kind of thing. But to ensure that we are on the path of building our trust center properly, so we are working towards getting those kind of certification also like that is already in our road map kind of thing. So we are going -- we are looking for SoC, GDPR, CCPA and those kind of certification, which is coming along in future -- like very near future on this to make sure we have an answer for this particular thing properly in a documented manner.

Shikha, let's move on to the next one, please.

The next question is Ansari Namra Firdaus. The question is, how do you ensure competitors can't easily replicate this product? And also in this product [Technical Difficulty].

Yes. So Ansari ji, we've -- there's quite a lot of -- there's almost sort of 4 years of engineering that has gone into it. The team that we have -- I must point out that this has been an investment from CMRSL. And I think the team that we have is -- has been an excellent team, right? And then right from the IPO, what we have been talking about is that we want to build products that are not just copies, but in fact, create a lot of value for the clients, right? So that's something that is often even talked about in India where there is a lot of software getting developed, but is it really creating value? And is it really something that can compete at a global level, right? So that's our aspiration. That's what we are going for. It's -- see, we welcome, I think, sort of potential guys to come and take a crack at it and try and build this, right? I mean we have been operating with -- and we work, in fact, now with so many agencies where they -- it's very hard to do the level of data engineering as well as back end as well as the front end that we have put together. And it's -- there is no -- sort of we can't stop, but I think at a global level, there are only I would say, a handful of companies that have sort of done this well and successfully. And we are in that club. We sort of -- our aspiration is to sort of be in the top few MarTech companies when it comes to solving these problems globally, right? So that's our aspiration. That's what we are working towards. This requires a lot of data engineering in the sense that it's not just mapping the data and putting together a table, right? The Google data that comes, the -- even the Meta data that comes, the sales data that comes, they don't talk the same language. They are completely different data sets. Everybody is fighting for attribution. And so there is no single source of marketing truth. So getting into the data and really identifying what is the accurate data is not so automatic and it's not a simple problem to solve, right? Moreover, sending the right signals back into a platform and what at any given point of time is working for a particular platform is an insight that we have fine-tuned and developed over years of managing this through our product. So it's -- we feel that there is a lot of exciting stuff that is there in Galaxy, and I don't think that is so easily replicable. But if there are people who are trying that, then sure, we welcome the competition. Okay, Shikha, let's move on to the next question, please.

The next question is from Ramesh Nair. The question is IT leverage third-party platforms, how scalable is the product in handling large complex data sets as client usage grows? And then the second question is how intuitive is CMGalaxy for nontechnical business users? What's the typical learning curve?

Yes. Ramesh ji, both excellent questions. Thank you for sharing them and very relevant to what our sales team talks about, right? So in terms of scalability, marketing data expands very rapidly, right? And when you are trying to get very detailed information, we typically work with extremely large data sets, right? So we are very capable of -- and the way our IT infrastructure has been set up, we are using AWS. We're using DigitalOcean. And it is designed. It is able to handle a very significant amount of data very easily. We do have consultants with us on how to optimize the data if necessary. And -- so therefore, on the data front, today, our costs are very optimized despite the fact that there is very large and complex data that we are collecting on behalf of our clients, right? And this complexity, by the way, continues to grow and evolve, right? Now brands are starting to even look at new greenfields like connected TV ads and so on, which is something new, which we are also looking at as an opportunity since we have the platform. So these are going to be all areas of opportunity, but I think we are very, very well set and our architecture is very, very well designed so that it can handle this level of complexity, right? So that's one. Agam has also, by the way, put in some of the more technical inputs in chat, and I think you can go through that in terms of what is the backbone -- the IT backbone that is being used to handle a lot of this, right? To answer your next question on how intuitive CMGalaxy is for nontechnical and business users, that's something that we often get really, really strong feedback on that it's actually designed for a CMO. It's designed for a decision-maker. It's not designed for somebody who is only very, very technical. So even the dashboards that we showed, it enables right somebody from a CEO, who is not necessarily very technology savvy or not looking at marketing on a day in, day out basis, to somebody who is a digital marketing head and looking at -- really wanting to do a deep dive. The way we have tried to structure it is that we give good top-level snapshots. But yes, if you need to do a deep dive, then that option and that opportunity is available through reports, through getting into specific creatives, through getting into AI tools that could be used for very, very specific instances. You can use Lex AI for, again, asking it to create a specific campaign, like say, a Diwali campaign. So it starts to become an assistant or an agent, not just for senior decision-makers, but also for day-to-day marketers. Okay. Yes. So let's move on to the next question, Shikha.

The next question is from [indiscernible]. The question is, "Hello, I am new to your company. I wanted to know if your product is limited to the marketing aspect of a company? Or is it that you are able to on various other data sets and generate insights for your clients?

All right. First of all, welcome to the company. And in terms of our focus area and as far as CMGalaxy is concerned, our focus is very much on MarTech, right? So we do have a market research and data analytics business that does take care of such other requirements. But as far as CMGalaxy is concerned, that is very much focused on what we showcased today in solving marketing problems and marketing -- paid marketing challenges. That is what our core focus and emphasis is. Shikha, next question please.

The next question is from Bhavesh Choudhary. The question is what is the range of charges for customers? And what are the competitors charging?

Yes. All right. So when it comes to the competitors and our charges, our charges are focused at -- for Indian clients at $150 a month. So that's a starting point. But typically, we will work with larger clients who also more often than not have customizations, right? And so when it comes to customizations, there could be, for example, AI-related customizations, there could be data integrations, there could be a lot of signals that now they want from CMGalaxy back into other systems. So based on that, we do end up obviously building out those customizations for them. And therefore, there could be clients who are also spending thousands of dollars with us, again, based on whatever their current requirement need and setup is, right? Globally, I would say that we are competitive in terms of our pricing. And most of the other brands who are offering CDPs or sort of marketing-oriented dashboards at our level would typically be higher price point, right? So different -- but they have -- may have a limitation on the number of seats. For example, in our case, we are not putting a lock on the number of seats, and we want to enable brands to sort of use it not just for marketing, but -- I mean, also in terms of the AI and enable them for the day-to-day services. I also want to mention that for the data cost and the AI tokens, that is, of course, something that gets chargeable on over and above, right? So that's based on actuals, right? So that's how our pricing is set up. All right. Shikha, next question please.

The next question is question from [indiscernible]. The question is what exactly CMGalaxy is doing, is also being done by some other software? The companies might already be tracking their entire marketing activities. What are we offering that gives us an edge over others and makes customers choose us. Also has CMGalaxy been commercialized? Do we have any customers onboard?

So I'll answer the second part first. So yes, we do have -- very much have customers onboard. Yes, it is being commercialized. And that is something where now our focus on GTM is growing more and more. We have had it in development, and we have been investing more and more towards the technology over the last few years, but now there is a shift and clearly working towards onboarding more and more clients, right? In terms of -- it's being done if -- what we are doing is being done by some other companies. See, I think -- I don't want to get into commenting about what other companies may be doing. My focus is on our product development road map, which is very robust, which is very aggressive. And I also want to mention that we do regularly look at what's -- what are some of the offerings out there in the market and not just we are talking about India market, at a global level. And honestly, we end up benchmarking ourselves with some of the MarTech activity that's happening probably at a global level more than what's happening in India. I think maybe I want to put it that the wrong way. I don't think there are too many homegrown solutions around what we are offering right now, right? So that's something that we are very wary of. We are very -- we are constantly looking at what's the latest innovation that's coming about in the market. And we feel that we are in a very good place to make a difference when it comes to onboarding and solving these MarTech challenges. All right, Shikha next question please.

Sir, the next question is from Mr. Ramesh Nair. The question is beyond traditional social media and digital platforms the CMGalaxy also track and provide insights from new age apps such as food delivery and quick commerce players like Zomato, Swiggy, Blinkit, et cetera. How deep is the coverage and how is that data leveraged for clients?

Yes. Okay. So Ramesh ji, let me share one clarification here. CMGalaxy is today solving for all marketing challenges when it comes to the web and including the mobile web, but not the app ecosystem. So what we are doing is for app owners, we end up integrating with AppsFlyer, right? But where -- what our focus area has been is that when it comes to B2C as well as D2C as well as B2B, most brands still very much operate on the web directly, right? And that's where CMGalaxy ends up having the maximum impact. The app ecosystem is something that we -- where we do have customers where AppsFlyer kind of tools get integrated and the data flow is then coming via some of those tools, right? Zomato, Swiggy, Blinkit is -- I mean, if they are onboarded direct as a customer, then yes, but otherwise, we are not sort of pulling in data from these platforms specifically for -- on CMGalaxy. Is there anything worth adding, Agam, should we move on to the next question?

Yes. And the other part is the Blinkit, Zomatos of the world doesn't have a correct API. Their API ecosystem is very limited to their own platform. So still there is way to go from that side of it. So it's kind of a limitation right now.

Yes, Shikha, back to you.

Sir, the next question is from [ Rajat Jain ]. The question is, can you please upload the presentation recording as snippets or shorts on some social handle of CMRSL. It can help gain some organic traction?

Sure, sure. I think that is a good suggestion. Shikha, let's make a note of that. And we can -- so of course, aside from the website, on social media, we are -- CMGalaxy is posting. It's relatively -- it's a few months back, but we have started to build traction on that. And for -- from this particular presentation, we can put together -- we have a deck and we will put that up and make it available.

Sir, the next question we have is, you say marketers, but that's a very broad term. Who in the team, the CMO or brand manager or digital marketing manager, do you believe will be the primary user of this platform?

Yes. So we had covered this a little bit earlier when we spoke about is it -- is the platform sort of easy to -- it should be easy to use for nontechnical people. And the way we have designed it is that we are finding that teams -- everybody in the team, right from CMO to the day-to-day digital marketing manager can use -- is using CMGalaxy for recommendations, for budget management, for obviously the data insights. So basically, it completely cuts out their dependency to create presentations or build reports, right? And that is how we started CMGalaxy and started solving this problem because in the industry, most agencies even today end up spending so much time in manually putting together reports. And by the time those reports get created and by the time somebody -- a decision-maker sees the report, it is already too late. The marketing moment has gone. So this is a challenge we find across an entire marketing team, right from a CMO to the day-to-day campaign manager. And it isn't limiting to one sort of -- one person or one specific person in the team at all. In fact, it is very much a collaborative tool. It is a tool where everybody across the organizations, including creative people, including MarTech people, including day-to-day digital marketing guys, CMOs, AI -- the team members who may be using marketing AI tools, they all can work on the platform together. So that way, it is a collaborative tool. Next question, please.

Sir, the next question is from Mr. Ankur Gulati. The question is, what is GTM strategy and current status of rollout now?

Ankur ji, hope you're doing well. Good to see you here. So the GTM strategy is where we have been focusing on, adding sort of more resources as far as our GTM is concerned. We have gotten underway with a large lead gen exercise a few months back. And we are now sort of pushing GTM not across multiple channels, right? So it's a multichannel approach. We're looking at generating leads through participation and events in B2B. We are, of course, doing a rollout in terms of e-mail marketing. We are participating through, of course, paid marketing channels as well. Agam, maybe I can also request you to jump in here and talk about the rollout plan as far as GTM is concerned.

Yes, sure. Thank you. So from GTM aspect, like I would just structure it in 3 levels. The first level is like customer will see it and sign up. So basically, that's the awareness level. The second is when we will go for the conversion part of it, like customers are closing. And the third level is basically we can do for upsell and cross-sell kind of thing. So currently, we are in the top level of it where we need to generate awareness. And in the limited part, the cheapest or you can say the cost-optimized way to approach is, the first is exploring partner ecosystem of like Shopify, like WooCommerce and those kind of players whom we are working with it, where we are providing the connector and integration. So that's the one way. We have Priyankush here, so he's doing and heading that particular bit already with us and closing a couple of customers from that channel. The second bit we are going with another the most cost-optimized way of mass marketing is basically automation. So we are going for all in for cold outreach, but these are not typically cold. We are building our own automation engine using like Apollo, Lusha and these kind of sources, then we'll enrich those leads. And basically, automatically, we are putting drip campaigns out. And through those drip campaigns, we are getting like more enriched leads, which we can put on our paid channel kind of thing. So the GTM engine currently is all out on selective, cost-effective channel. Once we discover like what channel is working for us and where we are getting more closures, we will actually work towards it. So that's the overall part. And in terms of rolling out, it's already there. We have already started our pilots to that, and it's working in our favor. We'll share more results maybe...

Yes. Ankur ji, I also want to add that this is where the -- as Cyber Media as a group, of course, has a more than 4 decade old legacy, and that is something that we would certainly be also looking at leveraging to talk to the right decision makers and see how we can help them modernize their data stacks, right? So that's the -- this is something that is going to be a focus area as far as CMGalaxy goes.

Dhaval, am I audible?

Yes, you're audible.

What I was trying to understand is...

Sorry, you're audible, but your voice is not clear.

Is it better now?

Yes.

So when we interacted let's say, a year back, I guess, you guys are also planning to get someone senior hires in new markets to start campaigning, right -- not campaigning either digitally or -- so any senior hires getting done yet or not really in [indiscernible]?

Yes. No. So we have very much done that. That is already -- there are people who are part of the team, who are very much looking at that. And that's exactly where the focus on even sort of better technology, better data processing, better GTM are coming from that. So we have some of them on the call today, but that's been already done, I would say, at the beginning of this year.

And when you are reaching out -- just give us more color, are you reaching out to bigger accounts first so that you get better billing? Or you guys are not really focused on anything -- whatever comes away is fine? Or is there a thought on stab the bigger accounts first?

Yes. So we are looking at a double-pronged approach, right? So what we're doing is that the automation that Agam was talking about is focused on SMBs, right? And that's where we are looking at spreading a wider net. We are looking at engaging a larger number of companies and potential customers. And also, I want to add not just in India, in fact, looking at other geos as well. Having said that, when it comes to large accounts, we are also looking at identifying organizations where we are seeing clearly that there is an opportunity when it comes to MarTech and engaging larger businesses in trying to tackle sort of their MarTech issues where, of course, some of them have AI as a challenge, some of them have data silos as a challenge. And so those conversations are also on in parallel. So we have a two-pronged approach when it comes to that.

And when do you see this product contributing to your top line, in what time frame, in a month, 6 months, 12 months?

Yes. So it started. We've obviously onboarded clients. It's already started. We are generating bottom line as well. And we will be, I think, in a better position to sort of start probably giving Galaxy specific guidance from next year onwards because right now, as we had also discussed earlier, the base is relatively small. The other businesses contribute a lion's share of top line and bottom line. But we see this as something that will, of course, drive margin growth in the future for Cyber Media. So don't -- I don't have a specific answer for you on that today, but we do -- of course, given that we have the resources, given that we have -- we are doing the GTM, we've shown today a product which is significantly upgraded from what we spoke about maybe some 9 months back. So yes, there are a lot of, I think, relevant things where now the revenue should also start kicking in.

Perfect. And 2 last questions. What is the total amount of funds you have invested either as operating expense or capital expense or reaching wherever this CMGalaxy is? and second, how many paid licenses have you guys listed so far?

So Ankur ji, I won't be sharing -- I mentioned at the beginning of the call also that today, we're not sharing and giving that kind of guidance and data points. And we're not sort of right now giving that breakup. So I think we'll reserve that for this time. But I think as -- once we get more and more specific and more and more traction building on CMGalaxy, at that particular point of time, it will be meaningful to start giving that separately.

Okay. Congrats on the product. It has definitely come out really well.

Thank you very much for the kind words. Shikha, next question please.

Sir, we have 2 questions in the chatbox. First is from Mr. Vimal. That is, is there an option to store data generated [Technical Difficulty] and second question is from Mr. [Technical Difficulty].

Yes. So Vimal ji, the short answer is yes, absolutely. If you, for example, have Google Cloud platform or Azure, then we can deploy it there. Obviously, there's a little bit of data engineering and encryption required, but that's very much a part of how SaaS setups are. So yes, we can enable that. Yes, Shikha, the next question.

The next question is from Mr. Bhavesh Choudhary. The question is what are we doing for marketing and how are the transactions going on that?

Right. So we spoke about GTM a bit earlier, Bhavesh ji and what are some of the efforts that are underway. And I think that should answer that particular question. How are the transactions going? Again, that comes down to sort of giving specific numbers and guidance, which at this stage, because we -- see, as an agency, CMRSL also does -- as you would recognize, we do a lot of media buying. We do a lot of programmatic campaigns. We do a lot of data analytics, market research. So there are multiple revenue streams that obviously CMRSL has. And so sort of having this as a separate thing, we still haven't carved out and are giving specific and separate guidance on it. In some cases, these are also overlapped with other services that we are providing to clients, right? So that's one of the reasons why that is the case. From -- like I mentioned, moving forward, from next year onwards, we should be able to give specific guidance on our product development and related revenues as well. Shikha, any other...

Sir, we have no further questions in the chatbox.

Okay. All right. So it's 5:12. We've shot over the 1 hour we had set aside for this call. And I want to really thank everybody who took out the time on a Friday evening to step in and understand what we are doing on our product road map and development. Thank you very, very much. Again, heartiest wishes to all of you for the ongoing Navratra as well as, of course, the upcoming festival of lights. And with that, wish you all a very good, very happy weekend, and let's sign off. All right. Thank you so much.