Ops Cast
Ops Cast, by MarketingOps.com, is a podcast for Marketing Operations Pros by Marketing Ops Pros. Hosted by Michael Hartmann, Mike Rizzo & Naomi Liu
Ops Cast
Operationalizing First Party Data with Vishnu Vankayala
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Unlock the secrets of data-driven marketing with Vishnu Vankayala, the visionary founder and CEO of CustomerLabs. Gain exclusive insights into the world of first-party, second-party, and third-party data, and learn how to navigate the complexities of data privacy and tracking restrictions. Vishnu sheds light on the transformative power of first-party data, revealing how it can elevate your marketing strategies in an increasingly privacy-conscious digital landscape. Discover the game-changing shift from traditional tracking to server-to-server connections and the ways ID resolution can sharpen your performance marketing strategies.
Explore the burgeoning field of first-party data operations (1PDOPS) as we discuss the role of ID resolution in creating a cohesive identity across multiple platforms. Vishnu shares his expertise on unifying disparate system IDs to enhance lead quality and marketing performance. Learn how the synergy between CRM data and marketing operations can empower platforms like Google, Facebook, and LinkedIn to generate high-quality leads. This episode is a treasure trove of knowledge for marketing professionals eager to optimize campaigns and reduce costs while navigating the challenges of privacy regulations.
Elevate your networking game by tuning into our conversation with Vishnu about the power of LinkedIn for knowledge sharing. He shares invaluable tips on using the platform to connect with industry leaders and exchange insights. This episode promises to be a rich resource for anyone looking to harness the power of data in digital marketing. Join us and become part of a community that values learning, growth, and collaboration.
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Hello everyone, welcome to another episode of OpsCast brought to you by MarketingOpscom and powered by all the MoPros out there. I am your host, michael Hartman, again flying solo, as we are approaching that. We're now well within a week to Masa Palooza 2024. So hopefully we will see many of you there Joining me today to catch us up on what is happening with first-party cookies and all that entails. We'll also talk about, I think, second and third-party cookies, but we'll get there, but also, I guess, just first-party data in general is Vishnu Venkayala. Vishnu is founder and CEO of Customer Labs and for those of you who were at Mopspalooza 2023, you may recognize that name from last year, when they won the award for most innovative marketing technology presented by the MarTech Weekly 100 Awards. So pretty excited to have that. Vishnu has held several roles in higher education after starting his career in software development. So interesting career path. Vishnu. Thank you for joining me today.
Speaker 2:Thank you, michael. Thanks very much for having me here and hi everyone who is a great fan of MOps.
Speaker 1:Yes, we're ready to have you All right. So I know we said we would talk about first-party data and first-party cookies and whatnot, but I think it would be useful to take a step back and talk about what kind of what that let's do some definitions right. What does that mean? There's I think I've, I know I've definitely heard first party and third party. Those will make sense, I guess. Data and or cookies, uh, I think occasionally I've heard second party. Um, but maybe you can help us with a baseline like definition of those two or three, you know you can clarify if there should be two or three only and what's the difference between those.
Speaker 2:Absolutely no. So usually most of us just get understanding of first party, second party and third party data and when it comes to first party, anybody who is interacting with the particular business and they would be able to eventually share that information is entirely first party, 100% concentrated and 100% shared by the first party user when they're interacting with you. So, for example, right now we are on the podcast, now you know me and I'm sharing my name, my details. This is first party. And let's say you are inviting someone to the podcast through a friend. That is second party data. So, say, michael, I know Vishnu and Mike introduces me to you. That's second party data. So I'm a friend of a friend.
Speaker 2:Third party, entirely not related. I shared my details with somebody else and they share the data with you in terms of, for example, hey, these are the group of people you might be interested in talking to you. Why don't you just reach out to them in a more non-aggressive way or more privacy-centric way? So that is the third-party data, and most of the businesses interact with first, second and third-party data without them knowing, without them, day in, day out, and the primary angle is whenever someone shares the data with us, how do we eventually collect it, store it and activate it? Because it is 100% concentrated, it is your data, and how effectively you can use it is the whole game here.
Speaker 1:Got you. I'm just curious. So I think I get the distinction between second-party and third-party data the way you described it, but from a practical day-to-day technology standpoint it seems to me like there wouldn't be all that much difference in that. But am I missing a piece of this?
Speaker 2:No, so I mean there will be a slight difference. The second party is basically like we are collaborating with, let's say, uber. Uber shares the data with the driver. That's primarily second-party data. So you know that they will be sharing the data with someone else and that is the second-party level. So we both know we are in a contract and when I share the data with you, it automatically shares, for example, amazon. Amazon saves the data with the delivery partner. What is the data? So it could be just a phone number, it may not be the name, but how do they share the data? Is the whole idea?
Speaker 1:Okay, they share the data is the whole idea. Okay. So there's sort of maybe contractual is an extreme, but some sort of either, I guess an explicit agreement that this data that you're sharing with that I'm sharing with you, vishnu, that you are able to share it with other entities, that you also have some sort of agreement with. That's right In terms of how they would handle that. Okay, that makes sense, whereas third-party data is also shared, but maybe done so without that. Maybe there's some implied consent a little bit Okay.
Speaker 2:So eventually, if you take ad algorithms or ad platforms not algorithms so eventually what happens is we are sharing as much data as possible, but then these guys don't reveal the first name or last name, so eventually what they do is based on the data. Whatever we collect, they start showing the ad and eventually, without sharing the whole detail, so that's the third-party kind of data, how they use it. And then you have outbound email marketing or there are companies which can identify the users when they come to your website. It is third-party data sharing. So someone comes to the site. I will give the email address. That is entirely third-party data. So that is not the data anybody owns. It's just that they enrich the data and give it to address. That is entirely third-party data. So that is not the data anybody owns. It's just that they enrich the data and give it to you based on the third-party identifiers.
Speaker 1:Got it Okay. So that's really helpful to clarify that, okay. So the other piece of this which kind of surprised me is that when you and I talked before, you talked about first-party data, that we can have first-party data both unknown and anonymous, or unknown users or, I guess, maybe mostly visitors. So I'm trying to wrap my head around that, because I thought first-party data meant we knew who you were, but it doesn't sound like I understood that right.
Speaker 2:Yeah, no, I mean 99% of the people. When we speak to them, everyone thinks whenever someone is identifiable, he's first party data. That's not actually right. The understanding is anyone who lands on the website. If you are able to identify them, like, for example, based on a cookie or based on an identifier if you're able to place it across, at this point, what you don't know is their name or PAI personal identifier information that's what you don't know. But if you can collect it and if you can activate it, that's still the first part of the data. But the question is how can you collect it? How can you activate it at scale, despite someone is actually sharing their PII? So that's the identified users and non-identified users. Who is coming to the site is still the first-party data.
Speaker 1:Okay, so if I'm someone and I'm going to a website for the first time, they may identify me with a cookie, some sort of identifier, but until I have an interaction of some sort where it reveals my PII or other data about me, then I still remain unknown or anonymous from that standpoint. Exactly Okay, got it.
Speaker 2:The major angle here is how do we keep those identifiers, because, let's say, you're going to have 30,000 or 40,000 people coming and landing on the website. How are we going to keep those identifiers intact? How are we going to use them so that we'd be able to reach out to these customers who came to your site and share that data?
Speaker 1:Right, yeah, I can see how that would be very valuable. All right, so it's interesting that we're having this conversation about the topic of first-party, third-party, second-party data at this point, because I think it was what 18, 24 months ago that Google was talking about in Chrome. They were going to disable or remove its support of third-party cookies, right, I think that was basically it, but then it got. I guess I'm not even sure right now. It was either postponed or completely taken off the table, so maybe you can help. What is the current state of that?
Speaker 2:And what do you expect the outcome or what do you expect that's going to happen in maybe the near-term future, mid-term future? No, I mean, google eventually lost their whole. I mean they decided not to deprecate their third-party cookies anymore. So that's the latest information, what we have. But whenever someone thinks of third-party cookies, they almost assume that it's not privacy-centric. That's the way the narration has been built by competitions of Google.
Speaker 2:And what Google intelligently started doing is they started bringing in consent a lot into their entire ad platforms. So, for example, the moment you land on the website, especially in Europe or GDPR-oriented countries, you have to give a consent, even to identify you, and without giving the consent, there is nothing you can actually pass back to Google or Google AdWords, or even Facebook, for that matter. So the Google has taken a very different approach, saying look, we will use third-party cookies, but we will use only when the user is consented. And I think it's a fair approach, because you still wanted to reach out to the people who is coming to the website, who is sharing the data, but with the consented mode. So they launched new technology.
Speaker 1:Can I interrupt real quick? So are they doing that global Like it's just a global decision, that that's the way it's going to be, that global like it's just a global decision, that that's the way it's going to be? Or is it only in more regulated environments like Europe, where there's GDPR, castle in Canada, etc.
Speaker 2:Yeah, no, you're right. So right now the consent is highly. I mean, google has made it mandatory in GDPR regulated countries, especially in Europe and UK, whereas in the US still the consent is not highly. Google did not make it mandatory in non-GDPR areas. I foresee that that will be changing pretty soon because Google will start having those consents in pretty much in all the countries, eventually based on the regulations, based on the privacy laws.
Speaker 1:Yeah, I mean, it's me Just the way I think about this stuff, right, I want to keep it simple. I would probably try to keep it as simple as possible. Do the same thing globally, then how you use that is is a different thing. You know, you could choose to. I guess, for lack of a way you say, way of saying it, you ignore, right, some of that if you didn't get explicit, um consent about that, force people in the us or whatever. But absolutely okay, yeah, so so as far as we know, right, right, google doesn't have any new plans to restrict third-party cookies through Chrome.
Speaker 2:At this moment. Yes, Interesting.
Speaker 2:But what I foresee happening in the background being in this tracking, profiling kind of technology in the background, the way Google and Facebook started moving their whole tech is they're moving away from the browsers and they started moving into server-side angles. So, for example, google recently launched something called 1P domain tracking, so first party, so all the tracking will happen from server to server and enhanced conversions, which is the way of identifying the user who is doing what on the website, and similarly, consent mode is another big thing which Google has launched. So, although they don't, they're saying they're not going to deprecate the third-party cookies, but the usage of third-party cookies inside the Google technologies or that platforms will eventually go down even without us knowing, and having a right technology to maintain all these data is quite important.
Speaker 1:Okay, I will admit I am not sure how that server-to-server piece works with a user going to a website, but I know that it's not like I'm going directly from my computer to some server, right, there's other hops along the way. I assume it's something related to that. Okay, yeah, which makes sense. Okay, and I don't think we need to get into the rabbit hole of that kind of level of technology, yeah, Okay. So let's bring it back to what? Into the rabbit hole of that kind of level of technology? Okay, so let's bring it back to what's the impact. So, for most of our audience, right, marketing operations professionals how should they be thinking about using first-party data? Maybe they're not doing anything yet.
Speaker 1:Most people out there, if they've got a marketing automation platform, they've probably got some sort of tracking script that that works with that. You know, I know, I know for sure Eloqua and Marketo do, I'm sure HubSpot does, and I'm going to assume whatever they're calling Salesforce. Salesforce is Pardot stuff nowadays. If anyone's still using it has something like that too. But that's essentially, I think, in most cases, third-party data. I think there are some options on those to turn it into first-party data, but it's kind of getting into gray area for me in terms of how I understand it. But anyway, long story short. How should our audience be thinking about first-party data? Should they be? If they're not actively doing it, should they be pursuing it? Is there like what are the benefits of it versus third-party data? Should they be? If they're not actively doing it, should they be pursuing it? Is there, like what are the benefits of it versus third-party?
Speaker 2:data, that kind of stuff. Yeah, so we just touched base about the server-to-server connections, right? So what happens in the previous days? If you want to track something, you place a JavaScript inside on your website and it loads on the browser and starts picking back that information back and forth between that platform, so the analytics platforms, et cetera.
Speaker 2:And now that browsers are restricting such kind of behavior, tracking most of the companies like, for example, google or Facebook they eventually started working on the server-side tracking and with the marketing ops professionals when I met them, when I saw them, it's primarily oriented towards maintaining the CRM, running email, marketing aspects of it. Those are the kind of areas they were focusing a lot and I think it's time for them to start looking at this also as one of the functions, and that particular function will focus more on how do we start tracking the data from the website and how do we unify the customers whenever someone is landing on the website and becoming a lead, and whenever someone becomes a lead and becomes an opportunity, how can we bring that back and push it back into the platforms. So, if you look at it, how do you use it? So one is optimizing the campaigns not only for the leads, but also for the bottom funnel conversions, like opportunities or deal one. And similarly, whenever you try to ID those users who are coming and landing on the website, how can we use this in audience for retargeting purposes and obviously to do all those things?
Speaker 2:What we need is a very integral part, something called ID resolution, and that ID resolution is what happens between the systems. So, for example, the Google, the Facebook or LinkedIn should know Michael has landed on the website and I want to target Michael or show an ad or give a nudge on Google and LinkedIn that hey, this is the ad you are interested in, can you go and book a demo? So when you want to act on those retargeting campaigns, this is a primary aspect. The ID resolution would be the primary aspect. Someone should invest. So, marketing operations so far they have been looking at GTM as one of the area and then they add a line between performance marketing and typical sales-led organization. Now the marketing operations can also bring the data back into performance marketing and be able to enable performance marketers a lot with the data, what they collect. So that's the shift, what we are looking at and what we are trying to make in the market.
Speaker 1:Sorry, just a clarification for you. When you say performance marketing, what does that mean to you? I don't want to make any assumptions here.
Speaker 2:So performance marketing is basically people who spend media buyers, so media buyers who generate the leads by running ads on Google and ads on facebook, linkedin, tiktok, wherever the platform they are, and that's what I meant by performance marketers okay, so it might also be, I think, called demand gen or lead gen or digital marketing as well.
Speaker 1:Right, okay, got it. Okay. Yeah, um, okay, that makes sense. This ID resolution stuff, though, so could you maybe? I have a pretty good idea what that means, but maybe could you drill down on that a little bit and you know what is it and why. Why is it?
Speaker 2:so important to this whole bit with first party data. Yeah, so ID resolution primarily, when I speak with sales-led organizations who have been investing a lot on Salesforce, eloqua, marketo kind of areas, what they're trying to do is I have a person in Marketo and I want the same person to be in Salesforce, so use the same email address to create a unified record. Now I just spoke about the consent a couple of minutes ago. So a user lands on the website let's say a user gives consent, saying, hey, look, you can use my data for tracking and without the ID resolution on that particular moment, you won't be able to send that consent parameter back into Google. When the user becomes a lead, and whether it is giving a consent or denying a consent, it has to start from the day it lands on the website. So right now you're an anonymous user. And how do you create an identity for this user is very, very important. So one you create a first-party identity who is an anonymous user, which we call it a pseudo ID, and then the user becomes a known user. He enters back into the CRM and this is the point where you have to attach the pseudo ID with the real ID, which can be Salesforce ID, it can be HubSpot ID or any other CRM, for that matter. And when you send them back, for example, now, today I'm a lead and tomorrow I became an opportunity, and I have to push this opportunity back into Google or Facebook or LinkedIn, and now the LinkedIn should know whether you have given a consent for me to use that data or not. So this whole part is being connected by ID resolution.
Speaker 2:So, generally, for any systems to work, id resolution is mother of everything and without getting that piece right, you won't be able to do this properly. You will see results, very mediocre results 50, 60 percentage returns. But if you want to push the markup, the id resolution piece is something you have to get it right, starting from how do you place the server, set cookies so it stays intact it stays there literally forever and how do you collect the data? So, for example, you click an ad, google creates something called google click id and Google creates something called Google Click ID and Facebook creates something called Facebook Click ID and LinkedIn creates something called LIFAT ID. How do you collect it?
Speaker 2:When you're an anonymous user and when you become a lead, how do you attach it? And when you make an opportunity. How do you attach all this information and push it back into that platform so that it knows? These are the kind of users who are becoming opportunities. These are the kind of users who are becoming opportunities. These are the kind of users who are junk. Let's not target more so that's how you can connect the dots between the systems.
Speaker 1:Okay, so this is like it's generating a master ID that connects all the other individual systems IDs. Okay, I'm oversimplifying it, I'm sure, but it seems my small brain is working.
Speaker 2:That's exactly what it is. So you create one ID and you collect all the IDs and put these things together and whenever you send that information back into that particular system, you make sure you're sending the right ID back into the system, because LinkedIn doesn't know the Google ID, facebook doesn't know the Google ID, so you have to send the right IDs back into the systems.
Speaker 1:So can it also help with sort of connecting the dots between, say, someone's work email address and personal email address?
Speaker 2:Well, the Google and Facebook knows it. We may not know it, but they know it. So when you send the data back into Google and Facebook, eventually they would be able to figure out personal email address and work email address, but as a first-party data we will know only whichever the data is shared by that particular user.
Speaker 1:Okay, that makes sense. Cool, All right. Well, that's really helpful. So one of the things I think we talked about is that, to use this at scale, you need to operationalize it, and you used the term with me, first-party data ops, so again, I can imagine what that is, but why don't you give us a definition? What is that? Why is it important?
Speaker 2:Yeah. So again, like I just mentioned, marketing operations professionals, so far they have been helping a lot. The sales team not primarily helping out. I wouldn't say not primarily, but as far as I know they couldn't help performance marketing team or media buyers or digital marketing team a lot. Now, with this data, can we power the media buyers or performance marketing team to get the maximum? So let's say, for example, the sales team says I have a problem with quality, can we help the digital marketing team to generate high-quality leads? And if they want to reduce the CPU, can you use this 1PDOPS to do it? So that's where we are carving out, slicing it down.
Speaker 2:Saying 1PDOPS is basically the future of advertisement and collecting it, activating it is very important and there lies a lot of technology in between. It's not a simple solution. You have to work on multiple bits and pieces so that you collect it, store it and activate it in a seamless fashion. So what we are anticipating in a few years is the 1PDA ops will eventually become a division. Every single company, whether it is e-commerce or whether it is a non-e-commerce company, will have one specialist who will be working on this 1PT ops, but it's very, very in a specialist role.
Speaker 1:It makes sense. Okay, so there's conceptually, first-party data operations and then there are platforms which I think enable this, maybe even yours In my head. I'm trying to kind of compare and contrast that to something that we actually just recently talked to somebody about again customer data platforms, which seems like it would be a natural place to do that we actually just recently talked to somebody about, again customer data platforms, which it seems like it would be a natural place to do. That ID resolution, some of those things as well. What's the difference? What makes one better than the other?
Speaker 2:This is the exact problem. What we have been facing right. Cdp is not well defined and in the last two to three years, everyone started calling themselves a cdp marketing automation platform. Yes, we are a cdp email marketing platform. We are a cdp data warehouse activation platforms we are a cdp. So everyone started calling themselves CDP and I love the term CDP because I came across the term CDP somewhere about 2017, 2018. And it's like an awesome feeling to have some name for everything we have been doing. But everyone started jumping into the bandwagon calling themselves a CDP and we were like, okay, fine, this is not something where we want to be so. So the definition was missing. And when you say CRM, you know what the CRM does. When you say marketing automation, you know what the marketing automation does. When you say email marketing platform, you know what it does.
Speaker 1:I would argue that when you say CRM, there's actually lots of different things going on in people's heads. But I digress.
Speaker 2:I agree. So it could be the same issue. What happened with the CRM? So CRM is supposed to do a basic functionality and eventually it started moving away. The same thing might be happening with CDP, and it started moving away from what it was, or what at least we wanted to define it. And then we thought, okay, fine, we don't want to be in that competition. Either we should have enough money to define the CDP. This is what the CDP is like, how big companies like Salesforce are trying to do, or some of the companies are trying to do. We don't want to get into that war, we don't want to be in that particular area, and we decided let's focus on a small area where we can create impact, which is nothing but one video Collected, stored, activated as simple as that. So just stick there.
Speaker 1:Okay, so see if I can recap this. So if I'm talking to a customer data platform and they are saying they can do something like first-party data collection and ID resolution, yeah, that is a sort of a, that's a piece of the puzzle. It's not probably the full thing of what a CDP does. Whereas the first-party data ops is primarily that sort of collection, identification and then how you leverage it through some channels, dataops is primarily that sort of collection, identification and then how you leverage it through some channels.
Speaker 2:Yep, no, you're exactly right. So that's the idea, but then now everyone calling themselves CDP lost that definition, so eventually it's becoming very cloudy in the customer's mind. It makes no sense to go and explain that. The moment we started positioning as first party data ops, there's a clear definition, there's a clear value and we are able to close deals much faster than calling ourselves a CDP.
Speaker 1:Okay. So if I'm sitting here listening to all this and I'm thinking well, google's not getting rid of third-party data, our performance marketing activities are performing well, you know why should I care about this first-party data and operationalizing it? What would be your argument for why our listeners should be focused on this if they haven't already? Is there any tangible benefit? Because anything like this requires effort, money, change to an organization to put in place.
Speaker 2:No, it's really a good point. That's what we have been advocating Since 2023, early 2023, january, google started pushing AI a lot, facebook started pushing AI a lot, and LinkedIn they just started very recently, maybe two, three months ago. So what they really want is hey, you have the best customers, give it to me. You have non-converting customers give it to me. And you have high-value customers give it to me and I will go and find similar customers like that. So how fast can you do it? How soon can you do it? How well you can do it is the whole idea.
Speaker 2:So, for example, you click an ad, you should collect that GCClick ID and you pick an opportunity. Can you send that back into Google in a matter of seconds? So that's where this first-party DevOps comes into play, and if you're not making those connections between the systems, it's basically saying I mean, like you are just brushing out with whatever the information Google is trying to give it to you without powering the data. So Google recently came up with something called Data Manager. The Data Manager is purely how can you send the data back into Google Ads so that it learns from your business, which is entirely first-party data, and it brings more customers, like, whichever the way you want. You want high-value customers, it will go and be able to find high-value customers. If you want a category of customers, it can actually go and bring a category of customers. You can actually go and bring a category of customers. So that's what's changing here, with first-party data.
Speaker 1:So that sounds like a speed and efficiency kind of benefit. Are there any other like I'll call it financial-type benefits that might come from something like this?
Speaker 2:Yeah. So speed, efficiency to do what? So, ideally, if you want to reduce the CPL, or if you want to reduce, let's say, for example, optimize for more high-quality leads, which we generally call it as LTOs lead-to-opportunity rate, so how do you increase the lead-to-opportunity rate? Only by bringing the high-quality leads into the funnel. So can you close the loop, the feedback loop, by sending the data between your CRM and Google Ads. So, in terms of real money, people will start seeing can you reduce CPL cost per lead by X amount, or can you increase the opportunity ratio by X amount, or can you increase the number of leads we would get? So all these would be the direct impact of ROI, not only the speed and efficiency, but the direct impact on the marketing, direct impact on the revenue.
Speaker 1:So just okay, all those things would be great. How would a first-party data ops platform or enabling first-party data ops to scale, like how would that actually do that? I'm trying to connect the dots to a reduction in cost per lead, or you said, I think, something like I'm going to paraphrase here. I think what you meant was like higher converting opportunities or something like that.
Speaker 2:Yeah, so high quality leads is the whole game, right? So literally two weeks ago, linkedin has switched don't optimize for the leads, but optimize for the quality leads. And similarly in Google, when you set up a campaign, you don't only go after the leads, you can also go after the high value leads. So now you collect the data, you click the ad, you know which keyword you have been searching for on Google and you have been marked as an opportunity. And now that opportunity needs to be told to the system so that the AI understands okay, this is the person who these kind of people is, what these businesses are interested in, and it will go and automatically adjust the bidding in the background. Be able to bring in leads similar to that.
Speaker 2:That's how you increase the lead to opportunity percentage and when you want to reduce the CPL and this is one of the insurance companies in Canada what they have started doing is they started working on the retargeting campaigns. So retargeting campaigns whoever comes and lands on the website. They started working on retargeting campaigns because of the audience who came to the website did not make the decision. It automatically started bringing their leads lead cost quite low. And the third aspect is lookalike audiences on Facebook and LinkedIn. So you send the lookalike audiences back into LinkedIn and Facebook and automatically you would be able to run campaigns to attract more people like them. So that's how the loop is being closed right now, with a lot of feedback back into the ad systems.
Speaker 1:So see if I'm understanding this correctly, then See if I'm understanding this correctly, then. So by doing this and getting this sort of rapid feedback, I guess from both systems, you're able to better target where you're spending, because I think the majority of the costs. Well, let me clarify, because I'm not super familiar with linkedin or facebook, where the costs are, is it based on, uh, impressions or clicks, or how is that? How do you, how is it the cost drivers for those?
Speaker 2:both impressions has, uh, the cost, or the click has the cost. But the final measurable cost where you can actually control is the CPL. How much are you spending for generating a lead? That's the final cost. So if you are able to reduce that cost by sending the right kind of feedback back into the system, that's the big win for most of the companies. That is one part of the problem one part of the problem.
Speaker 1:I assume, then, that if it's based on both the audience size, the target so your impression numbers, as well as the people, the conversion of those to click-throughs and ultimately to leads, that what you're able to do with this is then to better sort of narrow those windows. I don't know how. I would call it micro-targeting, but essentially you're targeting a smaller group, right, so by default, you're already going to be reducing the cost if the major driver is the volume of people you target, right, so you can, you're going to get, and you're probably a. There's probably a higher propensity of matching, say, say, the lookalikes right, matching people who look alike because you're providing a more detailed set of data and behavior to the system to be able to do matching, especially as algorithms get more sophisticated with AI, et cetera.
Speaker 2:That's exactly what people have been doing, right? So people have been setting up campaigns into multiple segments, multiple ways to identify which cities are actually giving more leads, which kind of person is giving more leads. Now that everything has become AI-driven, how can you transfer the knowledge of whatever you have been seeing on the CRM into the system is the whole game. So now, whatever you said is right, but the targeting options interest-based options are becoming very, very low right now. So let's go back to the privacy, right? So privacy is now stopping us targeting a very small subset of people where you know they will definitely convert. So now that is not there. How can you train the AI algorithm in the background with high quality leads? So you have to send the data back so AI learns this is a good lead, this is a bad lead. This is a good lead. This is a high value lead, this is a low value lead. So that's the feedback loop, is what we're trying to do.
Speaker 1:Oh, okay, I get it. So it's not just like click-throughs but also like downstream. This person we targeted in this campaign as it looked like they clicked, they eventually became a lead, but this other person displayed it clicked through, didn't become a lead. We send those two back and it gets smart. It kind of looks at the differences in those two people that were initially targeted and gets smarter about okay, well, if we make any volume, I can imagine right, like single points probably are not indicative, but if you get enough of a pattern, you can get better. Okay, yeah, that makes sense.
Speaker 2:And this all connects back to the privacy right. So the third-party cookie is still not going away, but it still goes back to the privacy. Because of the privacy loss, the interest-based targeting, the audience-based targeting, everything is now taking away from the customers. Now that these are all taking away from the customers, ea has to do the job, which means you have to transfer all the knowledge you have in the CRM or the business back into the ad systems. So that's the heavy lifting for you.
Speaker 1:So that's how the whole thing is connected. It seems I was going to use the word obvious, but it feels a little bit obvious that if you have first-party data data, that is, specifically things that you're interested in collecting about your audience and the people who interact with your organization that that would be more valuable than third party less directly connected to your business data. I mean, it seems like a fairly obvious thing, so I assume that's more or less true. Let me ask you this. So one last thing Do you think is there a difference in how you would think about this for, say, b2c versus B2B organizations?
Speaker 2:Yeah, B2C needs a lot of feedback, pretty much in real time time, because we are talking about purchases, impulsive purchases so B2C needs much more real-time data for the campaigns to perform day in, day out. It's almost like stock. That's how I see. When I speak with marketers. They almost treat the media platforms like stock trading, day in, day out. They are always in pressure and they need a lot of this data going in, going out. B2b is slightly relaxed. It's okay if you could actually feed that system back, maybe a few hours later or a day later, but you still need to work on the whole system. So B2B is slightly complex because the journey is not intact. People land on the website today, they become a lead after, let's say, 10, 15 days and then they become an opportunity after 60 days, so the sales cycle is pretty long. So you need to have strong systems to track everything day in, day out. But at the same time, the difference is a huge amount of data in B2C and a little bit less data in B2B, but two different beasts altogether.
Speaker 1:Yeah, okay, that makes sense, and it sounds like it's not necessarily a difference in the data you use, but one. It's a difference in, maybe, volume, but also in how and when you use it to optimize what you're doing from a go-to-market standpoint.
Speaker 2:Yeah, that's a good point, right. So for B2C the optimization works in a very different way. Can I get more high-value customers we call it as high AOV people who can spend, let's say, three times of the regular AOVs and for us in the B2B, can I get a qualified lead? So those differences act very majorly. So how they optimize the campaigns works in a very different way in both the angles. But end of the day the feedback is same between both the systems, but the angle they take is entirely different.
Speaker 1:Got it All right. This has been really for me, has been helpful to get out me. It's been helpful to get out to speed on what's going on in this world. So we covered a lot of ground. Is there anything that we didn't cover that you want to make sure that our audience hears about?
Speaker 2:Yeah, I mean, I think in the next one or two years you will see all the ad platforms moving into service tracking and all the platforms would be asking for more data, more first-party data to close the feedback loop. So it's a very good time to start on this understanding of 1P, deops, service tracking, capi, enhanced conversions etc. And anyone who is interested. They can always have a look at chat with us to understand what's going on here, happy to share that knowledge with them.
Speaker 1:Perfect, all right, well, so let's wrap it up there, and maybe this will be. You led me into the next question, which is, if folks want to keep up with what you're doing and talk about, or this space in general, what's the best way for them to do that? Linkedin.
Speaker 2:LinkedIn would be the best place. We are quite active on LinkedIn, so they can find me out with a simple search Vishnu Customer Labs We'd be able to find me, connect me on LinkedIn and happy to share the knowledge as much as possible.
Speaker 1:Fantastic. Vishnu, thank you so much for sharing this. Got pretty techy, geeky, but I think it was well worth the dive into it. So thank you for that. As always, thank you to our audience for continuing to support us with your listening and rates and things like that. As always, if you have ideas for topics or suggestions for guests or want to be a guest, please reach out to Naomi, mike or me and we will take you up on that. Until next time, everybody Bye.
Speaker 2:Thank you.