Transcription
Aderson Oliveira: I had an awesome conversation with Venkat Nagaswamy about what account-based marketing is and how AI can help to scale ABM initiatives. He also mentioned that one of the key aspects of a successful ABM initiative is content that speaks to the right target audience. Lastly, he talked about the fact that AI is a bigger change than anything that we've ever seen before, and we are just getting started.
Hello, hello, Aderson Oliveira here. This is the OuchSourcing Podcast where I talk to experts, to business owners, to influencers, to people about outsourcing and the trends in the market as well. Talking about trends, no bigger trend out there than AI, and that's the reason why I have our guest today. His name is Venkat Nagaswamy, and he is the founder and CEO of a company called Mariana. Venkat, welcome.
Venkat Nagaswamy: Good to be here, Aderson.
Aderson: Very good, very good, Venkat. By the way, Mariana is an AI-powered account-based marketing platform. Now, I'm going to start with the basics here, Venkat, because to be honest, the first time that I saw ABM was when I landed on marianaiq.com and I said, "What the hell is ABM?" So, Venkat, let's educate myself and my audience as well. What is ABM?
Venkat: I always say ABM is old wine in a new bottle. But, AMB basically stands for account-based marketing, and as the name implies, it's basically about orchestrating a series of activities around a given account, a series of marketing activities which is tied around an account that brings a greater alignment within sales and marketing.
If you really think about it, any sale is, by definition, account-based. A salesperson goes into an account, they figure out who -- in any B2B purchase that is people involved in the purchase. So, a salesperson goes into the account, they figure out one decision-maker, then maybe they go out and figure out all the influencers involved in the account, and finding this whole buying committee or the purchase committee, right?
So, any sale, by definition, is account-based, and therefore, this whole movement around ABM is being able to then say, "Given that any sale is, by definition, ABM, what are the kinds of marketing activities that we can surround an account with and thereby help sales close better?" Now, you can ask yourself why is this becoming very important, very current today.
By the way, the definition of ABM, as laid by the Marketing Association was done 25 years ago, so it's nothing new. The reason why it's become, and this is my own take on it, take it for what it's worth, before, let's say, 10, 15 years ago, when you talked about B2B marketing, it was primarily centered around events, third party events, first party events, and so on and so forth. That and branding were pretty much what B2B marketing was.
In other words, 10 years ago, 12 years ago, with the rise of marketing automation, you had a whole bunch of people, marketers who grew up on inbound marketing, which is you write a lot of blogs, you write a lot of content that engages your audience, and therefore, brings the audience in. And that, we marketers have been doing very effectively for the past 10 or 15 years.
Now, over the past five years or so, once that movement started happening, apparently, there's another movement around having marketing justify its existence, so to speak, and immediately, that translated into sales, and therefore, how does marketing assist sales? Now, when you are thinking inbound sales and inbound marketing, you did not quite have control over what accounts were responding to you, who was responding to you, what personas were responding to you, and so on. So, the leads that we marketers were sending to sales were not that robust.
So, with this need for alignment and with this need for accountability, marketing has now needed to go and reinvent outbound marketing, and to be able to start getting engagement and connection with the accounts that the sales guys really care about. Those are the motivating reasons as to why ABM has become big in the past year or two, and it's going to continue to become big. And this, we believe is the future of B2B marketing, a combination of inbound and outbound, and outbound being primarily on an ABM basis.
Aderson: So, Venkat, if I may ask, what is the difference, then, with just the traditional outbound sales as compared to ABM? What is the difference there? What else is there in the ABM model that is not already present in the outbound sale?
Venkat: A couple of things. Usually, in traditional account management and sales, you'd go try to figure out which accounts to go after, who in the account to go after, and how to do the sales to them, and predominantly, it was either email-based, or phone-based, or event-based. So, the other types of activities that you can do today have to do with targeted advertising, targeted advertising in the form of display ads, you can do the same for Google Adwords, you can use the same thing on LinkedIn, Facebook, Twitter, all these new slew of these digital methods that you've got have allowed you to start doing a more targeted outbound.
Let me be slightly more precise on that. Traditionally, when you try to do B2B advertising, you went to, let's say, a publisher site and you'd place an ad on that, right? Now, with identity-based marketing becoming bigger and IP address to company mapping becoming bigger, you're now able to target specific accounts and people within specific accounts, people with certain titles, certain interests, certain persona. Companies like ours are using AI to be able to figure that out, right?
Traditional marketing or traditional sales had to do with phone calls and emails. Today, you can layer it on with a whole bunch of other online marketing activities that you didn't have an option to do earlier because of better targeting capabilities that you're getting today.
Aderson: Let me see if I got the idea there. So, what you're saying is that, now, the marketer is able to reach that person from that function on that company specifically. I mean, laser sharp. Is that what you're saying?
Venkat: Yep. The way to think about it is, targeting capabilities today now allow you to find the account, found the specific people or set of people within the account and target just those people using targeted advertising, and that is the level of specificity that you can get today that you couldn't even two or three years ago.
Let me address a couple more things on that. When you think about digital advertising, you can proudly think about it two ways. One is identity-based advertising, and the other one is anonymous advertising. By anonymous, I mean cookie-based or IP address-based, and that is traditionally what we are doing a lot on. Now, in the past, let's say, five years or so with Facebook, LinkedIn, and other things coming on, you have an ability to target the individual or a small set of individuals in a very targeted laser-focused way because of this identity getting established on the web, which you didn't have until recently.
That is one of the big things that's happened in the last, let's say, three, four, five years, which allows you to be able to target the individual in a much more laser-focused way than what you could do earlier.
Aderson: That brings me, Venkat, a question pops up in my mind right away is that if you are laser targeting one individual, how does that scale? Are we talking about big ticket items, big ticket accounts that it's really worth going after that individual, that company? Because, again, it comes to mind right away, how do you scale an initiative like that?
Venkat: Yeah, great question, right? So, this is where AI and all these modern analytical techniques come in. To your earlier point, which is that a lot of ABM sounds a lot like traditional outbound sales, right? So, if you think about what a good salesperson does when you give them an account, they first go figure out, "Okay, which account is a good account based on a parameter that I've established in that head?" and then they say, "Okay, typically, for these types of accounts, I have these types of personas involved in the purchase, and therefore, I need to go target them." So, that's what a salesperson does.
Now, because of AI, you can do the same exercise at scale, and you can do this for thousands of accounts without needing a huge human capability to be able to do that. Of course, there are some people who are doing it based on human beings. There are people, companies like Upwork, who have a whole bunch of people that you can get for hire, and they do these kinds of work. However, you can do the same thing with AI and replicate a lot of what a good salesperson would do at scale with ABM, which is why we always say, "Because of AI, ABM, at scale, becomes a reality that wasn't the case, let's say, two years ago, three years ago."
Aderson: I love the fact that you brought there, Upwork, because our audience is used to -- what is the link between AI and outsourcing? I usually say that the traditional outsourcing model, we outsource to human intelligence, and now with AI, we are outsourcing to artificial intelligence.
Venkat: Exactly, right? So, it's very instructive to see, if you see how outsourcing has grown over the past 20, 30 years, you’re going to see a similar pattern in how AI is adopted over time. Let me explain what I mean by that. Outsourcing happens for two or three reasons. One reason is that you don't the capability within the company, secondly, you don't have the capacity within the company, and thirdly, even if you do have the capacity, you might say, "Hey, for cost reasons and other things, I might want to outsource it." So, those are some of the reasons why you would outsource.
Similarly, AI is going to get adopted in these types of places, right? What I mean by that is when I say ABM had scaled from Mariana, when you want to do it at scale, it's very difficult to do it on your own within any company. However, AI can deliver that at scale. Or, you can outsource it and have it delivered at scale as well.
Second point is capacity. So, in some areas, let's say, for instance, inspections. Actually, inspection and auditing are great examples. When you look at a factory floor, depending on, let's say, the value of the goods being inspected, you would either inspect every piece, or if you are looking at a car, every car gets inspected. On the other hand, if you are making chocolate, each of which costs you $1, you don't inspect every chocolate. You inspect every random, every 10th or so.
Similar to AppZen, where auditing on expensive quotes used to happen randomly. Today, you can inspect it every go. So, where I'm coming at is there are certain cases where we have not deployed human intelligence because human intelligence is too expensive, or we don't have the capacity to do it. In which case, you might want to outsource it either to a human being or to AI. And certain areas where even offshoring to another country, or even outsourcing to a different place, human intelligence is still going to be more expensive than AI, and those are the places where AI would take off. AI would take off in the capacity-concentrated area. It's going to take off in places where the risk of missing certain things is not that great and the reward is fairly good. So, you do it.
For instance, again, going back to the expense report, monitoring if you make a mistake once in a while, it's not that great. Even for targeting, for that matter, in marketing, if you get 95% targeting right, that's huge. But, if you get 5% wrong, that's not that big of a deal. At the same time, you don't want to deploy AI to detecting, or immediately relying on it solely to do hard operations, for instance. Because, the downsides of the idea being wrong is huge.
Anyway, the way we think about, AI will get adopted in a similar pattern to what you saw in outsourcing where you start doing it either based on capacity constraint or capability constraints, and do the discourses to one equation to then determine what's going to get outsourced and what's not. I could keep going on and on about that.
One example would be if you think about outsourcing, Y2K was the place where outsourcing really took off, and the reason for that being, there is not a lot of capability within companies because of Y2K. And once Y2K died away, people then figured out, "Hey, you can use the same thing for doing other things as well. So, that was a capability type of thing that then morphed into a capacity.
Similarly, AI will also see a similar pattern in the future.
Aderson: Again, even in a case like Mariana, your AI, I'm going to put it this way, will become smarter, and smarter, and smarter as it practices more and gain more and more knowledge over time, correct?
Venkat: Absolutely. So, one of the main points about machine learning and AI is that it learns from not only the data you started with that you provided, but as it executes and as it figures out what's important and not important, it gets better and better over time. And that capability of AI to learn as it proceeds is one of the important things that we deployed for.
Aderson: Venkat, you alluded to that already a few times there, but I'm going to ask that anyway. Mariana was founded back in 2013, correct?
Venkat: Yeah, in '13, early '14.
Aderson: What was the gap that you saw in the marketplace that you said, "Hey, you know what? There must be a better solution for that." Again, you alluded to that, but I would like to be more explicit in my question here.
Venkat: Explicitly, the key problem that we are trying to solve is finding the purchase committee within ABM, and how do we target them, surround them with marketing. The background behind this is that before I started this company, I used to run enterprise marketing for Juniper Networks, and now Juniper Networks sells networking gear. We have two basic parts of the company: one as a service provider. We'd sold to AT&T, Verizon, and so on and so forth, and something like 15, 20 companies around the world contributed to 60, 70 percent of service that I've used for Juniper. I don't know about the exact numbers, but approximately.
Any marketing that we did on the service provider was almost, by definition, ABM. Because, people like AT&T, where a few $100 million customers, and when you did marketing, you're trying to get all the 2,000 or 5,000 people within AT&T to engage with Juniper.
When we were trying to take the same lessons of ABM from the service provider side to the enterprise side, and I handle the enterprise side, we immediately ran into issues where we said, "Hey, one, we don't know which accounts to go after, because unlike the service provider side, in the enterprise side, this could be any company, tens of thousands of companies around the globe who could be targets for us, how do you figure out which companies to go after? Secondly, what is the purchase committee within a given account? How do you figure out who is, in order of the purchase process, buyers, influencers, and so on? And once you figure out these buyers and influencers, how do I surround that person with all kinds of marketing?"
As we alluded to earlier, display banner ads, display ads, Facebook, social ads, Google Adwords and so on. That's basically what we do, which accounts -- who within the accounts, how to surround them with all kinds of marketing?
Aderson: You mentioned there a few big names, Venkat: Juniper Networks, and again, you alluded to big organizations. Is ABM applicable, as well, not only with Mariana, but overall, applicable as well to SMBs?
Venkat: Yeah. You interviewed some of the analysts. This is a discussion that's been going on in a lot of different places. For some people, ABM, by definition, applies only to very large accounts. However, we, and a lot of other people, believe that, with modern AI techniques and so on, ABM can scale.
Let me explain why people say the former and why we believe it could be latter. So, when you're trying to do outbound and when you're trying to do it on an ABM fashion, normally, you're trying to figure out which accounts are good in the accounts. You're trying to engage people with a kind of content and kind of things that are relevant to that kind of account, that particular industry, that particular account, region, that particular individual in the purchase process, the purchase cycle, and so on.
There is a lot of human effort that is traditionally needed to be involved to understand which accounts, and to understand the need both from an account level parameters, the industry level parameters, account level parameters, and individual parameters, you needed to understand all of these things to create content and to create engagement to the audience, right?
Now, what you're saying is that, yes, and that's how you need to do marketing. However, with modern AI techniques, you can do the same level of understanding somebody from an industry account and an individual level, you can do it at scale using AI where AI, to your only point, we are outsourcing to human intelligence that was able to deploy for a few tens of accounts. You can do the same thing for a few thousands of accounts because of AI.
The point we're making is that ABM, by definition, needs to be very targeted, very personalized to the industry account, and be personal, and we're saying you can do the same kind of personalization at scale with AI. That's the basic point we're making.
Aderson: Let me try to close that. So, what you're saying is that because of the AI layer that you are putting in place on top of ABM, you are able to bring costs down. Because, ABM used to be only reachable by companies, organizations that had the finances to do that. Now, because you can scale that, you can scale to a level that is affordable, and in reach of small business as well.
Venkat: Exactly. So, as we say, every account deserves ABM, and it's not just the largest one. Every account deserves an ABM because every purchase, every sale is account-based. If you're buying pencils and staplers, okay fine. It might be an individual taste, but once you go beyond that for any reasonable purchase, it's, by definition, account-based, and there's a lot of people involved in the purchase process. Every account deserves ABM, and to your point, because of AI, because we outsource, if you will, the effort of doing this ABM to AI, we are able to bring down the cost small enough that it can apply to a very small account as opposed to only the larger accounts were able to do earlier.
Aderson: Perfect. Now, we're talking about ABM. Let's do a bit of an overview, again, on the ABM model, and what are the key components, Venkat, if I may ask, of a successful ABM initiative?
Venkat: The first thing is there's a meta point that applies to these different things. The meta point is that we need to tie up sales, marketing, and even customer support and other things into a connective joint go-to-market model. So, to deliver on this true ABM, what needs to happen is we look at it in four basic boxes, or three boxes with an underlined thing. The first one is account prioritization, which accounts to go after. Second one is contact prioritization. Well, what is the serious decisions? This is the decision. How do I figure out who are the personas, who are the people within the personas.
Finally, once you do this, what are the types of activities that I'm going to do to some of these people? Meaning, what are the physical events I'm going to, what are the first-party events, third-party event, what are the online activities that I'm going to do, and all of this sits on a very solid foundation of measurement, reporting, and planning.
The first step that you would need to do is to first put in enough measurements, systems, and reporting so that you can understand what's going on right now. Once that is there, then you can sales marketing and customer service can all come together to determine, "Okay, which type of accounts do we want to go after? Who are the specific list of accounts to go after?" and then marketing and sales can come together to then determine what are the personas, identify those, and then again, execute on different sales and marketing activities that needs to happen.
One of the things that we need to be careful about here is that marketing and sales don't need to be aligned not just on top of the funnel and during the pipeline, but also after the sale. How do we help the account best use the products that we are selling them to increase engagement and so on?
On this note, I'm going to go on a slight tangent and give you an example. Cisco, who were my competitors when I used to work at Juniper, didn't experiment on trying to figure out who were the best salespeople in Cisco. They look at a lot of different variables and so on. If you look at quota achievement and so on, it's not tenure, it's not education, it's not experience. It's none of those things.
The main thing that determines whether you're going to be successful or not is whether you kept in touch with your accounts in between cell, and that is a very, very important thing when you come to do marketing. When you think about marketing, we keep thinking about it on top of the funnel, and then we say, "How do we support the sale during the purchase process?" but then we abandon our accounts after we sell it, and the point is, with this whole ABM and what we're talking about, it's not about a point process, it's about a full process of being able to support the customer in their complete lifetime.
Aderson: I would like to hook that with how that's applicable to small businesses. Because, here's the thing. What you mentioned there, you mentioned Cisco. But, if you think about a small business, this is key as well, because it's not only about getting the sale, but following through and following up and keeping contact after that so you make sure that whatever they are buying, whatever you're delivering are really put to use and to the best use of it. Again, it has repercussion or similarity in this small business scenario as well.
Venkat: Actually, in some sense, small businesses are in a slight advantage relative to large business, because a large company, because of so many layers between the actual things that are happening out in the field versus what might happen at headquarters. Large businesses don't often know what the heck is going on. But, on the other hand, small business, we, and we have 10 people in the company, 12 people in the company, so we had a small business too. But, everybody in the company knows our customers, has connection to the customers, and therefore, being able to offer a better level of service, understanding between purchase is far easier, in some sense, for us as a small company than it would be for a much larger company, because we have a more direct link to the customers that large companies don't have. So, this is applicable. You do this for what kind of business that you do.
Aderson: Here's the thing. You mentioned there the key components to execute a successful ABM strategy. Now, let me ask you think. How does Mariana come in play here? Because, you mentioned key components. Does Mariana address everything there? It's one-stop shop for that or there is one particular area that you deliver on? Tell me a little bit. How do we map Mariana back to the key successful components of ABM?
Venkat: Mariana's focused only on the execution for marketing, right? I've made up to three boxes plus the measurement of the reporting boxes, we don't do anything on the measurement and reporting and planning kind of pieces. We also don't do tools that are focused on account-based sales, account-based customer service similar to what, let's say, an engager would do on somebody like an -- those are people who have tools that help the sales connect with ABM world. We, on the other hand, are focused only from creating -- our vision is to create an execution platform for marketing for ABM.
So, that's what we are trying to focus on, which means all the outbound activities that you want to do with respect to ABM, we want to coordinate that. Within the boxes that I laid out, we help you figure out which accounts to go after, who within the account to go after, and how to do all the different digital marketing activities that go with it. We don't do the sales activities, or we don't do the offline physical activities and so on. So, it's the digital marketing execution is what we are focused on.
Aderson: Venkat, if I asked you what will be the ideal scenario or profile of a company to work with Mariana?
Venkat: We have found -- taking a step back, the kind of places where we work the best, our ABM project scale works best, is if you have some kind of fragmented market. By fragmented market, I mean, either the companies that are buying are fragmented or the purchase teams within the companies themselves are very fragmented. So, we need some kind of fragmentation to work.
Aderson: Let me just stop you right there. Can you give me an example of that so I can visualize that a little bit better?
Venkat: To contrast it, the world that I was talking about earlier for Juniper, because we are selling on the service provider side, we are selling to 15, 20 companies around the world, there's not a whole lot of fragmentation, certainly, only the 15, 20 companies, and Juniper knew all the decision-makers for the most part, and probably knew their kids' and dogs' names.
On the other hand, when we were selling to enterprises where we were selling to tens of thousands of companies, or probably even more, we don't know all those accounts and all the decision-makers there. So, that is a difference that I would make between a place where the purchase is concentrated versus a more fragmented market. So, anyone who's selling into a fragmented market is good for us as a customer to us. So, that's one aspect.
The second aspect that's important is that you have enough content to engage the customer. A lot of the context that we talk about in digital marketing for what we provide have to do with social, have to do with Google Adwords, and display, and so on, and these are slightly once removed from your traditional kind of marketing where you're supporting various on-the-field activities, or more what I would describe as into-the-funnel activities. These are more top-of-the-funnel activities, and therefore, you need to have good top-of-the-funnel content to engage with the prospects that -- the content needs to be engaging to the prospect, right? So, content is a very important piece for us.
Thirdly, you need to have enough historical customers for us to do an analysis. Typically, that just means 200, 300 transactions and above, or 200, 300 names of companies and people and above is kind of the minimum that we need to be able to do these AI models to be able to then help you with targeting. So, those are three broad success ideas.
What that translates to, typically, is that it's a company about 125 employees above who are selling into a fragmented market who might be using a lot of Google Adwords today, or who might be using a lot of content marketing today. I was looking at an outbound motion through ABM. Those are the types of people who are best fit for our companies, who are best fit for us.
Aderson: One curiosity that I have, Venkat, is that have you seen the use of Mariana by marketing agencies as well? Because, what it seems is that, of course, you are selling directly to the company who will be benefiting from the technology. But, do you see a middleman there? Do you see the use of an agency there?
Venkat: Absolutely. If you think about it, I would say, and I'm going to make up a number, but something like 70, 80 percent of B2B marketing activities are usually outsourced to some agencies. It's a combination of creative agencies, marketing automation agencies, media buying agencies, and so on. So, those agencies are super important to us, and we know we need to be with them.
We just now started working with one agency, Position², to help us think through this thing. But, we do want to work with agencies because we know that they're an important player in this ecosystem, and a lot of these agencies, in fact, are providing with human beings some of the services our AI can provide, and what we want to do is to help these agencies do more for their clients, and do more at scale. So, we do want to work with agencies, we're beginning to work with agencies. But, over time, we want to add more and more of those people.
Aderson: Okay, got it. Question here. Do you eat your own dog food?
Venkat: Absolutely. We're in July now. Until March, we do not have a single salesperson in the company apart from me. I'm CEO and I'm doing sales as well, and from May of last year to, let's say, March of this year, every deal that we did, every customer that we landed, which is about 10 or 12, whatever it was, all came through Mariana on Mariana. There were some inbound things as well, but came through Mariana on Mariana.
In some sense, we are not a good customer for us because we don't generate a lot of content and so on. However, to your point, because people ask the exact same questions that you just did, Aderson, we do eat our own dog food, and we generate -- I would say, today, we're generating about 20 to 40 leads per month just based on Mariana, and Mariana on our own. So, yes we do.
Aderson: Now, talking about clients, do you want to highlight the results of a particular client? I saw a video from Mariana about Zendesk. I know the Zendesk case. If you want to highlight Zendesk, that's fine, if you want to highlight somebody else, that's fine as well. But, highlight some of the results that you have been able to bring to some of your clients.
Venkat: Let's actually talk about Zendesk for a couple of different reasons. Zendesk, as everybody knows, is a well-known B2B marketing company. They've been doing a lot of inbound marketing. Historically, they've won numerous awards for their great B2B marketing, and predominantly, they were how a system where they drove inbound leads, which then went to their trial that they then tried to convert them. Now, for the reasons that we talked about earlier, they wanted to improve their targeting capabilities and do some outbound to target specific types of accounts. Because, they wanted to do larger accounts than what they were historically doing.
They came to us with that problem. How do we improve our lead generation targeting capabilities on an outbound basis that would augment the great inbound work that we are already doing? So, in that context, they gave us something like 400,000 individuals' names, we really think it’s some 40,000 companies or so in the U.S., and we created an account and persona model based on that.
The reason why I bring up this 400,000 is that this amount of 400,000, you couldn't have done an analysis on these 400,000 with human beings. You could have made me gather data about 400,000 people, but bringing it all together to analyze the patterns of these 400,000 people, it's almost impossible to do it with human beings. So, we were able to generate an account model and a persona model based on AI, and we were able to do it within a day, or half a day, or whatever it took us. I don't remember. Now, I should note that they did an internal effort on their own internally with a bunch of other consultants and so on, and they took three months to come up with a model which you are sampling and so on and so forth, which came up with something which is largely similar to what we did. This was more to demonstrate the AI capabilities, and earlier we were talking about outsourcing and being able to do things at scale because of AI. I just wanted to bring that up.
Anyway, so we created this account model, we created the persona model. We then targeted something like we created an audience of 100,000 people from the data and other things that we had, and they gave us, and Zendesk's grand campaign is targeting these people. A couple of key points. They were able to increase their lead volume by 4x while improving quality. They didn't tell us how much the quality improved by probably because we'll increase prices. But, anyway, while improving quality, while at the same time maintaining the cost. So, 4x better, more volume, better quality at the same cost.
One thing that I want to note here is that when they were trying to reach these 100,000 people, they ran a campaign targeting them on Facebook and they were able to reach half of the audience in three days. Now, this is an important point because there's not a whole lot of marketing activities that you can do to reach so many people in a very targeted fashion in a very quick way, and that's the reason why being able to target people on a platform like Facebook, which is a high-attraction channel, but being able to be very focused on that is hugely important because of Facebook's scale.
Anyway, so they were able to reach 50% of the audience within three days, something they cannot do in any other fraction. So, that's a quick summary of Zendesk: better targeting, delivering 4x leads while improving quality and maintaining cost.
Aderson: That's great results there. We are coming towards the end here, Venkat, but before I let you go, I have a few more points here. First is on Mariana's implementation for a new client, a new company. What is the number one challenge that we have to go through this road block here first before we can get some results? What is the one thing that is usually the biggest road block there for a new client to come to a platform like MarianaIQ?
Venkat: It's content. It's having good content. So, typically, what ends up happening is people have good into-the-funnel content, but top-of-the-funnel content, a lot of people might not have. That's number one. And two, how do we leverage and position this content? To give you an example, we were doing a trial a year or so ago with somebody, and they were promoting a Gartner report, and they said, "Look at this Gartner report. We are in the top right-hand corner of Gartner report. We didn't get a single download, single click, whatever." We changed the copy to read, "Hey, learn more about this topic from this Gartner report." Boom, seven to 10 downloads per day.
The reason I'm pointing that out is the first is perceived as the vendor just chest bumping, "I'm so great." The second one is something that helps the recipient, the prospect, and that is the kind of good marketing that you want to do that's helpful to the person receiving it. So, it's a combination of content, copy, and creatives that you do for the ad that needs to be helpful to the end customer of the prospect, and that is probably the single biggest determinant - apart from, of course, us doing our job - that is the single biggest determinant of whether a campaign that you do with us is going to be good or not.
Aderson: It's the difference between doing a "me, me, me" type of content strategy as opposed to "give, give, give". By the way, we can help you, you know.
Venkat: Absolutely, yeah. The true kind of marketing is this permission marketing that helps you. Of course, there are places in which we can help you. There'll be other places where we can't. But, that's the true kind of good kind of marketing that you want to be able to do.
Aderson: Okay, so Venkat, again, coming towards the end here, what is one thing that you'd like people to leave this conversation knowing about, either about Mariana, about ABM, about the future. What is the one thing that you'd like to stick on people's heads after they listen to this conversation?
Venkat: I want to bring about the AI, the topic of a lot of people today in what we're doing. People like us who've been around for a few decades in the high-tech and so on, we've seen a lot of changes, we've seen internet come, we've seen mobile come. AI is a bigger change than any of these things. In our lifetime, this is going to be the biggest change that we've ever seen. There's a lot of things going on about perceptions of what AI and how it's going to take people's jobs and so on and so forth. We, on the other hand, are optimistic about the future, about how this is going to add value to everybody in the world, and make our lives a better place.
I would encourage everybody, listeners of this podcast, to go learn more about it. Learn more about AI. Do not be too concerned about what people are saying. Find out for yourself. There's a whole bunch of resources available on the web these days to understand more about this, and more importantly, learn more to remove the mystique of what AI is, and understand, truly, what it can do. Because, this is going to be the future. The next 20, 30 years of our lives are going to be dominated by AI, and everybody needs to understand what it can actually do.
Aderson: Awesome. Love that. I know that you are a big reader, so I would like you to finalize here with a book. Recommend a book for people to read, whatever topic, whatever subject you want, recommend one book.
Venkat: Which is a bit of a challenge, because let me show you my -- this is only one-sixth of the books that we have. I'm a reader and my wife is a writer. But, anyway, we were talking about AI, so let me point out a book on AI that I thought is very good. It's a book called Master Algorithm by this leading AI researcher called Pedro Domingos. Master Algorithm, Pedro Domingos, which gets into AI, which explains it from a layman's perspective, layperson's perspective, what AI is, what are the different tribes of AI, and how to think about it. So, a book I strongly recommend for people to get their feet wet, and very relevant, apropos to the topic that we are discussing right now.
Aderson: Awesome. As you guys all know, all the links, the book that Venkat has just mentioned, everything will be on the show notes. So, you can all review it there. Venkat, how can people reach out to you, how can people connect with you, contact you? What is the best way?
Venkat: Please follow me on Twitter. My handle is @VenkatNagaswamy. That's my Twitter handle. Or, you can write to me, Venkat@marianaiq.com. Those are the best ways to get ahold of me. I'm on Twitter all the day. I take the train, so morning and evening, I'm on Twitter all the time, so that's the best way to get ahold of me. That or email. I would be happy to hear from any of you or all of you, and help you out in any way we can.
Aderson: Perfect. Again, as I said, all the links mentioned by Venkat will be in the show notes. Venkat, again, it has been a great pleasure, great, great pleasure, really good conversation. I really appreciate the fact that you shared so much knowledge. If you guys liked this video, subscribe to the video on YouTube. You have a lot more there, and thanks very much, Venkat. See you next time. Bye.
Venkat: Thanks a lot, Aderson. Take care.