theCUBE + NYSE Wired: CMO Leaders | Chandra Rangan, Neo4j

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Chandra Rangan

CMO

Neo4j

play_circle_outline Enhancing AI Capabilities through Neo4j's Graph Databases and Relationship-centric Data Approach

play_circle_outline Utilizing generative AI for generating insights and content

play_circle_outline Cost reduction and productivity through AI tools in marketing operations

play_circle_outline Restructuring CMO role based on revenue targets from pipeline performance.

play_circle_outline Real-time decision-making in marketing for engagement and nurturing leads.

play_circle_outline Non-linear progression and personalized content for effective marketing strategies.

play_circle_outline Collaboration between marketing, product, and engineering for integrated customer experience.

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Chandra Rangan, Neo4j

Chandra Rangan

CMO Neo4j

Chandra Rangan, the Chief Marketing Officer at Neo4j, joins theCUBE to discuss vital shifts in the role of Chief Marketing Officers amidst the accelerating influence of Artificial Intelligence on marketing strategies. With a spotlight on graph databases, Rangan shares Neo4j's pivotal role in powering AI infrastructure and the mechanics of graph databases. During this insightful session, John Furrier of theCUBE and renowned analysts delve into how these databases are redefining customer relationship management and strategic decision-making in marketing operati... Read more

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What is the difference between a graph database and other types of databases, and how does storing relationships as first-party data impact the use of AI and generative AI tools like GenAI and LLMs? add

What are the two types of generations used in marketing at Neo4j? add

What is the solution for increasing the number of banners needed for events without hiring more people? add

What is the reason the CMO at Neo4j started reporting to the CEO instead of the sales leader three years ago? add

What makes real-time important in engaging and retaining the attention of an audience, and how can data and technology be utilized to personalize and enhance the experience for different individuals based on their specific interests or needs? add

What is the concept of turning the traditional marketing funnel horizontal and identifying a point where qualified leads can be converted, rather than the linear progression of the old funnel concept? add

What roles do the developer relations team and the PLG team play within the marketing team at Neo4j? add

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Chandra Rangan, Neo4j

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>> Welcome back, everyone, to theCube Studio here. I'm John Furrier, host of theCube. We are here part of the CMO Leaders Series Summit we've been putting on over the past few days and part of the theCube and the NYSE Wired community. It's open source community of leaders coming together, sharing their knowledge around how the world's changing with AI. More importantly, how the societal benefits will come, productivity, cost reductions, and just more fun tech hitting the scenes. Obviously we're seeing all the news every day. Chandra here CMO at Neo4j. Chandra, great to see you again. You were here for our Supercloud 6, now part of the CMO. You're a CMO and you work for Neo4j, which is leading the charge in a lot of the enablement around AI. Thanks for coming in.

Chandra Rangan

>> Thank you, John. It's great to be here.

>> So I want to get into a lot of thoughts around how you see the world change of CMOs, but you have a unique position, Neo4j, fantastic growth company. Private still, soon to be public as the rumors, but more importantly it's the graph database. It's all the software around what's making all this AI- like infrastructure work, a big part of it. You're also a CMO, so you kind of have to think about your role, but you know what everyone else is thinking. So talk about Neo4j real quick. Set the table. Why is Neo4j important for AI and graph database, and how does that relate to some of the CMO thinking? What's that going to enable?

Chandra Rangan

>> Got it. Neo4j is a graph database company, right? And what's a graph database versus any other type of database of graph database tools of relationships as well as entities? So in a traditional database, you'll have a role for you, John, a role for me, Chandra. And then if you want to figure out how we are related, it's actually a compute operation. You have a index, you'll have a foreign key, and then you have to do a lookup, and all of that. In a graph database, you actually store this relationship that we know each other as a first party data in the database. So now what does it mean in context of using AI and generative AI tools? GenAI and the LLMs are only as powerful as the data that they use to train themselves on, and the quality of the data that they use to train themselves on. So they think quality of data. What really matters to understand you, John, or me, is less about our characteristics. It's not about the jacket we wear and how tall we are or how old we are. What matters is the relationships. So I can predict better what Chandra would do or John would do if I understand the relationships and the context that you have. So graph databases expressed as knowledge graphs become this critical part of the data layer for any GenAI stack.

>> Yeah, I think graph databases have been super important. I remember when Neo4j started years ago, really the only companies doing it were like the Facebooks of the world, and the social networks are graph-based because we all have social networks. And I had a family member saying, "John, explain this graph database study to me in language that I understand. " I said, "Well, think of it like a node, like a circle, then you have a connection to another node, and then you get an arc between them. That's your name, and maybe that's your relatives, your friends, or when you see on Perplexity or chatGPT, you type in a prompt, you get an answer, then there's some more things like, 'Do you want to know more about this person,' so it's just more data around that's connected around something."

Chandra Rangan

>> That's right.

>> And they go, "Oh, I get it. So like my Facebook page and I've got friends. " "Yeah, those friends have friends."

Chandra Rangan

>> Exactly.

>> And so they go, "Oh, I get it." This is huge.

Chandra Rangan

>> Yeah. - Because now as computation and GPUs

>> and AI infrastructure is getting more performant every day, even the benchmarks are every day someone's leapfrogging someone else in performance, this is going to yield things like personalization and other things for software. Now the CMO, they're in this business. People, customers, prospects... Why is graph database is going to be super important for CMOs, and what's that going to enable? Because the old database was a row, and a table, a schema, or a bunch of data around chats or call centers, they're all kind of all over the place. You got to build this harmonization layer, kind of complicated, but it could be done. But now the world's coming so fast to the CMO that all the stuff that they used to do with IT is going to change. Talk about the CMO's impact for things like graphs and some of the things you guys are doing.

>> Oh, my God, there's so much to talk about here, John.

Chandra Rangan

>> So first of all, if you think in marketing language or in terms of the function and the discipline of marketing, we've always thought in terms of a funnel. So you've got a marketing funnel, and it can either go, if you're looking at it in a slide, it goes from left to right, or if you're looking at it on a page, it goes from top to bottom. And the idea is you put in stuff at the top and then you filter, filter, filter, filter and something pops out of the bottom, right? And that's huge value to that. That's not wrong, but that's not how you and I, as consumers, behave. That's not how you and I, in terms of senior leaders at companies, engage with sort of prospects. So if you think about... Suppose I wanted to buy a car. How do I go about the process? I go about the process by saying, "Hey, I have existing relationships with vehicles that I own, and brands that I own. " So that's a set of my world today. I have relationships with influencers, people who are in my network that I trust, and my social graph. So there are people that I know who I will check in with and I ask questions about. And then I have research methodologies, right? In the past I used to do a Google search. Now I'll get a ChatGPT or Gemini and then I'll ask a question, so I've got all these mechanisms. Each of these, if you start mapping it out, they're all graphs sitting around Chandra. So if you wanted to connect with me and sell me a car, it's not about applying filters on multiple folks. It's about me, Chandra, understanding the different graphs that I'm part on, and helping influence that decision. And as you influence the decision, you have to think about, "Okay, what can I actually deliver to Chandra? Or Chandra wants this type of car with this color, can I actually deliver it? " That in itself is a product graph that you sit behind and a supply chain graph that you sit behind. So the headline here is, historically as marketers we think about funnel. I know the belief that when we step forward, we've got to think about stop thinking about funnels and start thinking about graphs.

>> Yeah, and I like the funnel example because the funnel is a framework that's based upon old mechanisms.

Chandra Rangan

>> Yeah. - The graph thing's interesting,

>> and I want to get your thoughts on this because I've been riffing on this and you're the perfect person to continue that. I was asked by a marketer, "John, what do you think is going on? " Of course I weigh, in my opinion. I go, "Well, the old way of doing things was you put things in a database, you get data from all your sources, they came to your website, it could be all over the place, unstructured. You put it into a database, you interrogate it, you got forms, and then you got to extract that out and you get a dashboard. The data could be a week old, a day old, but it kind of lags, but you can kind of see something, and then never mind the Internet. They're out touching things all the time. " And they're like, "What do you think about all this? " Well, graphs are important because networks are graphs. So the old school networking days, the Internet, was based upon graphs. You had a route, and you go to a router, and it connects over here. So the Internet is graph-based.

>> Yup. - They're connections.

>> We interface with social media, those are graphs.

Chandra Rangan

>> The Internet is now digital.

Chandra Rangan

>> Yeah. - So your customers are all running

>> around these graphs. So if you're a marketer, if you're not on top of the graph database piece, you're thinking completely wrong because that's where the marketing is. The funnel is the Internet.

Chandra Rangan

>> The funnel is Internet is now the graph.

>> Funnel is the Internet. - The funnel is the graph.

>> Exactly. So you agree. - Yeah.

>> So okay, take that metaphor one step further.

Chandra Rangan

>> Now I'm marketer, I'm going to reinvent the future.

Chandra Rangan

>> AI comes in, which can be very smart with high, supercomputing capabilities, you can traverse these graphs. So imagine the opportunity for a developer. So I think this is going to be a complete game changer because graphs are networks, networks are communities, communities are interfacing. I could be chitchatting on some app over here, so this is all going to come together.

Chandra Rangan

>> Absolutely, yeah. - What do I do as a marketer?

>> How do I figure this out? Give me your take, because as a CMO ,it's a little bit of a long game, but how do I bring it to the present? I got a martech stack, I've invested in all this infrastructure, I got account- based marketing, I've got segmentation, I've done all these things. Am I stuck? Is that an opportunity? How do you look at this? Because now I want to get at the actions of the customer. I want to sell them a product, keep them as customers and do things like cognitive dissonance campaigns or all the things I want to do, I don't want to get into the weeds in the tech. How do you figure this out as a CMO?

>> This is actually not as complex as a lot

Chandra Rangan

>> of people believe it is, and it's not as as a lot of people believe it is. And the interesting thing about marketing, and we were just chatting about this a short while back as there's a lot of room, and appetite, and experience with experimentation. So you can actually add capabilities that generative AI provides you in a whole bunch of different places. And the step one for that is having data and collecting the right type of data. So if your data is structured in terms of a knowledge graph, then you can start doing very interesting things on top of it. GenAI also does one more thing, which is the way people search has changed because of generative AI. So historically if you want a car, you would say, "Hey, tell me what car companies are there, and let me go and look up the cars and take a look at it. " If I want to buy a shirt, "Hey tell me... Take me to Gap or whatever it is, and let me look at a shirt. " Now because of ChatGPT, we have an entire generation very quickly getting trained on expressing intent. Not expressing outcomes but intent. So when you go to ChatGPT, what do you say? You say, "Hey, my wife's birthday is coming up. She loves shoes. And I think she would like red shoes, but I'm not 100% sure. What are the latest models of shoes, and are there new fashion trends I should know about? " That is the kind of query that I would put into a ChatGPT, which is very different from how I would search at Google. So from a marketer's perspective, now what does it do? It gives me a bunch of stuff around intent, which I had to spend a lot more effort and try to derive. Now the prospect is giving me intent. And they're giving me intent with a much wider range of possibilities that I actually can satisfy. So if we come back and look at the marketing stack, I'll give you an example. When I started Neo4j three years back, this notion of acquiring a contact and qualifying a lead. So I want to get a contact, I want to nurture them to get to a point where it's a lead. And a lead is someone who, in Neo4j's context, understands Neo4j, knows who we are, understands the value proposition, probably has tried out and play around the product, and they may say, "Hey, maybe I want to have a commercial conversation. Let me talk to somebody." That conversion rate from contact acquisition, it was 5%, 3%, depending on the quarter. That's normal. Today, that conversion rate is north of 30%. And the reason is, we are able to take first targeting better, better segmentation, and then when we get all these different signals in the back end, we actually use a Customer 360 model using GenAI tools so that we can combine all these different signals into that one entity or one person who's actually responsible for all the signals which we couldn't do before.

>> And that's a function of better use of the data?

Chandra Rangan

>> Better use of data. So the data has to be set up in that way, right? That means we have to connect it up a market or stack, we have to connect up with 6sense, so we bring in all the information that we can. We have a lot of contact enrichment that goes on, so actually increase the budget for contact enrichment. And then once we have all the data and it's set up as a graph, it's very easy then to say, "Hey, this is actually not five different people doing 15 different things. It's one person, John, who's doing all of this. " And suddenly I have a view that I would never have before. And then the next piece comes in, which is, what are the offer I make to you? So I can have a very customized offer. And that's the other place where we have started using GenAI, right? How do I take all this information and create an outreach through emails that is very specific to you that brings you along the journey?

>> Chandra, you're bringing some great points. There's so much. First of all, you guys are the center of all the action in my opinion where you are. There's two things I'm hearing. One, you got to set things up. Got to get the foundation, understand the data. But generative AI is... The word, generative, is a word, right?

>> Yes. - That means it's generating something,

>> so it's not a pre-programmed thing.

Chandra Rangan

>> Yes. - So this is where I think graphs shine

>> because when you generate either a prompt

Chandra Rangan

>> or you want to do something, the graphs can adjust intelligently around the prompt. It gets some context. birthday, that could trigger a reformation or intelligence around how fast can I get other data around this context?

Chandra Rangan

>> Yep. - It's a basic concept Like okay,

>> the old days was go search everything and give some results. Now it's like targeted off the initial context. It's like setting the bit.

Chandra Rangan

>> Yep. So there are two types of generations I use in marketing at Neo4j, right? So one type of generation is what we just started talking about is generating insights. The second type is generating content. When I say generating insights, that's about using an LLM on existing data to actually make sense of it, right? Which is... Customer 360 is a great example of that, right? Sometimes we have entities or people or prospects in our database that we don't fully have all the information that we need. And we can use generative AI to say, "Okay, there are gaps here. What are the high probability examples of what those fields could be so we can actually hydrate that particular contact or prospect? " So there's one piece which is insights. The second piece is generating actual content. I'll give you a different example. In three years, Neo4j has more than doubled in size. Since I took over marketing, we have probably tripled the number of events that we do, and we have standardized them, and we have about-

>> And staff too.

Chandra Rangan

>> We haven't. - No staff?

>> I have fewer people today... - Wow, really? That's

>> counterintuitive. - ...

Chandra Rangan

>> than when I actually joined the company. So how do I take-

>> Are they in platform engineering?

Chandra Rangan

>> So how do I take the two folks who are responsible

Chandra Rangan

>> for all creative sort of banners and-

>> Performance

>> marketing, all that... - ... all of that stuff?

Chandra Rangan

>> Yeah. - So every event I run,

Chandra Rangan

>> for example, we need banners.

>> We need banners like this that go up, and it's custom for every event. Now I have two people doing that, and I triple or quadruple the number of events, and we have to quadruple the number of people. We haven't done that. So what do we do? We actually have generative AI tools that we feed with our existing guidelines, brand guidelines, and creative guidelines, and now anyone who wants to run an event anywhere in the world can use the tool in Canva to automatically generate creative.

>> So you guys are unnecessarily driving costs out of the business because you kind of started lean and mean. You're already have cost reduction by not adding costs.

Chandra Rangan

>> Exactly. - You focused in on productivity

>> because that's where the gap is because you've got growth.

Chandra Rangan

>> Yeah. - That's a really great example.

>> I want to ask you about the impact to... First of all, you guys are a growing startup, so you're born in AI, basically. It's like born in the cloud. Remember the born in the cloud days, it's like company no-name comes like Dropbox, Airbnb in their rooms, coding on Amazon. They didn't provision data centers. They went born in the cloud, as they say.

Chandra Rangan

>> Yeah. - There's a born in the AI

>> generation going on right now. You can see that. Why add better tools.

>> Yeah. - Okay, so a little bit different than the big

>> enterprise that has it preexisting.

Chandra Rangan

>> So I want to ask you more about CMOs that have staff and structural issues and changes. How does a CMO look at their staff resources and also execs? Because first security popped above the line, because above the line is a phrase called below the line. It's executive level and then a line then it runs under it they're operating. Security pops above the line. Board level, a lot of strategic things. CMOs are coming above the line. Why? Because targets 5% to 30% conversion, that impacts sales.

Chandra Rangan

>> It's a huge . - Hello?

Chandra Rangan

>> Yeah. - Above the line detail.

>> Customer satisfaction, retention rates, targeted campaigns,

>> this is the future. First of all, do you agree with that? And two, how does a CMO understand how they can manage the structural change of their job, their reporting structures, and their stakeholders? Do they lean more of the CFO? Is it the CEO? CISO?

Chandra Rangan

>> Well, you're spot on, right? And first of all, I completely agree with some of philosophically the direction we are headed towards. So at Neo4j, the CMO used to report into the sales leader in the past, right? And that changed three years back when I joined because Emil, who's our CEO, recognized that he wants a strategic marketing organization. And his goal or challenge to me was something simple. He said, "Look..." This is three years back. He said, "Today we look at what we think sales will hit, so the CFO works with sales and sets up a number and a target. And then we look at the target for ARR, and we work backwards, and we say, 'This is the pipeline that we want marketing generate. '" That is a completely flawed process. Completely. And why is it flawed? It's flawed because of the time it takes to generate pipeline versus when the ARR shows up. So if I want ARR for 2025, the pipeline for that, I've already delivered a bulk of it, 70% of it last year. So how do I set targets for pipeline this year based on revenue targets? So Emil's challenge to me was a little bit different. He said, "Look, I want you to tell me how to set revenue targets based on the pipeline that you have been able to build."

>> Okay, so churn, managing churn, net new customers,

>> contract value increase, these kinds of things?

Chandra Rangan

>> Well, it comes down to two fundamental pieces within the pipeline, right? So churn is after the fact, right? So it's less about... So there's expansion then that's watched the business that churns, and then you get net new and expansion. For us, it's about two things. One is, what are the volume of incoming, right? Both volume and quality. What do I get in terms of leads and opportunities that sellers can actually take and close? That's one big piece of it, right? So the higher the volume, the higher the possibility of improved revenue outcome. The second piece, there is the conversion rate. And there are multiple conversion rates. What are the conversion rate... I just talked about one, from contact to leads.

>> Yeah. - What are the conversion rate from leads to sales-

Chandra Rangan

>> accepted opportunities, which

>> where often the BDRs come in and the sellers come in? And what are the conversion rate or close rate from an opportunity that a seller starts working on all the way to close, right? So you look at all those three pieces, a conversion rate improvement from 4 % to 6%. Everything else being equal is 50% more revenue. So Emil's challenge is that. "Show me how you can get me more volume that can convert better that I have much higher confidence in setting an ARR target and being able to hit."

>> So you're strategic with the CEO, so after they-

>> CFO. - ...

>> and the CFO, so that's the numbers that's

Chandra Rangan

>> above the line, good job on that. Thanks for sharing that insight. And I love your point about the old way because the old way was the sales guys were the leads, and so lead generation has kind of, I call, fell into the mechanism of email marketing.

Chandra Rangan

>> Yeah. - The old school, and there's a

>> lot of other lead mechanisms. But now you have... The concept of lead generation is just a concept. You get leads, you identify them, but where the leads are, and the mechanism to roll them up has changed. So that's going to be a key thing. So I want to talk-

>> Let me dig into that just a little bit, which is in spite

Chandra Rangan

>> of all the sophistication of marketing we talk about often, at least in tech marketing, when we say leads, we actually don't mean the same thing. When most sellers talk about leads, and I talk to my peers, it is, "Hey, I ran a webinar. Who attended?" Those are leads. "I came to an event. Who attended?" Those are leads. We put this video up, a bunch of people click on it, those are leads. I do not consider those marketing-qualified leads anymore.

>> Why? - Because I cannot control the quality

Chandra Rangan

>> and the conversion rate that we just talked about from all these different sources. Because end of the day, nobody makes a decision based on one interaction. Like I'm buying a car based on one interaction on one website or one sort of visit. Do I make the decision? No. So the decision from a prospect is made through a series of interactions. So in terms of the lead flow, I want have something that combines the series of interactions and gets me to a place where I can anchor and say, "Hey, this is a lead no matter what the source."

>> And how do you do that? Do you through that through a first party system? Is it a collection of throw everything at the market and let people boil down to a point?

Chandra Rangan

>> Yeah, so this is a combination of the GenAI tools we talked about, and just the philosophy of how we approach-

>> Everyone's going to want this.

>> I'm just saying this is a big answer here. Go! Because this is the holy grail.

Chandra Rangan

>> This is the holy grail, right?

Chandra Rangan

>> Yeah. - So what I think about this is,

>> I think about this in terms of progression, right? And progression equals conversion rate. I do not care about the number of people who came to an event or a webinar or swiped their badges, right? So this is what my team was doing when I joined. Every part of my team said, "Hey, I ran a webinar, I self set a target of I need a thousand people for it, I got 1,005. " Good job.

>> Yep. "Got good metrics, boss. They did a good job," that's the old way.

Chandra Rangan

>> And everybody did that. And they were all sources of leads, and all of these leads did not convert because they had one interaction. So I completely changed the model around. I said, "I do not care the number of people who came for the webinar. I care about the number of people who came to the webinar and then took the next step."

>> So you must do a lot of organic activity.

>> So next step, right? It's progression. So which means-

>> They're nonlinear progressions too.

Chandra Rangan

>> Exactly, right? And so I want to know,

Chandra Rangan

>> do people understand Neo4j ? And did they come in and did they try the product? And did they have a good experience? So the goal for the webinar team is the number of registrations for our free product. So did they come and do a trial? So suddenly, now I'm breaking down silos in my organization, back to your point about organizations so one team cannot be successful without the other.

>> You essentially optimized the bullseye.

Chandra Rangan

>> Yeah. - So you essentially made assumptions

>> that let touches happen, let's focus in on-

Chandra Rangan

>> I need a combination of behaviors

>> before I can say somebody is a qualified lead, not just one behavior.

>> And that's data-driven. So I love that. That's a great pro-tip. People are going to love that one. I want to get your thoughts on... You bring up a good point. It's all my hot buttons. I love changing marketing landscape because we know, theCUBE, we live in this world of... We're not very lead-oriented. It's all free. We don't really do email marketing, and I try to get people into our walled garden. We don't have a walled garden. We're all open. But a lot of the trends around what you're getting at is thinking differently. And one thing that's clear is that there's a lag in marketing. You mentioned leads. Leads come in through these mechanisms, they get cleaned, people go try to qualify them, MQLs, whatever they call them, and then they get shipped to the sales team either days, sometimes months later. And then context has changed, dashboards are like, "How was sales last quarter? " So things have just systematically been lagging because of the friction of the backend, and then the real-time execution on the tactical marketing. So real-time changes everything, okay? Graphs do great in real-time. You're in the graph business. You have real-time touch points everywhere, digital events, physical events, different apps all out there in this now horizontally organic, in some cases, walled gardens, different vendors, different subscriptions. How important is real-time? How should CMOs think about making real-time decision- making campaign management, data usage, data action? Because you can do something in real-time and have success but not have the mechanism to roll up the value.

Chandra Rangan

>> Yeah. - Talk about real-time

>> because I think this has been a big part of this week.

Chandra Rangan

>> And this is such an important concept and it's often a misunderstood concept, right? And why is it misunderstood? Because a lot of folks in marketing think real- time means there is this idea of, "Hey, I see some behavior or some action. I can sell you something right away. " That's not the promise of real-time, right? Especially in tech. Most decisions are not what I call window-shopping decisions. They're not emotional decisions. They are very thoughtful decisions by not just one person but groups of people, and you go through a trial process, and so on, right? So why is real-time then important? Real-time is important because you've captured somebody's attention. And when you have that attention, how do you keep them keep engaged and learning more? So I think about real-time as, "What can I do that's helpful when somebody is paying attention to me," right? And this is where a combination of good data hygiene backend with the knowledge graph, and LLMs, the creativity they bring to be able to retarget becomes super important. For example, I come to a webinar. After the webinar, why send an email to all attendees with the same five offers? If I know that you came to a webinar but you're actually working on a supply chain problem, and how do I know that? Because you spent the week before that, looking at our supply chain page on our website versus another person who actually came in from a HR background who's trying to figure how do I handle my team and talent management. The moment you finish the webinar, I should be able to give you content that works for you for supply chain and the other person that works for HR.

>> It's interesting. The old funnel concept you mentioned earlier was a concept where you put everything in the top of the funnel, mostly lead gen through these campaigns, and you make them matriculate down to the bullseye or some sort of magic spot.

Chandra Rangan

>> Yeah. - You've actually gone the other way

>> and kind of turned the funnel horizontal. You're allowing all this engagement, but you're identifying a spot where no matter how they got there, they're qualified in your mind, and then it's a point of attack or point of interest there you convert right there.

Chandra Rangan

>> Exactly. - And so that would assume that that non-

>> linear progression has to be thought through. So as a marketer, you then think, "Okay, the next step, " if you believe that to be true, and I do, "is that how do I make my activities facilitate the nurturing of getting to that new spot? " The video could change, could be a better video, more knowledgeable video, could be a better attention- getting convert in. So if I get your attention, you might not want to sell something, you might want to move them down or closer to their progression.

Chandra Rangan

>> Exactly. - So it's not linear,

>> you can't really map it out. You can just say, "We know why they get here most of the time," and then just organize a campaign to do that. I've never seen anyone do that.

Chandra Rangan

>> By the way, it's also very difficult to... I think we are also fooling ourselves if we think that, as marketers, we can magically convince a prospect to have a need when they actually don't have a need yet, right? We sell graph databases. You may not have a need for a graph database today, but there may be a project that comes along in three months' time where you do have a need. So my job is less about convincing you to buy a graph database when you actually don't need it right now, which is a bad experience for you, it's a bad thing for a brand, as opposed to be very helpful so that you understand, you learn, and then we stay top of mind, so when you do have a project that needs a graph database, you'll come and talk to us.

>> So one marketing strategy for you might be, "Hey,

>> let's put out content and messaging that says, 'Here are use cases where graph databases shine,'" and leave it at that.

>> Yeah. - Because when they're ready, they go, "Oh, wow,

>> we're going to do a big personalization project

Chandra Rangan

>> and we're going to do a data migration. Why don't we use graph databases? Oh, yeah, I'll go do a trial." Boom! There you go.

Chandra Rangan

>> When we say content, it's actually more than traditional content in the terms of blogs or videos or whatever. It's also your in-product experience. So at Neo4j, the developer relations team is actually part of the marketing team. The PLG team is part of the marketing team. And what we do is we work with product and engineering to think about if we want folks to actually try out the graph database and understand the power, build that Hello World app, can we actually start building in educational content within that product experience and tie that to educational experiences through our online academies and courses and so on?

>> Chandra, great conversation. You got so much insight. You have a luxury of sitting on both sides of the table. You're on the innovation side with Neo4j, with graph database also, you're a CMO. Final question for you. As you look at the future of the CMO, who are the key stakeholders if you had to have that magic triangle? Is it product brand? Is it demand? What are now the key areas that everything revolves around? If you had to have a look at stakeholders, obviously forget the executive peering, but who's around the table? If we have... we're sitting at the table. Who are the key stakeholders that really going to be the levers of the scale?

Chandra Rangan

>> Well, the CRO and head of sales, they continue to be super important partners, right? And I think about go-to-market as a partnership there, and that will never, ever change. And it can change. But then there are two other important partnerships, right? I think second partnership is working with the CFO and the CEO on strategy, right? What are we going after? What are the segments we want go after? How do we think about pipeline driving ARR versus ARR defining pipeline plans? So we talked a bit about that. The third piece to it, which we started touching on, which is a close relationship with the product and the engineering teams, right? Because a true experience for a prospect comes not from separately from a product experience and then separately from a bunch of marketing stuff. That has to be integrated in typically what could be a PLG motion, what could be a trial motion. And so that is a third sort of leg of this tool for me.

>> Chandra, great stuff. Got to get the revenue, you got the product-led growth, and of course, the CRO. It can all work and that's great for technical sales because you have the freemium model and you figured out how to crack the code. Congratulations.

Chandra Rangan

>> Thank you, John. - Thanks for sharing.

>> Chandra is here on theCUBE, the CMO of Neo4j. Again, this is where all the CMO is going to start to have these conversations. We're starting the conversation of the transformation because with AI, it's true business transformation, not just digital transformation. That's already happened, and the Internet's based on graphs so Neo4j is one of the big players doing it. Of course, I'm John Furrier of theCUBE bringing you all the action, thanks for watching.