EP 97: Why AI Won't Fix a Broken GTM Strategy

Speaker A: Welcome to Not Just Ads, the show where B2B brands discover how creator led content drives pipeline, builds trust and grows long term brand equity. Each episode we speak with business leaders, founders and creators who are defining their categories. I'm your host Marcus Sherwin and this is the creator economy for B2B. Hello, welcome today to Not Just Ads, the creator economy for B2B. Today I'm delighted to be joined by Vikash Kaushik. Vikash heads up Demand gen at uh, Rocket, but he has a number of years experience in the space. He has created his own AI Playbook. It's a site we'll include in the notes after our conversation where it is he's linked about 85 tools to that. So if anyone wants to get a good insight uh, into AI, GTM and demand gen, I think Vakash is a really good person that can give us a good detailed insight on it. I'm really looking forward to our conversation. Vikash, thanks for joining us today.

Speaker B: Of course, thanks for having me, Marcus. Yeah, always excited to chat about all things marketing and off late, anything and everything about AI.

Speaker A: No, thanks for joining. One quick one. In your opinion, and I know we're diving in at the deep end though, what is in your opinion and feel free to be as honest and open as you like, what kind of thing do you think is more hype than actually business impactful? When you see AI now there's so many tools, it's overwhelming for people. Tech stacks are getting more bloated and when you look at when the data comes out, I think Pavilion put a report in last, no the beginning of this year and I believe it was like, oh, was it 60% of reps that didn't make quota. Now there's probably a number of different external factors for that as well, but I think when you look at the tech stacks, what's available there, it's overwhelming. But from your opinion, what do you look at to see what's actually impactful but also what you see that's actually what's just really noisy and can actually be maybe more of a distraction from actually being an impactful impact to the business?

Speaker B: Yeah, good question. So I think I'll uh, take a couple of steps back. Right,

Speaker A: sure.

Speaker B: When it comes to the AI side of things, there's this sort of thought process in the sense that if we add AI on top of everything that we're doing today, it's just going to compound, it's just going to improve our productivity and that sort of stuff. Right. But What I typically tend to see is when you just add AI on top of the existing processes and all of that stuff, it is only going to amplify whatever you have. And most of the time, I'll just take one small example. If you take any CRM across any companies, it's usually like you, you can't make sense of what's happening, right? It's very hard, right? And when you add AI, ah, on top of that and ask you to like analyze and all of that stuff, it's just going to give you answers that you're definitely not going to be happy about, right? So that I think is where I think people will have to start. And that I think is what is like at a very male level, right? That is, I think, very underrated. The quality of the data in, in all of the systems is extremely underrated, right? And the overrated piece is basically all of the things that you see on LinkedIn, right? Everyone saying that, hey, comment, this common skill or uh, common prompt, the prompt is basically just helping you. It is your way of trying to guide the LLMs, right? That's how I look at it. And if the underneath, if the data that is underneath all of that is shit, the output you're going to get is also shit, right? So the data, and as a result of clean data, the context that you feed your LLMs, the AI and all the tools, right, That I think is like super critical and right? That is at a very meta level, right? One layer deeper in my opinion today, I think because of everything that's happening in the world because of AI and all of that stuff, obviously every single tool out there is trying to add AI on top of their existing product and trying to sell it so that they can stay relevant, right? The problem with that is the, the, it's a fundamental shift that is happening, right? And the architecture that was used to build the SaaS product back, say before 2023, before ChatGPT era, is completely different from what people are looking for today, right? If you take any tool that was built in the last say one or two years, right? Their fundamental architecture is, has already taken into account that, hey, AI is changing the world, so we need to build the product in a certain way, right? That I think captures uh, a lot of the nuances that people typically crave for when they are asking questions to these tools. And essentially the AI, right? Versus, if you take any of the products that were like before the AI era, uh, slapped AI on top of their old architecture, which if you've played with any of those, you know, old tools, right. You will see that this is like, you'll notice the response from those tools being like, okay, this is good, but I will still need to refine the prompt or refine, go through multiple iterations before I can get to a state where, okay, hey, this is good enough for me to take it to either share it to my manager or, or do a second pass at it or whatever. Right. That I think is what is like overrated versus underrated, especially if you are like out there looking for tools and all of that stuff. That is one thing that I am personally looking at when I'm evaluating tools, which is when was this product built? Right? And even if they are like, even if they were built long time back, is this company making a genuine effort, rewire their product architecture to make it AI first and all of that stuff. Right? So those are like the two high level things that I, I think are like overrated and underrated today.

Speaker A: No, it's interesting you mentioned there about like how uh, just putting it onto something else, it's going to amplify what's not working already. But when you look at say some companies and they go in and the foundations are off, let's say that there's bad data quality, there's the CRM is very messy and stuff. Do you think there's any AR tool or AI tools I should say that can help clean that up in a way that's much faster than going manually? Or do you think it's like actually they need to really start from scratch and go look, what are we measuring M? What's the input that we have, how reliable are the sources, how frequent is this input and when was the last time the hygiene M was ran on it?

Speaker B: Yeah, so I'll tell you how I typically think about it and then I'll probably share a couple of tools as an example. Right. So every time you like inherit a CRM, right. It feels a little bit messy primarily because the person who was previously owning it had their own way of thinking about it and all of that stuff. Right. So essentially we are now trying to rewire the CRM to map my current way of thinking and all of that. Right. So during that process as I'm making changes, I typically of course, like we create a list of okay, hey, what needs to change and all of that stuff. But then as and when we make these changes, like I typically look for, okay, hey, is this something that's repeating multiple times in a week or a month or whatever? Right. And Then the question is basically, okay, hey, what is causing this? Right? I'll give you a simple example, right. I think it's, it's fairly common for companies today to use some form of website de anonymization both at a company level and at a contact level today. Right. And all of these tools allow you to create these companies and contacts directly inside your CRM. Right. Many times, hopefully if it was set up properly, it just updates the existing record. If not, it's probably just going to create a duplicate. Right.

Speaker A: Makes sense. So docket for people that don't know what docket is, maybe you could just share a little bit about them.

Speaker B: Yeah. So docket is a conversational AI agent. It sits on your website, it is trained on your, all of your website content. It is trained on any of your internal documents that you have about your product, about your go to market motion. You can train it on your sales call recordings and all of that stuff. So whenever people ask for questions to the agent on the website, even if they go off script. Right. So if you think about, if I take a step back for a second, right. Uh, like the conversational chatbots of the past, they promise the conversational marketing

Speaker A: and it's one you, you've like a journey map. It's like you respond this, you go this way, you respond, so you go the other way. So it's very limited in a way in terms of what's possible.

Speaker B: Exactly. Right. And you can't blame them also, right. Like the tech wasn't available back then, Right. If any of the prospects went off script from what you've defined on the back end, it's just basically going to say something along the lines of hey, give me your email id, somebody will get back to you. Right. But today the tech is available, right. So what we are seeing both for ourselves and for many of our customers is the first sales call is actually happening on the website. What I mean by that is we see people having multiple conversations as long as 20 plus minutes. Right. And these are like super pointed questions, right. So basically a lot of the first sales call, which is typically some form of qualification or SDR qualification that's happening has uh, already happened on the website. Right. And the agent is able to understand that, okay, hey, this person is qualified based on everything that I know about the business and let me actually route it to the right person and book the meeting for them. Right. So that in a uh, nutshell is what docket does.

Speaker A: So you would see then probably as a result of that, you see a Higher conversion rate overall? No, that's the value add that docket provides. Put in the piece of software, it educates the buyer when they arrive, uh, on the website if they have any questions and then when they do book that call, they're definitely more qualified and the rep is more informed in terms of what the pain points are. No,

Speaker B: exactly. And the amazing thing is like we are able to push the entire transcript back into the CRM so the sales rep is actually able to see the entire conversation. Right,

Speaker A: gotcha.

Speaker B: And the other benefit, which I think a lot of GTM folks typically don't think about too much is how quickly the deal progresses. Right. The first call after the, the prospect has had with the agent when they book the meeting, it's not just the uh, just that one person who's having, who's booking the meeting with the uh, they are bringing the entire buying group conversation. So technically if you, if you think about it especially in like huge mid market enterprise deals, right. It's only the third or the fourth call. That's where the entire buying group is involved and everybody joins the call. Right. But in this case it's literally the first call with the AE where the buying group is actually coming on the call and we are able to fast track the deal cycle as itself

Speaker A: and that's a huge value add. What kind of companies do you serve? Is there a particular type of niche that you're, that works really well or what? Where do you see the most kind of product, uh, market fit per category?

Speaker B: Yeah. So Today we serve B2B companies, mostly mid market enterprise companies. I think where it works really well is when the company already has a huge amount of traffic that's coming in to their website and they're already seeing some level of folks who shouldn't have gotten in the meeting who somehow slips through and the SDRs, ah, are like overwhelmed as a result of that.

Speaker A: Sure.

Speaker B: That sort of situation is where we really are able to provide value. The second use case we see a lot is the PLG side of things. Right. So you have a free customer who's all, who's already using. Typically when you have. Typically companies don't want to have NAE involved in when it's a PLG motion and it's a very small company. Right. In those cases the agent is able to handhold all of these free users and try to take them all the way down to the conversion page. And yes of course if it's like a massive company that's coming in, we are able to route them to the right AE as well. So those are like the two big use cases, right? On the sales LED and on the PLG side of things. And yes of course we ourselves use it for the paid ad side of things. If you can start the conversation that I think by itself is like a big success metric, right? Uh, especially for folks who are coming in with a high intent, they're getting their answers, getting answers to their questions and all of that.

Speaker A: So you mentioned that you use it on the paid, I, uh, paid ad ah side of things. So how does that work exactly?

Speaker B: So it's basically two things, right? So folks land on the, so there's two specific use cases. One is like a very generic, let's just take Google Ads for an example. They see the ad on Google, click, land on the page instead of trying to have consume the entire page they can basically just have the conversation with the agent. And a lot of times I, I think you might have seen this as well, right? Like the best case scenario today is people spending 30, 40 seconds tops on a page, right? Instead if you can get them to spend even 2, 3 minutes by having the conversation with the agent and as a result they are more aware of what the product does, right. They are more likely to be qualified. Right? Again, depending on various factors and variables, right. So that I think is like a big plus. Right? So that is number one, number two is a lot on the ABM side of things, right? So we are able to create very specific agents for specific accounts that we want to go after and tell them that, hey, let me take an example, I think that might be helpful. Let's just take Figma as an example, right? Let's take figma. So if we use figma as an example and we are going after them, right? We would have a landing page obviously dedicated just for them, but we would also create an agent, right, Showing them, hey, this is how our agent would behave if it was, if you, if Figma basically purchased the product, right? And the agent would have already been trained on their publicly available content. So we're basically just showcasing, giving them value before they even come talk to us, right? So the entire pitch on the landing page is basically just to get folks from Figma to speak to the agent as if they were evaluating Figma. And obviously on the back end we're able to see what sort of conversations they're having. And based on that we are able to take them and ask them to have the ask our uh, SDR team and the sales teams have a follow up if they haven't booked the meeting all day.

Speaker A: And that, I guess the data that you have on those chats gives you a huge amount of information to create content as well. No,

Speaker B: exactly. It's, it's a bold mind for content. Right, you are, um. So when people are having the conversation, they are basically telling us explicitly about their pains, what sort of situations they are in and all of that stuff. Right. So it helps the content team and the product marketing side as well, like really understand what are those specific trigger points? What are those specific situations where it really makes sense for product, for docket as a product. And that's definitely, uh, a huge plus for sure.

Speaker A: No, definitely. What do you see then from when you're running your head of demand gen, like in your opinion, what just does not work now in demand gen, but people think it works. And then what are you doing if you want to share? That actually works really well. But like the general consent might say no, I. And the reason I give you the. I'll give you a couple of examples of different people that I talked to recently enough. Webinars, for example. The general consensus is webinars are boring, they don't work. But if you talk to someone in like relatively high trust industries like uh, legal, tech or even compliance or anything, webinars still work really well. White papers, another one in biotech, people, like, people would say white papers don't work at all anymore. No one gives information to download the lead. You talk to someone in biotech and they have a couple of like very, uh, specific researchers, subject matter experts on a specific topic. They could have a massive white paper, 20 pages long, but it's very detailed and very targeted at who their, their audience is. People would give in their emails and download it. So I'm always curious to talk to people of what they actually see in the field working versus what the general consensus of like the general narrative of sas. Because there's, there's, it's always a bit different than what you hear on a LinkedIn feed, no?

Speaker B: Yeah, that's true. So I'll, uh, be very honest. I used to be one of those folks who did not believe in webinars. And we ran it as an experiment and it's been a massive success for us. Right. So much that we made it into its own program. Right. So webinars is definitely one of those things that I think folks should definitely test. Right. And I think one of the reasons why webinars get a bad rap is probably because, like it, it basically boils down to the content of the webinar, right. If it's basically disguised as a sales pitch, yes, of course people aren't going to show up. Even if they show up, they, they're basically going to drop off and like fight in stocks. Right. So that I think is a big thing. One very specific example that I think gets a bad rap or uh, people don't trust enough is Facebook ads, especially in B2B even without any of the third party targeting and all of that stuff, right? If you already have a lot of folks in your pipeline, if you have a lot of opportunities, enough customers, a uh, lookalike of those and feeding that to Facebook and asking Facebook to go after just a lookalike of your existing opportunities and close to one. Facebook does incredibly well. And I'm talking just about the small ACVs. We have a pretty large ACV, right. Even for us, it performs incredibly well, right. The algorithm has gotten so good, right. And I uh, think Facebook is now able, is so good that it actually reads the content on the creative as well as your intro and it, based on that information it's now doing its targeting and getting us in front of the right people. Right. So I think a lot of the things that we see on LinkedIn, right, that people say hey, this doesn't work or this is dead. And all of that stuff I think still works provided you, you think about it the right way, right? You have the right mechanism, you have the right sort of content and all of that. So those are two big things that I thought never worked. We tested it and it's working well for us. So we're gonna continue doing it till it works for us.

Speaker A: Great. You're right about Facebook. I think the thing about Facebook is like 90 or 95% of their business is their ads business, whereas LinkedIn, it's probably about 40% comes from marketing solutions. And um, you can see with the algorithm recommendations in LinkedIn they're always trying to twe tweakers. There's a lot of kind of pushback now about the experience. They're trying to do different things. I still think there's still huge opportunity on LinkedIn. But the challenge there is that the traffic is very expensive. If you can. If you're solely using LinkedIn as a standalone channel, I think it's probably going to come out very expensive. But part of the mix overall for B2B I think it's obviously crucial. What do you see with kind of channel mix at the moment of in your opinion? Like if we stay on the topic of B2B, specifically Facebook, obviously you run on LinkedIn, you're quite experienced there. But anything else that you kind of think, you know what our audiences are actually here, uh, in communities or even Reddit or what have you tried that? Uh, you're, we're surprised with results either positively or negatively.

Speaker B: Yeah, Reddit is one of those things that pops up very frequently. It's actually been a while since I tested Reddit to be very honest. I used to market a developer product back then it was amazing. Right. But since then it's actually been a while since I gave it a uh, proper test. But apart from that, I think what is, what has worked well for me in the past is definitely creating this sort of like an ecosystem where it's not just you who's talking about your product, it's your customers. You have influencers raving about you. Right. When that sort of happens on a, uh, like when people see everybody around them speaking good about you, that definitely helps a lot. Right? Community is a good example of that. Right? Ah, at one of my previous organizations we invested heavily in, in communities where our target audience was basically spending majority of the time. Right. So we would partner with the community, we would run webinars and all of that stuff. We would be on the newsletters. You can get some immediate pipeline out of it, but it's hard to you get down the rabbit hole of attribution and all of that stuff. So it's a little tricky.

Speaker A: That kind of leads me on to the next point then around B2B creators and that's grown significantly since LinkedIn has brought in thought leader ads as well. What do you see it from in a demand gen point of view? Do you see it now as like crucial as your go to market or do you think it's something that it's. You have to be very decisive in terms of the creators that you select, otherwise it's, it can be very costly.

Speaker B: So it's definitely be part of a program and a strategy. But I think we do tend to be a little bit selective in terms of who do we want to like partner with and all of that stuff. Primarily because of the factors that I just mentioned. Right. So one is majority of their audience like very similar to our ICP that we want to go after. Right. That is like obviously at the foundation and the kind of content that they post, does it resonate with our icp? If not, no matter what they say, it may or may not, it might not land well. Right. So that's number two. Right. Things like the Impression and reach, I think is again, very specific to how much the sponsor, how much the influencer, uh, charges. And as a result, you take into account the CPMs and all of that. Right. But overall, like, it is definitely a huge part of the mix. Right. And the way we'd like to think about it is, okay, hey, we have this one message that we want to amplify, right. And how, what, uh, are like the different ways for us to amplify? Yes. We can do the typical image ads, we can do the video ads. Uh, right. We can have our own existing employees, internal folks, subject matter experts to speak about it. And we can amplify that through organic and then amplify it even further and make sure we get that message in front of the right audience by sponsoring it, running it as a thought leader ad. Right. And then can. Now we. We've given our best in terms of trying to amplify the message using our own audience. Right. Are basically our, uh, internal subject matter experts and by running ads. Right. So what else is there? That's where influencers and communities and sponsorships come into play. Right. If a lot of the times I try to also push for them to, if we are doing a newsletter, uh, sponsorship. Right. I would also try to get them to do a, uh, LinkedIn post as well so that they can do the thought leader ad. Because like I said, it helps with amplifying that trust and the credibility and all of that. Right. So that's how I approach it so far and it helps a ton. Right. So I wouldn't say so. So the way, if I have to summarize, right, the influencer and the creator side of things has definitely grown a lot, especially in the last couple of years. But the way I used to think about it, say one and a half, two years back, is completely different from how I'm thinking about it today. Because back then the algorithm was also different. We was getting at least 50,000 impressions organically. Right. That's no longer the case. So, uh, we have to think a little bit more strategically when we go for it.

Speaker A: No, that's true. It's definitely much more pay to play now, I think. And you can see that as LinkedIn is more integrated into Microsoft, that will continue even more. What, from yourself, because you share a lot of content on LinkedIn. What do you see from your own approach of like, sharing content? Do you still follow the same rules as you would before in terms of sharing what you're working on, seeing what's work and what's not, or have you looked at, okay, how can I change my approach so that I can continue to get reaching the right people and it's good for your own personal brand, but also for docket and stuff as well.

Speaker B: Honestly, the more I've tried to optimize for reach the, and try to gain the algorithm, the less successful I've been. I have had better success just in terms of engagement and reach and all of that stuff purely whenever I share out of personal experiences, which is basically sharing whatever that I'm doing, sharing the mistakes I've done, sharing the uh, sharing my playbooks and all of that. Right. Yes. I try to be a little bit careful so that I don't reveal sensitive information and all stuff. But at the same time I think the typical best practices of trying to optimize for reach and all of that, there are certain things that I'm not comfortable with. Right. So for example, I wouldn't post a selfie just for the sake of it. Right. Picture of my dog so that I can get more reach and all of that stuff. I want to. And another thing that I've noticed is every time I try to go off topic and speak about something else that I typically don't post about, I don't get a lot of engagement or reach. Right. So to answer your question, it's basically me trying to share what I'm doing, what is working well, what is not working well, as much as possible and as transparently as possible. And that has like what worked well for me so far? Anything beyond that? Anything new? Not so much.

Speaker A: I agree. I think the key thing, what I see is really consistency. If you can talk about like keep on the track in terms of your experience, but being consistent, that seems to resonate most of all. I think following the like there are like creators that basically their thing is to follow the. What the algorithm does and like the changes on the algorithm. And I worked in LinkedIn and like even internally we, most people don't know, apart from maybe some people in engineering. And also it's, it's not something that you just go and you go, we'll make these tweaks at the end and then this will be the output. It's more like very small testing. Then if there's any limitations on it, it's that's retracted. Then it's not like one big release and this is going to change everything. I think it's these small tweaks. But if you're constantly creating content around that, uh, I think it limits the quality of your own brand. For future as well.

Speaker B: You are right in. Because it's very hard to even try and reverse engineer what the algorithm likes versus doesn't like as. Right. Unless and until that's like your entire job, right? If you're like a social media. Yes, you're probably going to try different angles and all of that and see what resonates. Right. Even then, uh, like the lens that I would take even if I was like a uh, say a social media manager. Right. If something, if a specific angle gives me more reach and more engagement, it basically tells me that hey, this is the sort of content my audience want and not that, hey, this is the type of content that the, the algorithm prefers. Right. It's like slight shift in like how you think about it. But quite honestly, I don't know anyone who has been able to like reverse engineer really well and say, okay, hey, these are the exact things that you have to do to get maximum bank.

Speaker A: I think the whole kind of selfie image and then like putting it in different situations probably works to some extent, but then in the long term then it's. Is that going to get you in front of or uh, connect you to the opportunity that you want or is it just going to give you broad reach of like people that are. Maybe it's not connected to your world in terms of what you're working on or future opportunities as well?

Speaker B: Yeah. It really also goes back to why are you even posting on LinkedIn?

Speaker A: Exactly.

Speaker B: If the goal is to drive inbound opportunities for your business. Right. The question basically boils down to like you said, is that what you want to stand for? Is that what you uh, want to be known for? If yes, then will that directly give you opportunities and pipeline? The answer? To be very honest, I, in most cases I don't think that is true. Right. Selfies and dog pictures, cat gifs and all of that. It's great for reach, but I really doubt if those ever turn into opportunities or uh, conversations for that matter. Right. Doesn't even have to turn into opportunities. It can just be a conversation startup with folks in your network. Right. If you're not even getting a lot of conversations from your posts, then that essentially means that even further down in the future there's very little chance that you're going to get any opportunity. If you're getting conversations, then hopefully that conversation, say two months, three months, one year down the line might turn into some opportunity. Right. At least you have, you've built that rapport, you've built that relationship. So yeah, I agree with you.

Speaker A: I think it's what you were saying about the webinar as well. If you're going on with a hard sell all the time, it's. I think people get very repellent on that as well. People can relate to if you have a certain challenge that you see in the industry or that you see and it's. You're sharing how you overcome it or an observation or something like that can be quite a lot more relatable rather than the constant pitch of what your services are and stuff. I'd love to talk to you, Vikash, about you initially. Like earlier on in your career, you scaled revenue from like zero to a million on, in, in the demand generation space. Maybe like just from an overview that you could share some of the learnings from how you initially scale. Like when you think about demand gen, that's, it's probably a lot more difficult to scale from 0 to a million than it is from 1 to 5 or 5 to 10. What are the. And if you could just share for the audience, like people that are, maybe have an initial budget in media want to make sure that every dollar counts. What are the key things that you learned? Anything you do differently, if you're to go back and do it again.

Speaker B: Yeah, I think, yes, like the way we did, say a few years back versus how I would do it now would be completely different given all the things that's happening in the world today. Right. But at a, uh, very fundamental level, uh, the uh, the way I try to think about it is if you have a product that means you and you're trying to sell it, you definitely have one specific pain point that you're trying to latch onto and trying to solve for. Right. And if that pain point exists, that means there's a competitor uh, in the space who is not doing that properly. Right? So if you are going after a very known market and there are enough competitors in the space, right. The, my approach has always been go after the competitors, talk about the very specific pain point that they do not solve. But clearly prospects out there are uh, looking for. Right. It could even be a pricing thing. Right. It could be something as simple as pricing. Right. Early on, maybe pricing is the only differentiator. Right. But hopefully over the, over a period of time you will have solid differentiators and all of that stuff. Right. That I think would be like the first place I would go and attack. Right. Because you already have people who are out there looking for a solution and obviously if you are pre revenue or have very little revenue, the Only thing that matters at that point is having more conversations, right? Outbound is one way to do it. But when you get prospects coming in inbound, that is a different signal altogether, right? They come with very explicit interest, explicit intent as well. Their needs and their questions are a lot more appointed at that point. So can we build on top of that would be the first thing that I try to do, right? So if there is such volume, definitely go hard at it, especially against competitors, right? Then as of course I do non brands for the category. If you have more budget and all of that stuff, right? Your typical Google Ads best practices of going high intent first and then expanding right today and then on top of that, my thought process has always been around like, okay, hey, we have something that is capturing whatever intent and interest that is out there. Now, whatever we are capturing today is basically folks who are in the market that's helping us to get in front of them. But how do we, especially if that is working, right? Once, once you get to say 100k, 150 or maybe 200k, you have enough sales calls that are already recorded. I would mine them and try to amplify whatever pain points people are constantly talking about and amplify that on LinkedIn ads. That's where again, things like, again, if you have the budget, maybe some influencer campaigns and that sort of stuff, right? But LinkedIn ads, depending on the audience would definitely hire on the list for me. Because you want to get in front of your target audience as much as possible so that when they are in the market and when they are looking for a solution, you are the first, hopefully one of the first few that pops up in their head and they come and evaluate you, right? So that would be like the foundation for me, right? Once you have that, now it's about, okay, hey, can we be known for one thing? Can we be known for this uh, specific problem that we are trying to solve and can we build a brand around that? Right. Brand is slightly harder at least. So the way I try to think about it is a brand is not just about okay, being known for one specific problem, but it's also all the other different touch points you have, right? I'll give you an example. At my previous organization we were, we were a, uh, scheduling and a routing tool, right? And we were, we had an incredible product, right? People love the product, but what people loved even more was the support that we were providing, right? And the OP and the target uh, audience that we were going after were initially the demand gen folks, right? But later on it was mostly the ops, Personas, rev ops, markup, sales ops, those sort of folks. Right. And these folks, they are tech savvy. Right? But still, when you. It's a, uh, routing product, right. So if something breaks, that means you're potentially losing a prospect. And they were at their highest intent and you don't want that. Right. So when

Speaker A: you're connected to a really good pain point, then.

Speaker B: Exactly. Right. So we were like, the product was awesome. They understood what the product did, the value prop was there and all of that. Right. But because the support was incredible. Right. When I say incredible, we were on their slab. We would, we had the team, uh, solid enough to be able to respond to them in 10, 15 minutes tops and solve their issue within the hours so that this doesn't happen again. Right?

Speaker A: Yeah.

Speaker B: And that's what ops people really love. Right. Because it's a technical issue, it's a very critical piece of the stack. Right. So that played a huge role in defining what the brand looked like for us. What was the company known for? Apart from the pain, apart from the problem we solved? Right. So that is the second thing that I would try to build, right. Once you have the foundation of, okay, hey, we are getting enough demand, enough pipeline to help the sales team, to feed the sales team in the short run. But in the long run, what is it that you want to be known for? Right. And then try to amplify that message as much as possible. Right. I'll give you, I'll give you a very simple example. Right. One thing that we did very often. Right. Was people would organically Praise us on LinkedIn for the support that we were giving. Right. And even without. And back then, there was no thought leader ads, there was no, none of. What

Speaker A: was the name of the company? Vikash. Just so we can, if you don't mind mentioning the company,

Speaker B: the company was called RevenueHero still exists. They're a competitor to Chili Piper. Right. So what we would do was we would basically take a Screenshot of the LinkedIn post from our customer. Right. And we would keep amplifying that. That way it wasn't just that one specific instance where the prospect or the customer spoke highly about us. It was also like one week later it would be me reposting, taking a screenshot and posting that. A week later it would be one of the co founders. Another week later it would be another co founder. And then by the fourth week, there'll be another customer who would be speaking highly about us. And the cycle keeps repeating, right? And as a result it gave all our uh, prospects at that time this perception of, hey, everybody's talking about revenuehero constantly. Right. And that kind of helped build the brand. That ad at that time. Right. Or uh, maybe even today has. Right. So that is how I, I try to think about it. It's not just the ad set of things. But okay, what, what is this other piece of the puzzle that we can latch onto and amplify that.

Speaker A: And it's. When you think about. It's a, it's a fundamental thing to be able to try and solve a problem for a customer. But sometimes brands don't really do it. And are they maybe it's not that they maybe intentionally don't prioritize it, but because of scale and so on, but ones that do. You do have a lot of probably loyalty with customers then if they like the product, but also if they get a good service when something goes wrong,

Speaker B: 100%. In all fairness, it is definitely very hard to like nail the uh, pain point for sure and build a product around that. Especially today. I think today it's probably a lot more easier to at least experiment and run multiple tests and see build multiple things, at least an MVP version of it. But I think the harder part is definitely going to be the distribution side of things for sure. It's. Yeah, I think that's where uh, the product knowledge and just really understanding what the prospect on the other end is going through. Right. Like it's very easy to. One of the things I've learned. I think it's probably common knowledge most folks today, but for me it was very fascinating when I realized it, which is the closer you get to revenue and the uh, and you are able to solve a very specific pain point and if you're closer to revenue, it's a lot more easier to prove the value. Right?

Speaker A: Yeah.

Speaker B: Versus if you're farther away from revenue. Right. Or maybe even post revenue. Right. So things like upsell and cross sell, uh, it's very hard to say that you are the only reason why upsell happened. Right. Because there's multiple factors involved for the upsell to ever happen. Right. Versus in revenue heroes case and today eventually Pepper and a lot of these folks. It's a very specific point in the journey and as a result it's a very specific pain point that they're solving for. So it's easy to tackle that head on and then also very easy to show ROI and value result. Uh, right. It has been my learning and it was, I was like, okay, this is very interesting when I realized,

Speaker A: oh, for sure you're bang on there. I think the closer that you can get to, uh, proving that you're impactful with revenue, the more crucial you are, whether that's like a service provider that's working with the company or your product as well. I have a couple of notes here that I wanted to ask you about. LLM Discoverability. How are you looking at that now in terms of how do you. Because the way people discover people now is predominantly on LLMs. Okay. I know Google, like, they have the Gemini, which kind of sits on top of search and so on, but it's changing in a way. And, um, I'd be curious to see how you look at that and how you think that you can do things in order to, to shape that perception or not. Not the perception, but to shape how you get recommended versus competitors.

Speaker B: Yeah, I'll try not to get into the tactics because I'm not a genius. I used to do some SEO back in the day, but it's been a while. Right. But some frameworks that I sort of like to follow and we are doing some of that over here at Docket as well. Which is again, it goes back to the sales conversations and the call recordings. Right. Ultimately, you want to be known for one specific category or one specific thing. Right. It could be a category, a pain point that you solve in that category. Right. And alternatives. Right. Some version of that. Right. And then are you. Or are we able to, like, able to. Are we able to create content around that? It doesn't necessarily tie back to the search volume or the keywords and all of that stuff. Yes, those are still important. You still want to invest a bit on the SEO side. But if you are able to answer the questions that your prospects are typically asking for or around certain topics that you see popping up repeatedly. And while answering those, if we are able to ensure we are using the same messaging and positioning for our brand, that will eventually help LLMs to understand that. Okay, hey, this is what Docket stands for, especially as they like crawl our website and all of that stuff. Right. So that is one. Number two is this is a little bit more tactical and a lot of folks might not agree to me, but I think we've seen enough examples of it working, which is the LLMs.txt. i know it's a little bit controversial on LinkedIn. The way I think about it is you have a structured page for the SEO side of things, which is your sitemap xml. Right. It basically acts as a way crawlers to easily find all the pages that are there. You're basically helping crawlers to find more pages. That is exactly what LLMs txt is in my worldview, right, which is every time the crawler or uh, the LLMs are coming to your website and trying to understand what you do, the LLMs txt is basically your way of helping these LLMs understand a little bit easier, a little bit faster about what you do. And you're basically giving them directions on. Okay, hey, if you are looking for this information, go to this URL and this is the information for that specific topic, right? It is very similar to sitemap XML in my head. So those are the two things, right? Like one is being consistent with who you are and what you do in your content. Two is uh, trying to answer the most common questions or basically what folks used to call as middle of the funnel type of content right around the product, around the category, around the pain points as much as possible while staying true to your positioning and messaging and then making it easier for the LLMs to crawl your website and understand. What is it that you do though at a very high level. That's how I think about it. You have the citations trying to get mentioned on other people's statisticals and all that stuff. I'm not an expert to comment on that right now, so I will leave it to the experts to say more on that.

Speaker A: But I think the, what you mentioned there as well about staying on um, brand, staying on topic, that's a real discipline in itself. I think of companies that are like really staying there versus staying relevant and making sure that they stay on brand and then the data shows from all the research, like once you do that definitely compounds after a year or more. It just, it takes time in order to do it. Especially with B2B cycles as well.

Speaker B: Yeah, it's definitely a discipline, right. Especially I think it's a lot harder for early uh, stage companies especially as they are trying to figure out uh, what is it that, what is the product, what is the specific pain point that we're trying to solve and all of that stuff. Right? Which is why I feel like it's a lot more easier once the product is a little bit more established and you are seeing some, some momentum in terms of the pipeline and you are seeing some success because now what is it that your prospects want, you know, what is the market wants? So it's, it's a little bit easier for you to stay on brand and keep the messaging consistent. And then the second challenge is I Think for certain types of companies where they, they might be a multi product company. Right. So for them I think the challenge is going to be a little bit harder because they have multiple verticals, multiple products that they're building. How do you help the LLMs to understand that? Right. And without getting, without confusing the LLMs, basically. Right. You want the LLMs to understand that, hey, I'll take Freshworks as an example. Right. Freshworks has multiple products. They have a help desk, they have a, uh, ServiceNow competitor, similar product. Right. So what would it look like for Freshworks? Right. The LLMs need to understand that Freshworks are, is a multiple, multi product company and the different products that they have are the help desk, the ServiceNow competitor. They also have uh, a CRM M, I think. Right. So that would be like a completely different challenge for them and I think it'll be a significant challenge for sure.

Speaker A: Your website where you've reviewed about more than 85 AI tools, one that I think a lot of people talk about now, and it's not necessarily an AI tool, but it's a, uh, kind of the hot new tool that's been around for about two or three years, that's got well known in about two or three years is clay. And I wonder from your own perspective, because you hear two schools of thought. One is really the advocates that are like, this is amazing, it's Excel on steroids, the possibilities and so on. But then the really interesting thing for me was I saw that the founder of Clay, they were trying to break into enterprise accounts and what he did was he bought a load of merch from Augusta. I think he posted it on LinkedIn about how he went to a shop that was selling merch for the Masters. Augusta, they have the green hats and so on for the golf Masters. And they just started sending it then to prospects and as a result they got meetings. Now what they did say was they used clay to find out, uh, which of the prospects were actually fans at golf, based on different signals and so on. I just wonder. I've used the tool myself. I can see it's quite good, but I also think that used wrong, it can be like spam on steroids. From your own perspective. I'd love to hear how you use it if you think it's good, if you think it's just really well marketed.

Speaker B: No, I generally think Play is an amazing product. I've been using them for multiple years now. The challenge, like you said, is if you don't use it properly and if you don't Use it well, it's. You're basically just going to be spamming everyone in your tam, right? The, I think play is amazing if you want to search for a very specific signal, right? If, if all you're trying to do is basically just end, take a company, enrich some of your ICP, get their email IDs and work phone numbers and that sort of stuff, there's plenty of tools out there, especially today. I would go to the extent of, to some extent a lot of those basic stuff I think even plot can do, right? But if you want to go say two or three layers deeper and say, okay, hey, I am looking for some. Okay, I have my TAM from this spam. I want to understand who, uh, are all the companies that have in the recent past changed their terms and conditions page or change their privacy policy page, because that could be a sign that maybe they are probably evaluating something in the compliance space. Right. Though that's a very specific signal that you're looking for. Again, some of these signals, like the latest funding announcement, job change, hiring signals, that is very commoditized, right? Like everyone can do it. I think like I said, again, I would say, I would actually categorize a lot of those into the basic enrichment and say that a lot of that I'm sure, uh, Claude and ChatGPT2000X can get it, right? But like I said, if you want a very specific data point for a very set, a small set of customers or tam, then I think play is amazing. Um, yes, you can do a lot of other things on top of Clay as well. Like I know, for example, Clay can mine the, uh, call transcripts and understand if a specific phrase was said. I'll take an example, right? If your company has a habit where your AE is constantly asking every single prospect on where they heard about the company, right? Clay can basically mine that transcript, take that text, normalize it, and then push it to your CRM to a very specific field for that specific contact, right? There's a lot of these very specific use cases for Clay, right. The challenge I think is for a lot of the OPS folks is basically, I think to a certain extent you will get to a point where you have to ask yourself the question, hey, do we need CLAY for this? Or Can Plod or ChatGPT do this for us? Especially if your organization is not in the API. The enterprise plan, right? On the enterprise plan, On Claude and ChatGPT, the API charges are insane, but if you are using the subscription plan, it is relatively cheaper, right? For a lot of the things that are basic, you probably don't need play because Clay, I think clay has also realized that and which is why they made the pricing change very recently. So I think that is the question that every OPS and anyone who's basically handling clay will have to repeatedly ask themselves. Hey, should I run this via Clay or should I run this via, uh, the usual LLMs that I'm already using?

Speaker A: You make an interesting point there. Because I think that's definitely going to be the big topic of conversation about like the efficiency of using tokens and so on. And I think a lot of companies that are trying to become more AI fluent have like, for some of their employees, like they have a KPI of like how many tokens are used and now they're also seeing like, that doesn't necessarily correlate to efficiencies. So there's definitely going to be a question of is what LLM you should use and where you use it based on what the actual business need is as kind of, it seems to be the way the industry is going as it matures a bit.

Speaker B: Yeah, I think we will get to a point where the OPS team will have some infrastructure built for so that they can like orchestrate which set of employees get what set what types of tokens, right? What types of models? Basically that is one. Number two, basically goes back to the topic that we spoke about at the start of the call, right? Which is basically, hey, if adding AI on top of your existing processes will not necessarily drive more better productivity or better efficiency if the underneath, if the data underneath is not great, right? So that I think will still play a huge role, right? So I'll give you an example, right? A lot of the examples that you see on LinkedIn, especially around paid or at least I see a lot of paid examples, right? Yes. AI can automate a lot of the analysis that I'm doing. It can even publish campaigns for me, it can create the creators for me and all of that, right? But if my messaging isn't on point, if my offer isn't great, right? That is a foundation, right? If that isn't great and if the CRM is not connected back to the ad networks and the data isn't going back to the ad networks, there's no way the ad network is going to know what is good and what is it that we want to optimize for. Right? That is what I mean when I say the foundations, the efficiency and the clean data and all of that stuff, right? Yeah. So what Claude, if you had implemented that what AI has actually done at that point is basically amplified whatever you already had, right. If it was good, it's going to amplify the good. If it is bad, it's basically going to make it even more worse and it's going to show it to you, right?

Speaker A: No, that having the right foundations is really crucial. AI is not going to fix that at all. I think that's why with even LinkedIn Capi, the conversion API is like kind of crucial for anyone that's invested on the platform. Before we finish up Vikash, I'd love to hear from you what in terms of GTM also it like kind of media as well. Any tools that we talked about Klay, but anything else that maybe people are not as aware of that you have been a game changer for you, you've reviewed ton of tools. So what do you think would be like uh, some of the ones that you think are uh, useful.

Speaker B: Yeah, definitely. Check out docket.

Speaker A: Of course, we'll link that in the show notes.

Speaker B: So one of the things that has been a game changer for me personally, and I'll give you an example, we spoke about how Facebook has been insanely good for us, right? What so the tool is called Full Integrage. It's a data enrichment tool. All right. One of the things that I really love about Full Enrich is basically, I can basically give it somebody's personal email id. It will reverse, it'll do a reverse enrichment, find their professional network data and give me their LinkedIn URL and their work email ID. Right? I'll tell you why this has been a game changer for me. It this single tech stack, this single tool alone was one of the big reasons why for me our Facebook campaign was so successful. I do not enforce a work only email today, right? Most of the webinar registrations that we get are actually personal email IDs. But when I enrich those personal email IDs, most of them have our, you know, they fit perfectly into our icp, uh definition. Right? They were, they, they have the right sort of companies that we want to cooperate. And because I don't enforce that work email, because I don't have that restriction, the conversion rate has been much, much better for me versus asking for a work email. We actually ran the test. It's day and night difference, right? So if anyone is running a webinar registration sort of ad, uh, or uh, even a legion sort of a campaign, right. Like download ebooks or white paper or whatever, right. I would highly recommend not Enforcing the work email restriction. Enriching the personal email IDs using Full Enrich. Right. And the second thing it is connected to this is once Full Enriched gives the data back and feeds into us, uh, CRM, we then use that data and only if it fits our ICP criteria, only then we send it as a conversion back to Facebook. Right. So now we are actually feeding Facebook what exactly we want instead of

Speaker A: depending on them.

Speaker B: And all form submissions are a conversion. Right. So yeah, that would be a big. Where

Speaker A: is the initially where you're getting the lead then? Is that from LinkedIn? Are you running an ad on LinkedIn and then they're downloading it there or where does the lead initially come from?

Speaker B: So the. We are running the. I haven't run the webinar campaign on LinkedIn. We are running it mostly on Facebook today. So the ad runs, they click, they land on the landing page, they fill in their details. Most of it are, uh, personal email IDs. It comes to the CRM and I have an API hitting Full Enrich that automatically enriches them and then sends the data back to the CRM. And once it satisfies that condition, we have only then we send the uh, conversion event back to Facebook via capi through Zapier. And that is the full loop we have,

Speaker A: uh,

Speaker B: running today.

Speaker A: We'll put it in the show notes. I've heard of. I haven't used it myself, Full Enriched, but it definitely sounds like it's a really useful tool. I think the other thing as well, I think like a lot of people that are on LinkedIn and if they're going to fill in a lead form or they're going to, they usually don't always have their work email address associated with their LinkedIn account. And it doesn't mean that they, they won't be interested. So I think that's always a thing to take into consideration as well. Full Enrich and then Clay. Do you see them as two separate things or is there some crossover in terms of the offer that they have?

Speaker B: I think there is definitely some crossover. Right. Like I said, you can do some level like basic, uh, enrichment in clay as well. Right. But the way I've been using them in parallel is for a lot of the personal email enrichment sort of things, I go to Full Enrich. The data has been much, much more, better and uh, for more nuanced signals, uh, I typically lean towards Clay.

Speaker A: Interesting. The cache. It was great having you on. I think the audience are going to learn a lot from you. Sharing what you shared today. If anybody wants to find you, hear more about docket, we'll obviously put it on the show notes. But where are you most active and where do you share your thoughts and challenges and what happening as relevant in the B2B industry?

Speaker B: Yeah, I am mostly active on LinkedIn. Like most B2B marketers. You can search for my name, Vikash Kaushchik. I mostly share my thoughts over there. I've recently been sharing my playbooks, my prompts, and all of that good stuff about AI on a, uh, separate website. It's called get wicked growth. So getwicketgrowth.com we'll

Speaker A: put that in the show notes as well.

Speaker B: Cool. Awesome. Yeah, that's where I share all of my AI experiments and all of that stuff. So

Speaker A: great. Vikash, thanks again for joining us.

Speaker B: Thank you so much, Marcus.

Speaker A: Thanks a lot,

Speaker C: Sam.