Customer Success Playbook Podcast Season 2 Episode 24 -Alok Shulka - FunnelStory

In this episode of the Customer Success Playbook Podcast, hosts Roman Trebon and Kevin Metzger welcome Alok Shukla, co-founder of FunnelStory, to discuss how AI and data analytics are revolutionizing customer success. FunnelStory is a platform that provides product funnel intelligence to optimize conversion, adoption, renewal rates, and revenue growth for software companies.

Alok shares his journey from a two-decade career in cybersecurity to launching FunnelStory, driven by the challenge of processing diverse customer data to make informed decisions. The conversation delves into how FunnelStory leverages AI to enhance customer journeys, identifies and addresses bottlenecks, and provides key benefits and ROI for companies automating their customer lifecycle management.

Listeners will gain insights into FunnelStory's AI-driven approach to improving customer segmentation and targeting, predicting customer behavior and outcomes, and the democratization of analytics through a revenue chatbot. Alok also highlights real-world examples of FunnelStory's success in optimizing customer journeys for clients, emphasizing the platform's ability to rapidly integrate and analyze data, providing immediate value.

Tune in to learn how FunnelStory is setting new standards in the customer success industry, enabling teams to achieve faster onboarding, better adoption, and proactive retention strategies.

Key Points:

1. Introduction of Alok Shukla and FunnelStory.
2. Alok’s background in cybersecurity and the transition to customer success.
3. How FunnelStory leverages AI to optimize customer journeys.
4. The importance of rapid data integration and visibility.
5. Predicting customer behavior and outcomes with AI.
6. Real-world success stories of FunnelStory’s impact.

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You can also find the CS Playbook Podcast:
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You can find Kevin at:
Metzgerbusiness.com - Kevin's person web site
Kevin Metzger on Linked In.

You can find Roman at:
Roman Trebon on Linked In.

Transcript

Roman Trebon: 0:22

Hi everyone. Welcome back to the Customer Success Playbook Podcast. I'm Roman Trebon and with me always is my co host Kevin Metzger. If you're listening, do us a huge favor, give our show a rating, subscribe to our podcast, and like it so we can continue to grow our audience. Kevin, how are you doing this week?

Kevin Metzger: 0:42

I'm doing well. July's already passing by pretty quickly. you saw the fireworks.

Roman Trebon: 0:48

Did you do anything for 4th of July?

Kevin Metzger: 0:50

Yeah, we headed up to Chattanooga and actually, I guess it was on the 5th, but yeah, we went up to Chattanooga, had a nice day up there and spent some time walking through the city and walking along the river. It's a great, great city. I hadn't been there in a long time.

Roman Trebon: 1:06

Yeah, it's a great city. Well, I'm sure you were battling that heat just like we all here in the South, I guess all over the country battling the heat, but I'm glad we're doing the podcast indoors today and the nice cool air conditioning. Kev, we got an awesome show lined up. You want to tee it up for us?

Kevin Metzger: 1:20

Yeah. So today we've got the pleasure of speaking with Alok, who's a co founder of Funnel Story, a platform that provides product funnel intelligence, enabling software companies to optimize their conversion, adoption, renewal rates, and revenue growth. In this episode, we're excited to discuss how Funnel Story leverages AI to enhance the customer journey and ensures seamless. Transitions between different stages Alok explain how funnel story identifies and addresses bottlenecks, providing key benefits and ROI for companies automating their customer life cycle management will also dive into funnel stories. A. I. Driven approach to improving customer segmentation and targeting and how it helps predict customer behavior and outcomes. Alok is going to share some real world examples of how funnel story has successfully optimized customer journeys for its clients and Alok. We're really excited to have you today. Welcome to the show. Thank you.

Alok Shukla: 2:20

But I want to start talking about travels. I think that will tell you where my mind is coming from. Yeah, perfect. So last month me and my family traveled to New Zealand and we spent almost 10 days in New Zealand eight days in South Island, which was kind of what it's called the Southern Alps, if you will, and beautiful, beautiful place. Your first time

Roman Trebon: 2:47

there, Loke? First time.

Alok Shukla: 2:49

it was my first time. I have actually only twice crossed the equator once to South Africa and this was to New Zealand.

Roman Trebon: 2:59

I'll take your trip over Chattanooga. Nothing against Chattanooga or Chattanooga audience, but New Zealand would definitely get my vote if we're picking between the two.

Alok Shukla: 3:09

I actually was planning on my end, but then I Fell in love with the idea of seeing the location for Lord of the Rings and Hobbiton. I mean, everyone, all one, all of us have a kid inside us and

Roman Trebon: 3:21

looking

Alok Shukla: 3:21

at 20 years back, Lord of the Rings, those beautiful locations and people who are fans of Hobbit, like my son is. Oh my God. They have created a Hobbit village in north of that original village. That entire, all 44 houses they have created, the set exists and it becomes a travel. That's the number one travel destination in New Zealand.

Roman Trebon: 3:40

Wow. That is awesome. And there's Hobbit, Lord of the Rings movies have been on TV like all the time and I'm like a sucker. I see one minute of it and I'm hooked in for the next like half hour. The locations and how they film that is awesome. That's pretty cool. I didn't know they had a whole tourist thing down there for around the world.

Alok Shukla: 3:55

Oh, yeah. And that's the reason why I wanted to put a smile to everybody's face. I mean, it's, yeah, that's great. Okay, let's start.

Roman Trebon: 4:04

Let's start. Let's start with funda story. How did it come to be and you know Sort of where where'd you see the need for this in the marketplace? I'd love to kind of know a little bit about the the origin.

Alok Shukla: 4:16

Well, I think that's So my background is actually coming from cyber security if you believe it. I spent almost two decades In the field of cyber security, I was in companies like McAfee, Intel Security, Imperva, ShiftLeft, SafeNet, you name it. And for two decades, I have been working on large data problems because cyber security, interestingly, has seen large data much before many other sectors saw them. I mean, the amount of attacks that were happening, amount of data that we were generating. We In cyber security had a need to process that data pretty fast and make sense of it so that you can make the right set of decisions. And in my last company, when I was there, I noticed something interesting That I was a product manager by training, but I was also asked to do customer success. And I realized that customer success is a pretty interesting and challenging field. the diversity of data that this ecosystem has to deal with, you have product data, you have CRM data, you have meeting conversation, you have text data, and to be able to make sense of all of them, translating into a single language, sounds a very interesting challenge to me. And I said, wow, I mean, that's, I mean, think about it. You guys are thinking about customer. I'm thinking about data, and that's how three of us in a cybersecurity company decided to jump in. I said, this is an interesting problem to solve and we want to solve it. So that's how we basically got started. And I think we are pretty, pretty happy about so much about what we have done so far.

Kevin Metzger: 5:57

Yeah. So you want to tell us a little bit about the product and kind of where it's positioned?

Alok Shukla: 6:02

So I think if you're asking this question a couple of months back, I might have a different answer, but we continue to develop new things. So I'm going to give an answer which actually is valid for today. in my last company and my last experiences when I was dealing with customer success solutions, one of my biggest challenge was That took a long time to configure products, and I was surprised by that Let me kind of go back to my past and I tell you the context I come from. There is a very large shoe company in US and I'm not going to name it. But they were my customers when I was at Imperva and they used to launch shoes big shoes, new shoes. And and they had a special promotion on a digital manner, like come to the website we will launch issues and the biggest fans will get the first dip in the shoes, like they will get those first designs. For the fans, it's important thing. And what started to happen was that the moment they used to launch the shoes, that most of these shoes were very, very quickly taken out by the bots in 20 seconds. So think about you, your team launched a marketing campaign and all, but like a fraction of shoes are left at rest. Everything was taken by bot fans got nothing. Your entire marketing campaign was sucked dry. And so see the problem at that point of time for these guys was to look at all the data in real time, process it and make the decision whether you're dealing with a human or a bot. So the challenge at that point of time we were solving is to how to process very, very large amount of diverse data and make sense of it pretty rapidly. And here I am in customer success getting the answer that, Oh, it takes around three months, depending on the size of the company to just get your customer success platform going. And I was like, wow, that is from the modern age to the stone age. Right. And so at that point of time, we basically said that we need to solve for this. So we started with the first principles. we basically built out an entire system so that we can connect to any kind of data, any kind of system, transfer them to a common model and build a visibility for you in less than 24 hours, Our current deployment time is less than two hours. We can connect to any kind of data and we can show you visibility into ours. Then we go to the second problem that how you make sense of it. How can most of the customer teams start with customer journeys? They want to say that what the journey is so that they can then decide what are the places where we need to connect with, engage with the customer so that they can adopt our product well Now the question here is most of these journeys were being decided by it. People sitting in the room with a very informed opinion, I grant them that, but there is a value of data. Can I discover the journey from historical journeys done by customers, your successful customers, looking at your data and recommend to you, these are the multiple things that your customers have done and this is the best journey. So giving those journeys so that, and then basically identifying the places where you can engage with them. Which customers need help? how can you model it from a digital perspective? Thank you. So doing the solving that problem and then the third problem was that can I use that data now to start predicting which customer is likely to churn because I'm looking at so many customers behavior and I have a very good idea of what model looks like when somebody's about to churn or somebody's looking like being retained that's her problem and fourth problem was the democratization of analytics. Right now, if you want any analysis you deploy your software, it has some custom dashboards. You basically connect to the data source and you start to get something. But most of us know that those dashboards are always not enough. You need more context, more information. Sometimes you need to get that information. And all of us keep creating dashboards, keep creating new, new reports to answer new questions. But if it gets complex, You will have to ask some solution engineer and solution engineer will only work for that person who has a better hierarchy in the organization. The seniors will say, first you write my report, these guys can wait. So we wanted to democratize action so that everybody should be able to get answers from the system anytime, anywhere, any question. So we thought about launching a revenue chat bot, which can access your data and anybody should be able to ask any kind of question, simple or complex. And it works similarly for everybody. So summarizing this, what we do, we provide visibility data rapidly. With a speed that is valuable, cut down the time of implementation, cut down the need for having engineers. Number two, we help you master adoption, better adoption by discovering historical journeys. Number three, we are focused on Helping you understand which customers are likely to churn or likely to retain so that you can take action before bad things happen.

Roman Trebon: 11:20

Two hours to get on board. So we just set, my team just set the record for us on how fast we onboarded. that is an insane quick speed to value and then less than 24 hours to get stuff up. that is awesome. So in terms of the visibility, the mastering, adoption, the predictability, Where do customers typically start with Funnel Story? Is there one of those that they really gravitate towards first? Is it analyzing the historical, like where do they start when they start to use Funnel Story with their data?

Alok Shukla: 11:49

I think there are two sets of problems depending on your titles. So if you are a classical customer success person who has been in customer onboarding or getting adopted, you will gravitate towards the adoption problem first. And the other people who are mostly focused on revenue, it might be your CRO, it might be your CCO who has been given revenue opportunities revenue management, or who carry a number, they will gravitate towards retention churn prediction. Either of the cases, they both need access to the data rapidly. I will say either of the use cases, they will start with the use cases, but both of them are very attracted by the idea that we can get value fast.

Kevin Metzger: 12:32

Can we step back for a second just to you're saying two hours for onboarding and what's happening in the onboarding and how are you bringing the data in so that you're able to start generating. Information so quickly. is it APIs that you're going in to get data? Or are you driving? Is it CSV loads? What type of data are you pulling and how do you get it integrated so quick?

Alok Shukla: 12:58

I think we will go back to the first principles. So number one thing is because, as I said, the customer success teams are, post sales team generally work on the most diverse set of data that is there for I think any of the function organization in an organization, if you will. So the 1st problem to solve is that if you want to. Give a unified view of the visibility. You first need to convert all of this data into a common format. So one of the things we have done is to create what is called customer activity model, which is basically your accounts have users who perform activities and trend change in activity generate signals. So that's what we call the customer activity model. So what we have done is we have developed a variety of connectors with a lot of data who read your data and automatically convert that data into. Customer activity model. So what we're doing here is we are not asking you for any APIs because we want to work with raw data. We understand raw data in any format and we directly convert that into our model. So we take away a big need for anybody to tell us that, Hey, our data, we accept the data in this way. No, we are not asking you anything. We don't want to even talk to your team. Like we want to work with raw data as it exists. Number one. Number two, look, there are two sources of data. If you have business apps, they already have APIs, whom you can connect and fetch the data as it exists. The documentation is available, you don't have to do much. The challenge comes primarily in two types of data. One is unstructured, and which is whereby, say, the written word. So we have double edged modules, which basically take the text and converts that into our own model. So if you have a chat, if you file a support ticket, if you have a meeting, if you talk to somebody, all of them is written in text and we basically again convert that into the common model. This person from this company talked to us and the signals are basically where were they happy, sad, what were they talked about, what are the keywords they used. Now the hardest challenge is in terms of the product data, but that's where we kind of applied our mind. So what we have done here is that when you look at any product data. So what we tell people, and that's my product manager background, that rather than asking them to instrument their code, put something in the code or put something or dump it as a log, we say don't do anything. All of your products have something very beautiful called product database. And product database generally has most of the data all the time because that's how a product remembers what you had done in the past. A product never starts from scratch, when you log into a product, it knows what you had done in the past. That's how it maintains a state. So what we do is we have built our own unique technologies to connect to the database and automatically reverse engineer all the events that have happened historically since the dawn of your product. And we again don't want you to do anything, we'll connect to the data, we will have developed AI to automatically interpret your columns to kind of start understanding what that data looks like and start generating activities from that. So what we're saying is we avoid talking to data engineers and asking them to work apart from giving us access to the data. And then we also don't ask them to convert into a model because even we do that job ourselves. So we took away the engineering work that was required to fetch and convert data into a language that we understand. We do it ourselves. And that is the biggest chunk of work for any CS platform to deploy.

Kevin Metzger: 16:34

And when you talk about getting access though, to the data, because some of that data obviously is proprietary, right? So if I'm giving you access to my product database of what's happening inside my product, I mean, it depends on the product too. So how is that anomalized? How is it from a security standpoint, how am I. How are you working on getting access to it so that it's not you know, you're not coming in and taking customer proprietary data?

Alok Shukla: 17:03

actually an excellent question. One of the things that we have done is first of all, The fact that all three of us founders come from security backgrounds helps. So I always tell to everybody guys This is something I used to create products to sell to your teams who are going to evaluate us So they are my people. I know them They also understand me, right? So don't worry about it. I mean that is My unique unfair advantage if you will I know you guys like because data is you rightly said there's one of the concerns so we have built our products using the same tech strategies that we used to recommend everybody. We have built it ourselves. So we basically provide all the kind of layer of information on why we are secure so that your security teams can get certified, number one. But number two is that I recommend people not to give me access to the product database directly. I want what is called as a materialized view of the information that we only need to see in a read only manner. I generally suggest everybody give me information through a data warehouse which itself is getting replicated data from an actual product database. So you should not give me access from your product database directly. I do not recommend it. I also want you to give me a read only access because I don't need to write anything there. And I want you to give me materialized view. So that my scope of what I can do is limited. So my security background, it's a trust thing and my approach to getting data where I become the consultant to them gives them a confidence that these guys know what they're talking about.

Roman Trebon: 18:40

yeah, they must love that security background. A lot when you're talking to him about all this data and where it's coming from and how it's getting used, etc. My question is, you know, we're talking customer success, and as you're looking at your funnel stories, pulling data from different sources, I'd love to hear kind of a success story that you guys have. We don't need any client names, but I'm sure there's some really great stuff that clients are getting when they're able to take all this data and really look at it without any bias and seeing insights. I'd love to hear one.

Alok Shukla: 19:09

So I will talk about actually two or three customers. So one customer is a very major startup. they are kind of a series B onwards with the major revenue, major customers. the founders have come from one of the largest security companies in the world. They sold their prior company to this largest security company in the world and then they ran the business there to more than a billion dollar business before starting their current startup and they had deployed one of the marquee, one of the most popular customer success platform and they said I started deploying that for nine months. And I had to leave for starting this new company until that day that platform never got deployed because it was so clunky. And so it requires so much effort. And he asked me to deploy. And when I deployed in, in their case in less than two days mostly because we were taking the permission, he was sad. You guys are out of this world if you have what you just did here, and that was one of the earliest validation of what we were trying to do. And they bought into this and said, this is how people should be. I shouldn't be making decisions, not waiting for the data to come in. It's like that 20 years back, downloads used to happen on internet. You are just waiting. 45 minutes. That word has to go away, right? And then there was another customer who comes from the field of construction robotics so they have basically devices who are in the field who are doing things and that is the product and they are collecting the data and they are dumping the data into data warehouse. It's not a classical UI based product. And the fact that our model was about what a generic model. So we could convert their data into our model seamlessly. Once again, we were the only product who was able, ever able to kind of make sense of that data. the people who used to use those robots were Not the ideal people who come into the white collar jobs who come to the office and do those things and Getting their sentiments about the product from the notes or from the conversation And matching up with the usage into a common model was blowing off them We did that in less than a day. They did not even require us to help them They just configured in less than two hours with that complex data, Interestingly, they were one of the earliest people who gave us feedback about the bot we had launched. They said we are able to ask questions that we never thought had come in my mind. Like I just saw this data. Can you explain me further? And then they asked a chain of questions, one question, two questions, three questions. And because the revenue chatbots, these new technologies are able to chain thoughts, it was able to answer complex questions. That is this customer likely to churn? Why do you think so? What are the factors that are driving this? Can you tell me recent instances that were very angry, they were angry about some things? And suddenly you were talking to somebody, an expert was giving you answers and suddenly you were able to hold that account because you now had not only numbers but a context and a very summary behind things. Does it make sense?

Kevin Metzger: 22:14

Yeah, for sure. Were they able to actually identify? So when the bot says, hey, this customer is likely to churn and this is why were they able to see by responding to those indicators reduction in churn? Like, were they able to actually reduce their churn?

Alok Shukla: 22:30

Yeah, I think this is the difference between a cold conversation and a warm conversation, even a customer success concern. Concern everybody appreciate if you are empathetic to them, but empathy in a customer sense comes from knowing the problem beforehand, try taking an effort to understand where they were wrong and remembering the small details. So, in this case, the revenue chatbot actually tell them that I know that you have a problem, but I know more. One of your team members had this conversation where they had a frustration and I looked back and I saw that there was a support issue that was unresolved and you were not able to use the product and I'm sorry for that. The fact that you took that much effort to know about me and you guys have been in customer success for a long time, empathy goes a long way to get people to drop their guards, right? And talk to you more openly. And I think data helps you get that even if you have never paid attention to that account before.

Kevin Metzger: 23:28

Yeah, that's interesting. I mean, and I agree with the empathy on the one hand. On the other hand, you know, the, the technical problems don't necessarily drive churn, right? It's churns gets driven for a lot of different reasons. So it depends on what.

Alok Shukla: 23:45

yeah, I think that's what I say. Like the product can be tell the customer that don't mix adoption with churn. You can have a perfect adoption. You can have still have a churn. they might be caused by actors or words that were said outside of the product adoption. You don't know that. And that's why you have to observe other channels and actors who are not in the product which you call non product actors. You will find them in meetings and support tickets, but they are not found in the product itself.

Kevin Metzger: 24:12

Are you able to track that in your data as

Alok Shukla: 24:14

Yes. So when we build our account and user model, we are looking at everybody who is interacting with you, whether they are doing in product or non product, but we basically tell them that these guys are not in the product, but they seem to have very strong influence. Over because their actions are highly correlated with how the adoption goes up and down

Roman Trebon: 24:36

You know, look you mentioned you're working with a startup company big company So it sounds like you're you can any sort of size company There's sort of an entry way for them to kind of come in here and and use your solution

Alok Shukla: 24:46

Yes, I mean look the only difference, is for me is Before I even connect to them because larger the company for them to kind of give access to Their data they have to have a much higher bar of getting convinced They have a lot more people a lot more bureaucracy for me to go through before I connect So that is something unfortunately, there is no product solution for that. That is a human thing and I can also see that. I mean, the bigger companies are more risk averse. They cannot just get anything in. They will have to get convinced, they have to convince a lot more people. But beyond that, from a product perspective, once we get in, they ask the same.

Roman Trebon: 25:25

Kavway, any other questions for Alok here on Funnel Story before we get into the hard hitting questions?

Kevin Metzger: 25:30

Well, just from a tech stack perspective where do you run? How do you run? Can you kind of hit that a little bit?

Alok Shukla: 25:38

So we are the AI platform, the post foundation model stage where we have build up technology stack. so by Getting away with the traditional SAS stack, replacing with the AI based stack. So the AI is not like that. You have you will, you will still interact with the ui, you'll still interact with the product, but the underlying layer is a huge LLM and a process mining and a data mining, all kind of ai stack, which is now basically doing bulk of the analysis. In fact, we have baked in a lot of foundational model data into our UI itself. So a lot of UI is not made of. Traditional UI components made of LM or foundation model driven content, which you will not be able to interact with, but that's how the UI is formed. so that's from a tech stack perspective, but otherwise we are a SaaS platform which basically takes your security very, very seriously.

Kevin Metzger: 26:33

Yeah. And, and, and are you on a, so your, your foundation model is, is it hosted like via AWS GCP, are you?

Alok Shukla: 26:45

I mean multiple places. this is not a kind of a static thing. Depends on what is the better thing. We can swap in swap out the different kind of models.

Roman Trebon: 26:53

Oh, look anything we didn't ask you about funnel story that we should we should have.

Alok Shukla: 26:57

No, no, I mean this, that conversation can go long, but get the hard hitting questions in.

Roman Trebon: 27:01

Yeah, that was awesome. alright Kev, I think it's time to move to the tough questions. You ready?

Alok Shukla: 27:08

let's

Roman Trebon: 27:08

do it. All right, I'll start, Alok. Early bird or night owl?

Alok Shukla: 27:14

Actually both. In a startup, both things can happen at the same time. I am early bird as well as a late nighter.

Roman Trebon: 27:23

That's awesome.

Kevin Metzger: 27:25

where do you want to visit next? What's the next place on your bucket list?

Alok Shukla: 27:28

That's a great question. So I have never visited South America, so I want to go to Patagonia. I want to travel from Patagonia to Ghana. I come, my original students from cricket sorry, India. So I want to kind of go through the Caribbean and visit all the cricket stadium that I have seen from the very young days I want to go to Morocco because I visited Spain, Granada and I want to go down and see what we have to see in Morocco. Lots of places actually. I want to go to the Sebelbad, which is the northernmost island at around 17th horizontal latitude, which is north of Norway. Which is the highest one, which is the, which is the highest, not highest, I mean, the most northernmost airport, civilian airport that is around.

Roman Trebon: 28:18

When you're not working, what do you do to unwind, relax and have fun?

Alok Shukla: 28:24

So I am basically, first of all, I travel. We do one international travel every year where me, all three of us will take a country and we'll start from its southern tip and go to the northern tip and keep on driving for 15 days till we finish the country. I read a lot. And of course I watch a lot of movies. I'm a movie buff. So three things.

Roman Trebon: 28:47

Well, then You got a book recommendation for our audience? Either something personal or work related, either way?

Alok Shukla: 28:54

there are three or four books that my first book, I mean, it's, it's very interesting in the context that I, one of the first book that actually got me very much interested in the field of books was a book named Exodus by Leon Ores. It was about the birth of Israel many, many years back, like 25 years back. I didn't knew, but I was fascinated by the story. And I then read a second book called Topaz that was about the Bay of Pigs invasion. Fantastic books. Then there was a book called Slender was the Thread. It was about invasion of Kashmir in 1947. Again, I'm in very political topics. Then a book called Zero to One. I think it's by one of the investors in Facebook founder of PayPal. It's a great book. Blake

Roman Trebon: 29:39

Masters, is it? Blake Masters, Peter Thiel? No, no, no.

Alok Shukla: 29:41

One of the, Peter Thiel.

Kevin Metzger: 29:45

Yeah,

Alok Shukla: 29:45

yeah,

Kevin Metzger: 29:46

I think I've read that.

Alok Shukla: 29:48

Yeah. So and what else? Let me see if I can remember any other book. There was a book on there's a book called singularity, I think. Yeah. which was amazing book. I will say that. So anyways, so these are the books that come in my mind.

Roman Trebon: 30:03

That's awesome. What about movie now? You got to give us a movie, a couple of movie recommendations.

Alok Shukla: 30:12

Can I give you a recommendation about a show?

Roman Trebon: 30:14

I'll go whatever, yeah.

Alok Shukla: 30:16

Yeah, so one of the shows that I was fascinated like nothing else was called Babylon Berlin. It is the biggest German show that was ever created. And it is a three part show, which is basically set up in the 1920s Weimar Republic before the birth of how the Nazism war entering. And they have created a world of early 1920s of Germany, brilliantly written and brilliantly acted I recently watched The Wire. Oh, my God, like it should be kind of added as a textbook in, learning about things. I mean, how much historical they were in understanding of the world before it happened. Just right now I was looking at that tragedy where a ship hit the Baltimore bridge. And I remember that scene when the conversation happened under the Baltimore bridge about the longshoremen.

Roman Trebon: 31:08

Yeah, yeah, yeah. Well, now I'll start giving Omar quotes here, so we won't get too much on the wire here. Oh my God.

Alok Shukla: 31:14

Omar, that guy is a legend. I'm still a fan of it. wow.

Roman Trebon: 31:18

Yeah.

Kevin Metzger: 31:19

That's awesome. I think we probably can wrap it up, but I'm going to have to check out the wire, haven't seen that yet.

Roman Trebon: 31:26

Oh, I've watched it twice already. It's awesome. we'll do a whole episode. We'll bring a look back to a whole wire episode. So, all right, well, look, thanks so much for joining us. This has been terrific. Check.

Alok Shukla: 31:40

Yeah, go ahead. Can I say one thing? I remembered a book that I would like to recommend to anybody who's in the leadership thing. It's called, and I'm sure a lot of people have read it. It's called Thinking Fast and Thinking Slow. by Daniel Kahneman. It's one of the finest books that anybody can read to understand how people make decisions. That was the last book that I finished reading. I'm happy to share with with you guys to kind of put it in the podcast itself.

Roman Trebon: 32:07

Hello. you're texting me at the right time. I'm going on vacation next week. I can see my Kindle wishlist already growing after this episode. I got some books to order. I got a new series to put on the checkout. So this has been awesome. And seriously, thanks for joining us. Check out Alok online. You can find him on LinkedIn. Funnel Story. Check out Funnel Story online as well. and that's a wrap for this episode. As always. Thanks so much for listening. Hit us up on LinkedIn. You can find us at Roman reon at Kevin Metzker. Check out our customer success playbook page. Again, give us a rating subscribe that helps us attract new audience members and helps us grow our audience and get amazing customer success. Leaders on the show, like a look thanks for listening. And as always, Kevin, keep on playing.