How Snowflake Grew Into a $70 Billion Dollar Company & Had the Largest Software IPO in History #scottsthoughts

Welcome to the success story podcast, the most useful podcasts in the world. I'm your host, Scott, and today we're going to be breaking down how snowflake became the largest IPO in software company history. I'm going to walk you through the sales and marketing strategy that took them to a $70 billion evaluation. I hope you enjoy. Okay, so let's talk about snowflake and why I'm even doing this piece. So when I first was looking into some case studies, I like I like putting together case and marketing studies coming nerd like that. I saw that there was a lot of interest on snowflake and when you go on YouTube, you see some people talking about snowflake, but most of the discussions about snowflake are investors wondering why the hell they grew so much and how they grew so quickly. So I thought, you know what? Hell, I'm from sales marketing background. Let's try and do a little bit of a deep dive and break it down. There is some information out there, but I want to disseminate it to you and walk you through why it was so effective, why their strategy was so effective, and also when you start to look at their strategy for selling and marketing to major customers, it's actually not that surprising why they grew the way they did. But let's get right into it. Now, if you don't know what snowflake is, you may be wondering, well, isn't it just another software company, another Silicon Valley story? Well, it is the largest IPO and software company history. That's one thing, but also to give you an idea of how impressive this IPO was, you know Warren Buffett, you know Berkshire Hathaway. So they have not invested in an IPO in 50 years, but they invested in snowflake. This is a big deal. This is this is historic IPO. So let's walk through the let's walk through snowflake. What do they do? So snowflake is a data a cloud data warehouse provider. So they provide server services to companies. So companies, big companies, they need a lot of server space. They don't have it all on site or they don't have, you know, the expertise to have that level of server space on site. That's why Amazon is such a huge company because lots of companies use Amazon for server space and cloud space and whatnot. But snowflake offers these services to customers. Now, what snowflake offers is not brand new to give you an idea of the people that they're competing against oracles in this space, IBMs in this space. Like there are big companies in this space. So snowflake, there are proprietary IP, there are secret sauce if you want to call it that is the fact that when they provide cloud data warehouse services for customers, they allow customers to make massive amounts of requests. That are retrieval requests simultaneously. So when a company is using a cloud provider, they have application. Every company uses applications, you know, whatnot. They have to pull customer data and that's not stored literally in the building where the company is located. So it's stored, for example, at an area or in data center that snowflake trolls. So when a customer, when a company needs to pull a lot of data, they put the request data, applications request data. And sometimes you can have hundreds of thousands or millions of requests at the same time. And not every cloud data warehouse provider will be equipped or capable to service this many data requests simultaneously. So sometimes if you go with a smaller provider, your request may be throttled or if you're tubing a company, it just won't work for you. So that's that's sort of the differentiator for snowflakes. So they do, they really do have a great product. But besides the product, there's obviously other reasons why companies grow. And there's basically four reasons why snowflake grew at the rate that it grew and why it had such a successful IPO. One of them being the sales and marketing strategy, the second being the fact that they did perfect the cloud data warehouse product that they offer their customers. The third being that they completely revamp the pricing structure. So if you are in the enterprise business to business software space, B2B space, a lot of the pricing structure is license or seat base. Meaning if you have one employee that uses my software, I'm going to sell you one license. If you have two employees, I'm going to sell you two licenses or seats, whatever you want to call them. But snowflake did a little bit different. What snowflake did is they set their pricing up so that it was based on utilization. So it makes sense, but it's actually not the status quo. It's not it's not what a lot of companies do. So if I'm using snowflake, if I need more server space, I'm paying for more. If I need less server space, I'm paying for less. You know, who else does this? Amazon does this as well. But many software companies do not sell their services like this. They sell on a per license or per seat basis. So snowflake did a utilization cost structure, which of course was very favorable for customers. And then lastly, they did do some strategic management changes pre IPO. So they got rid of a well-respected CEO that had done very well with the company. And they brought in Frank Slutman, who has a record of IPO's under his belt. He is known as a CEO who's only brought in to IPO at high evaluations. He has an incredible track record. So that was also something they did very purposefully for the IPO. But of course, let's discuss why I'm not breaking down three of the four items that really led to snowflake success. So I'm not going to break down the fact that they built an amazing cloud product because there's a good chance you're not building an amazing cloud product. And if you are good luck, you're up against snowflake or colon IBM. But I'm speaking and I'm putting together this video for a lot of people who want to learn sales and marketing strategy who aren't building the next iteration of the cloud product that's going to compete with snowflake. Also, the utilization model, the pricing model for their software. Well, for a lot of people watching, they may not actually be in a software company. So obviously that doesn't matter and it's not useful for them. But also, if you are in a software company and you do have a pricing structure, a pricing model that is not in line with that, I'm not going to recommend or give you any advice on how to change your pricing structure because I can be damn sure your CEO is not going to be too happy when you told him or heard that you found out from Scott that you should change the entire way your company prices that's product because that is super disruptive and it's probably not going to jive too well. But if you have, for example, an innovative sales and marketing strategy that I'm going to walk through, that's something you can implement tomorrow. And then lastly, why am I not talking about Frank? Well, you probably don't know Frank Flutman and you probably can't afford him. So that's kind of a mute point and it's probably not going to have a big impact on your company. So let's talk about sales and marketing. So what do they do? What do they do? They were so innovative. Well, nothing it was innovative and what they did actually, what they focused on was sales and marketing alignment. Why does that matter? Why does nobody get it? Well, in most companies, let me paint you a picture. In most companies, there is no sales and marketing alignment. Companies have marketing teams and sales teams and marketing sends out collateral to customers. They put stuff up on the website. They put they put stuff up on social media and they do not communicate with the sales team. They do not tell the sales team what they're putting on social media. They don't talk to the sales team about what they're putting on the website. So when the sales rep goes and calls somebody, emails somebody, they have no idea what their marketing teams actually focused on. So the conversation, the sales team member, the sales person is having with the customer is completely different from what the marketing side of the business is focusing on. This is obviously broken, but this is how most companies function. So when a customer, when I'm the customer, I'm looking at a company, social media, I'm learning about their product. I jump on the phone with a sales rep and they're pitching me something completely different than what I was reading about online. A different feature, a different product, a different use case, whatever it may be, that's not a great feeling for a customer. But that's how most companies operate. Normally, the left hand doesn't know what the right hand is doing and left hand right hand doesn't know what they're doing and vice versa. So at its core, snowflake focused on sales and marketing alignment, getting those two revenue generating business units to talk to one another. Now how did they do that? Well, they focused on ABM or account based marketing. What does account based marketing? Well, account based marketing, again, at its core is focused on sales and marketing alignment, but also it goes a step further. So account based marketing, what it means is you are understanding which account you want to sell and market to. You're building those profiles and then your sales and marketing strategy is focused on selling to a specific profile of customer. This is called an ideal customer profile or target customer profile. So you build this customer profile. Now, what snowflake did differently than most other companies is they didn't just model their customer profile off what everybody else in the industry was doing. So what many people will do when they're building out an ABM strategy and they want to figure out what their customer profile is, they'll say, well, listen, let's take this example. So say I'm snowflake and I want to take a product to market. I know that Oracle is selling the same product or similar product. I know that IBM is selling a similar product. So I'm going to say, well, why don't we just go after the same customers that IBM and Oracle are going after? Kind of makes sense, right? But pause for a second, what if there's a chance that IBM and Oracle have not perfected their customer profile? What if it's not absolutely perfect? Well, that's basically what snowflake said, not so many words, but they said, we don't want to just go with the ideal customer profile of the category. We want to create our own and we want to back it up with data and we want to know with 100% certainty that it is absolutely correct. So what did they do? They built out their own customer profile and that's a core tenant of IBM having a customer profile. How did they build out their customer profile, their ideal customer profile that was specific to their product and their customers? They took their 50 biggest deals and they took the 50 deals that closed the fastest and they put that into a tool that actually used a tool called Everstring, which is a business analytics and information tool and that used machine learning to generate the perfect customer profile based on those them. So how which customers close the fastest and which customers are the biggest deals, that's what we want to target and that's what Everstring did for them. So now they had their customer profile and now they can use that for the marketing team and their sales team. But they took it a step further and they didn't just let this customer profile be static. They constantly tested this model. So when they closed 50 new customers based on that customer profile, they brought them in to this tool. They modeled out a new ideal customer profile. So they kept getting more granular, they kept getting more specific and more exact about what that customer profile was. So now they have this constant iterating process of developing this customer profile of refining this customer profile and now that's what marketing and sales runs with. So marketing is marketing to this customer profile. Sales knows exactly what marketing is doing because they're working off the same customer profile and they're communicating and this is how you do proper ABM account based marketing. Now, one more thing they did was they did a specific one to few one to many sales outreach strategy. What does this mean? Okay, so when when Snowflake was first starting out, they had roughly 30 sales rep. They assigned 100 customers and these are enterprise customers. So the like huge, huge companies is a customer to each of these sales reps. What the sales reps did is they split their outreach. So they did one to few one to many. The one to many is automated. So they took 90 of the 100 customers and they were sending automated outreach to employees within these 90 customers or companies they were targeting. Then the one to few, the one to few was personalized outreach to the top 10 customers that they wanted to personalize outreach to every employee of every company that they were reaching out to. So because these were enterprise companies, they were probably reaching out to 10 to 20 to 30 different employees within each one of those 100 customers. So when I say customers, not just one person that they're actually communicating with, they would reach out to multiple people within each one of those customers. But 10 of those customers, it was all personalized. By the way, the act of reaching out to multiple people within a company to try and close a deal, that's called multi-threading. It is a very good strategy for enterprise large deals when you're trying to close a deal. Not going to get too much into that right now. Top it for another day, but look it up. And if you are in the enterprise space, you should try multi-threading. So now we have this one to few where they're doing personalized outreach to 10 customers and one to many where they're doing automated. What this allows them to do is to personalize to the customers. They really, really, really want to close. Then they also have automated so that they can have some scale because of course you cannot personalize everything to everyone all the time. So you have a nice, healthy mix of both personalized and automated. And that obviously did quite well for them because they kept bringing in more customers that kept refining their customer profile. And you rinse in repeat, rinse in repeat, excuse me, so on and so forth. And this was the core of their product. This was the core of their strategy. This is how they brought in customers that were the right size. They brought them in quickly. And another piece they focused on was retention. So part of this entire model was focused on retaining customers. It's not part of the initial, it's not part of the initial, for example, customer outreach. But when you model your customer profile, you want to make sure that customers that you're bringing in are customers that are going to stay with you for a long time. So that's also why they focused on getting that model right at the onset so that when they brought in customers, those customers wouldn't turn. The customers wouldn't leave. Actually, I wanted to walk through the exact, because I was when I was doing research for this video, I actually found the exact tech stack that snowflake used. So this tech stack was put together shout out to Douglas Carr from martec martec.zone. So Douglas was at some sort of, it was some sort of event. And he was listening to a director from snowflake breakdown their tech stack. So the tech stack, this is the sales tech stack, by the way, the the account base marketing and sales tech stack. So they broke their ABM process into four pieces. They broke it into target, reach, engage, and measure. So for the target stage, they used Everstring in Bambora. They basically were discovering businesses that match their best clients that have displayed an intent to purchase a product. Number two, for reach, they were utilizing Terminus, Sixter, and LinkedIn. Snowflake was assembling personalized content experiences that touch prospective buyers before they may even be aware of their solution. The keynote was stating that one customer had seen snowflake software 450 times across social or on web before they had submitted a request for a demo. The third step is engaged. They utilized Uber Flip. So snowflake has content experiences that are owned by the sales account manager, but produced by the ABM team to provide highly targeted content to drive the buyer into the customer journey. So again, in layman's terms, basically the content is is being signed off on by the sales team, but is being actioned by the marketing team. So the sales team is saying, this is the content that I need to sell. The marketing team is actioning it. And the two are communicating back and forth so that there's there's congruence across these two departments. Then lastly, the last step is measure utilizing Engageo, Tableau, and Looker. Snowflake developed a proprietary means of scoring the leads, providing sales intelligence needed the sales account manager to assist them in closing the deals. And then again, once that deal is closed, they're bringing that into their initial ideal customer profile model. What were the results? Well, besides a $70 billion IPO, click through rates increased $149 on ABM ads. And half of all the content that snowflake produces was seen by customers, by customers, and ABM targeted organizations. That's an insane metric that that ratio is incredibly is incredibly good. So half of the content they ever put out is being seen by exactly who they want. They want that person to do the content. So basically, the story of Snowflake is they focused on alignment across marketing and sales. They threw out any preconceived notions and used and trusted data to provide that model. And then they just they adopted traditional outbound to allow their sales team to scale, but they made sure when they're doing that outbound, they're still communicating with their marketing team. Anyways, this obviously is all the right pieces of what a modern day sales and marketing process should look like executed properly. You'll hear a lot of people speak about different components that I mentioned today, but a lot of people do not execute it religiously, properly, strictly. So you have to trust the process. You have to trust the data. And that's exactly what snowflake did. And that's why they were so successful. Anyways, if you like this case study and this rundown of snowflakes process, hit that like button, hit subscribe and leave some comments below. Let me know who else you want me to analyze and break down their sales and marketing process. Have a great day.