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

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Growth Story is a weekly podcast that breaks down the strategy and tactics utilized by high growth companies, in a short case study format hosted by Scott D. Clary (@scottdclary).

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Welcome to these success story PODCAST, the most useful podcast 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 seventy billion dollar 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 like putting together a case in marketing studies from a 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. And there's a there is some information out there, but I want to I want to disseminate it to you and walk you through why it was so effective, why their strategy of 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 Silica 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 Berkeshire hathaway. So they have not invested in an IPO and fifty year that 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 Snow Flake. What do they do? So it's Snowflake is a data a cloud data warehouse provider. So they provide server services to companies. So companies, big companies, any 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, IBM's in this space like there are big companies in this space. So snowflake their proprietary IP, their 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 request, that a retrieval request, 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 Snow Flake trolls. So when a customer, when a 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 request simultaneously. So sometimes if you go with a smaller provider, your request may be throttled or if you're too big, a company just won't work for you. So that's that's sort of the the differentiator for snowflake. 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 in 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 be to be 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. You have two employers, I'm going to sell you two licenses or seats, whatever you want to call them. But snowflake did a little bit different. What's 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 quote. It's not. It's not what a lot of companies do. So if I'm using SNOWFLA like, 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's 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 seed basis. So snowflake did utilization cost structure, which, of course, was very favorable for customers. And then, lastly, they did do some strategic management changes free IPO. So they got rid of a well respected CEO that had done very well with the company and they brought in Frank Sluteman, who has a record of IPOs under his belt. He is known as he is known as a CEO WHO's only brought into IPO at high evaluations. He has an incredible track record. So that was also something it 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, Oracle and 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 snow flake. Also, the util is a 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 a software company and you do have a pricing structure, 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 its product, because that is super disruptive and it's probably not going to drive too well. But if you have, for example, an innovative sales or marketing strategy that I'm going to walk through. That's something you can implement tomorrow. And then, lastly,...

...while I'm not talking about frank, well, you, for probably don't know Frank's Loutman. You probably can't afford them. 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, though, was so innovative? Well, nothing, it was innovative, and what they did actually what they focused on with 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 push 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 though, what they're putting on the website. So when the sales wrap goes and call somebody, emails somebody. They have no idea what they're marketing teams actually focused on. To the conversation the sales team member, the salesperson, is having with the customer is completely different for what the marketing side of the business is focusing on. This is 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 I'm learning about their product, I jump on the phone with the sales rep and they're pitching me something completely different than what I was reading about online. A different feature, a different product at 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 lefthand doesn't know what the right hands 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? Will they focused on ABM or account based marketing? What does account based marketing? Well, count based marketing. Again, at its core is focused on sales and marketing alignment, but also it goes a step further, so count based marketing. What it means is you are understanding which account do 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, we'll listen, let's take this example. To say, IM 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 I be am is selling a similar products. I'm going to say, well, why don't we just go after the same customers that I be am an oracle are going after? kind of makes sense right, but pause for a second. What if there's a chance that I be am an oracle. Have not perfected their customer profile? What if it's not absolutely perfect? Well, that's basically what's snowflake said. Not so many words, but they said we don't want to just go with the the ideal customer profile of the category. We want to create our own and we want to back it up with data. We want to know with a hundred percent 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 a BM having a customer profile. How did they build out their customer profile? Their ideal customer profile there was specific to their product and their customers. They took their fifty biggest deals and they took the fifty deals a close the fastest and they put that into a tool. They actually used a tool called ever string, which is a business analytics and information tool, and that used machine learning to generate the perfect customer profile based on those inm so how how which customers close the fastest? Which customers are the biggest deals? That's we want to target and that's whatever string 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 a step further and they didn't just let this customer profile be static. They can instantly tested this model. So when they closed fifty new customers based on that customer profile, they brought them into this tool. They modeled out a new ideal customer profile. So they kept getting more granular, they kept getting more specific and 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 they're working off the same customer profile and they're communicating and it's 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 too many sales outreach strategy. What is this mean? Okay, so when when snowflake was first starting out, they had roughly thirty sales rep they assigned one hundred customers, and these are enterprise customers to 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 too many. The one too many is automated, so they took nine of the hundred customers and they were sending automated outreach to employees within these ninety customers or companies they were targeting. Then the one to few. The one to few was personalized outreach to the top ten customers that they wanted to personalized outreach to every IMP employee of every company that they were reaching out to. So, because these are enterprise companies, they were probably reaching out to ten to twenty to thirty different employees within each one of those hundred 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 ten 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. Topic 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 too few where they're doing personalized that reach the ten customers and one too 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 know, rinse in her pretty, rinse and repeats, use me, so on and so forth. And this was the core of their product, this was a 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 the customers that you're bringing in our 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 text at that snowflake use. So this text act was put together. Shout out to Douglas Car from MARTEC, MARTECH DOT zone. So Douglass was at some sort of it was some sort of event and he was listening to director from snowflake breakdown their techtact. So the text act, this is the sales text act by the way, or the the account based marketing and sales text that. 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 ever string and Bombora. They basically were discovering businesses that match their best clients that are displayed and intent to purchase a product. Number two, for reach, they were utilizing terminus sister and Linkedin s no flake was assembling personalized content experiences that touch perspective buyers before they may even be aware of their solution. The keynote was stating that one customer had been had seen snowflake...

...software four hundred and fifty times across social or on Web before they had submitted a request for a demo. The third stay, a 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 congruents across these two department then, lastly, the last step is measure. Utilizing Engageo, tableau and looker, snowflake developed a proprietary means of scoring the leads, providing sales intelligence needs. The sales account managers to assist them in closing the deals and then again, once that deal was closed, their bringing that into their initial ideal customer profile model. What were the results? Well, this besides of seventy billion dollar IPO click through rates increase a hundred forty nine act on ABM ads and half of all the content that snowflake produces was seen by cust stomers, 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 see 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 adopt the traditional outbound to allow their sales seem 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 mention 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, studying this rundown of snow flakes processed, 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.

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