Right now is one of the hardest times of the year for marketers. Most CMOs will be heads down wrapping up a year-end assessment and figuring out what to pitch for next year’s budgetary spend to drive revenue, all while navigating an ever-changing environment of inconsistent metrics, lower conversion rates, and a rapid rate of change with the adoption of AI in SaaS.
A CMO panel consisting of the CMO of Snowflake, Denise Persson, CMO of Carta Nicole Baer, and the VP of Marketing at LinkedIn for Sales, Gail Moody-Byrd all answer Carilu Dietrick’s questions, CMO and advisor formerly at Atlassian, about all things growth for 2025.
Growth Levers at Snowflake
How are these companies thinking about growth levers for their business? At Snowflake, they’ve been through everything: breaking into industries, verticalizing the sales and marketing organizations, and expanding into 40 countries in the last eight years. Now, the next phase of growth is coming from multiproduct adoption.
AI is a big part of that. The past years were so focused on new business, and they’ll still do that, but now it’s about breaking into customer organizations and going wider and deeper with new products.
Denise Persson, CMO at Snowflake explained: “Our AI offering is of course a growth opportunity for us. Also, we’re really very focused on the machine learning space. We’ve really been so focused on new business over the years, and we still of course are, we’re not slowing down there but we’re at the point where we need to break into our customer organizations, wider, deeper with our new products.
We’ve invented so many new products so at the moment we, just can’t invent more. It’s a focus on which are the programs that we can scale even further. What are the programs that we can stick to scale with our partners? It’s all about scaling what we have. Breaking into our accounts at a wider and deeper level. That’s really where our growth is going to come from next.”
Central vs. Decentralized Workforce at Snowflake
Snowflake has a hybrid work model. They are headquartered in San Mateo, and for that non-quota-carrying “centralized” local team as they call it, they come into the office three times a week. Snowflake’s working model is that the role of the central team is only to focus on building scalable, repeatable programs to push out to each of their regional teams.
Everything from positioning to messaging, to brand and sales enablement, all comes from the central HQ team. But for everything else, they let the regions decide how to best implement it.
“The regions cannot just rely on us here in San Mateo, right?” Denise explained. “That would be a massive bottleneck. So now it’s more about more power to the regions. Let them move faster. It’s all about DORA: do it once and repurpose it anywhere.”
Carta’s Growth Levers for 2025
Carta is in a different place than Snowflake. They have traditionally focused on its cap table business but are now expanding into new products and audiences. So what are their growth levers for next year?
Carta is making it their strategic mission to transition to create software for fund CFOs with venture capital and private equity firms. This underserved community still uses Excel and single points of failure with accountants. Carta is giving fund CFOs a true ERP system.
Nicole Baer, CMO at Carta explains: “I can say as a CMO, it feels so great to have a singular focus. It really does. We’re laddering focusing everything we’re doing in marketing and product and sales into the singular vision around how we’re going to fall in love with the fund CFO.”
That’s their focus next year. As a CMO, having a singular focus is great. New campaigns, new categories, and new audiences will all fall under this singular focus on delivering value to the CFOs.
LinkedIn Accelerates Growth with New Levers
VP of Marketing at LinkedIn for Sales, Gail Moody-Byrd sits at an interesting place. While LinkedIn is a talent solutions business, her role is in the sales solution business, so they’re operating like a startup within LinkedIn. The question is, how do you grow and continue to accelerate? At LinkedIn, they think the answer is mining the customer experience.
90% of their revenue plan is working with existing customers and going deeper.
Growth levers include deeply understanding the value that CS, sales, lifecycle marketing, and product marketing bring to customers, as well as what levers to pull to get greater utilization of the people who already have their products.
Gail Moody-Byrd explains: “So we’ve firmed up a priority within our organization to get greater utilization of the people who already have our products. Making sure that they understand the values. So (we spent) a lot of time spent on strategic value reviews. Making sure that the onboarding process is clear. LinkedIn has 15 customer experience maps, so everyone has their own view of (it). The goal is to unify those maps to create a seamless customer experience focused on value. So, when it’s time for renewal or a growth conversation, it’s clear that value has been delivered, and people are using it within their organization.”
Category Creation: To Do or Not To Do
In CMO land, category creation is a big question. For early-stage companies trying to talk about their business, it’s important to clearly communicate what you offer to customers in a way they can understand. Let’s look at how Snowflake approaches this idea in the context of data warehouses.
In the early days of Snowflake, they were so much more than a traditional data warehouse but no one knew them yet. You can read more about Denise’s approach to marketing from a couple of years ago on their path to $100M.
“In the early days, Snowflake was so much more than a traditional data warehouse,” Denise explains. “But when you’re starting out and your name is Snowflake, nobody’s ever heard who you are. You have absolutely no credibility to try to go out to say, ‘Oh, we’re this enterprise data platform.’
No one would even believe us.
And it would take too long to explain what we really do so it was better for us to break into a category that already existed, a category that people understood and that there were budgets for. I think it’s much better to break into an already existing category with something significantly better than in the early days, try to do something bigger.”
Once they adopted this mindset, prospectus understood more quickly how Snowflake was a data warehouse built for the Cloud. Building out in an existing market where budgets were already being allocated made a world of difference for them.
Of course, Snowflake grew a lot, and quickly and customers pulled them into the “We need a data Cloud and platform that sits across the Cloud.” And that’s how they’ve evolved into the data Cloud positioning they have today.
The most important thing Snowflake did well was to be extremely consistent in its messaging. It was always “The data warehouse built for the Cloud.” They hammered that, home and it worked.
“It’s almost more important to be consistent than being a hundred percent right,” Denise said.
An Established Company Can Create a New Category Much Easier
LinkedIn created a category they called ‘Deep Sales.’ It became transformational for the business, resonated with the market, and got the sales team excited to have a North Star to talk about. But as Gail Moody-Byrd explained, it only worked because LinkedIn is well .. LinkedIn. When they set out to do this they already had a large enough platform and presence to speak to this on a daily basis. They had the social leverage to make Deep Sales a thing that mattered. Gail rolled it out to a sales team of 2,000 people and flooded the LinkedIn feed with it—share of voice matters.
Conversely, before LinkedIn Gail was CMO at a series B AI startup where they didn’t have the leverage to start a new category. They tried. But without the budget, the platform, or the sales team to spread the word of mouth, it ultimately failed.
“It’s very hard to strike in the market when no one knows who you are,” Gail explained. “You don’t have strong representation to create something new. So although we really believed in the positioning, we just didn’t have the resources to make it stick. So I think you have to know the sort of ‘boundary conditions’ of when it (could) work and when it doesn’t.”
How AI Affects 2025 Marketing Strategies
Generative has had a big impact on the productivity of Snowflake’s sales team – specifically their outbound SDRS. Snowflake has about 300 SDRs in seat, each with an average tenure of ~15 months (before moving up or to inside sales or other departments etc.) Which means Snowflake has to effectively hire about 200 new SDRs every year.
Across 10 different cohorts in their sales development academy, new hires join Snowflake as an SDR every month, so for them, it’s hard to write the right emails and get the right content. So that’s AI is having the most impact at Snowflake. They’re seeing more than double the meeting rates for its teams who use generative AI for their messages and outbound.
More and More and More With Less
The biggest problem about being a marketer is having to do more and more and more with less. Let’s see what each of these companies plans to dial back on in 2025.
LinkedIn will be doing less with web optimization. The idea that someone sees content, fills out a form, goes to a website, and that information gets fed to an SDR for outreach hasn’t been effective. You could spend hundreds of thousands of dollars optimizing web, but instead, Gail is focused on building community and doing a lot more with influencer marketing.
Carta is dialing back on undifferentiated online events that use too many resources. They’ll also be turning up on the community building and tailoring events to their specific needs.
Snowflake will continue to focus on eliminating the things they can’t scale or repeat and dialing up the things they can. Plus, they’ll be investing a lot into the learning and development of their people. You need to take your entire workforce into the new with these technologies.
It’s never been a more exciting time to be in tech and marketing. Everyone needs to focus on brand-new paradigms rather than trying to adapt AI to existing ones.
