The key trends from Snowflake Summit 2024
Every year, Simon Data attends Snowflake Summit to meet with industry leaders, companies, and customers to discuss the latest advancements and trends in MarTech.
Summit always treats us to hundreds of hands-on sessions (this year, I was honored to host two of them — one with Zillow and another on AI in MarTech), insightful keynotes from experts, dinner events, vendors, and training and certification opportunities.
This year was no different — except for the fact that there was far more buzz around the desire for enterprise marketers to better use and activate customer data than ever before. With Snowflake’s recent launch of the Marketing Data Cloud (and, more specifically, Snowflake’s recently announced LLM, Arctic), this isn’t surprising.
At Summit, I noticed three particular trends emerge:
- An increasing awareness around the need to access and activate first-party customer data for the personalized marketing customers now demand.
- AdTech & MarTech are two separate worlds - and Snowflake is joining them together…albeit still somewhat slowly.
- The hype around genAI is real, but we need to be strategic in how, where, and when we use it.
Trend 1: An increased awareness of marketing and activation
I had the pleasure of presenting with Ravi Kandikonda, SVP of Marketing at Zillow, on how our CDP helps Zillow drive marketing personalization. The event was well attended, and we were flooded with specific questions about how our platform works and how Zillow uses both Simon and Snowflake to support its marketing campaign strategies.
I won’t bore you with all the details of how Zillow accomplishes this (we’ll have the full story on our site soon), but in short, Zillow implemented the Simon CDP to support its top marketing opportunities: omnichannel personalization across the entire customer lifecycle — all at Zillow scale.
After our event, Ravi and I spoke with attendees about details of how this all actually works, and we had great questions ranging from how AI is integrated into our system to what types of first- and third-party data we support to questions around marketing workflows and optimization.
The biggest change from last year’s Snowflake Summit? For one, there were more marketers in attendance — I asked for a show of hands to see who was in marketing, and about a third of the audience responded positively.
The conversations I had with folks reflect this. Chatter has shifted from, “I didn’t know you could plug Snowflake into Salesforce” to, “How can I leverage Snowflake to drive effective 1:1 personalized and omnichannel messaging?”
I’ve also seen this reflected in my conversations with industry experts and our customers over the past few years. Despite hot topics like genAI and composability within the CDP space being top-of-mind, the CDP Institute reports that “there has also been a steady growth in CDP capabilities among vendors whose primary focus is marketing and operational systems” in 2024.
Trend 2: AdTech vs. MarTech are further apart than we thought
AdTech and MarTech have historically existed in different worlds — generally segmented across use cases focused on acquisition and use cases focused on retention and customer engagement.
The data behind these are significantly different:
The beauty of Snowflake and cloud data advancements is that we now have a single place to leverage a single database to house both of these disparate types of data. Specialized DMPs or backend systems that optimize for “column 1” vs “column 2” are no longer needed.
Couple this with the vision of creating a singular customer experience driven by a singular customer 360, and the vision behind the convergence of these two categories becomes quite obvious.
At Simon, while our roots are historically MarTech-focused, we’ve made significant AdTech investments and support for acquisition use cases. Our recently launched integration with The Trade Desk, for example, enables Simon customers to create and activate segments using their customer data from Snowflake and integration with The Trade Desk. The results? Increased acquisition rates, better spend efficiency, and improved outcomes of segmented campaigns.
This being said, the actual convergence between these two categories is slower than I would have expected, with some of the core reasons below:
1. The data that powers MarTech and AdTech are at very different points of maturity. Most customers still have most of their AdTech data siloed in a DMP or legacy system and not yet in Snowflake.
MarTech data on the other hand is on the other end of the spectrum — customers have tons of enterprise data in Snowflake but they’re data starved (or lack operability) in their MarTech stack. The problem here is about unlocking what’s there as opposed to create net-new data investments.
2. AdTech is still way too complicated. A few independent non-walled garden players have broken out, such as The Trade Desk, but most of the category is incredibly entangled. The web between DSPs, SSPs, DMPs, inventory planning tools, and ad servers is hard to untangle.
While net new use cases such as data cleanrooms have become popular on Snowflake, moving over to other workloads has been difficult. MarTech’s SaaS model on the other hand makes this transition much more available (at least, for vendors who want to build on Snowflake or cloud data platforms).
3. Most publishers are still in the poorhouse. The promise of Snowflake-enabling media optimization requires making investments that much of the supply side just isn’t able to make. So while some like Netflix innovate, others are stalled and progress is much slower.
At Summit last week, I went to some events that were AdTech focused and others that were MarTech focused. When I switched between the two, I felt like I was crossing between foreign countries speaking different languages — but on the same land mass.
Trend 3: There’s more hype than ever around marketing AI
GenAI and machine learning (ML) are still all the rage. My presentation on using AI and ML for things like personalization, streamlined workflows, and predictive analytics in marketing was jam-packed, despite being an end-of-day slot on Wednesday.
Today, nearly every SaaS product includes (or is building) AI and ML tools in their product. What does this mean for Simon? This technology isn’t new to us or our product.
My experience is that any new tech, especially AI and ML, must first be created to solve business problems and be tightly coupled with applications to be effective. In the CDP space, customer data needs to be complete, accurate, and secure, and applications must provide fast value that solves business problems. AI, through its secure and optimized logos, becomes the key that unlocks a streamlined marketing workflow and use cases between the data environment and the application.
Identity modeling, for example, encompasses AI’s 3P identity data sets and AI-powered addresses and entity resolution, while the benefits of no-code automation within a CDP mean that the platform requires integrated LLMs with data and integrated test loops.
So, what does this mean for Simon? We’re aggressively building and incorporating more advanced AI and ML into our product, but what’s more important is that we’re working closely with our customers to learn exactly how and when these technologies can help them streamline workflows, build smarter, more personalized marketing campaigns, and encourage marketing experimentation.
Our product roadmap isn’t just focused on building AI that’s packaged into our product. It’s about finding the right set of problems that we as a CDP own—- and then the right support capabilities to enable our customers and AI partners to plug into our platform across segmentation, personalization, channel optimization, experimentation, and beyond.
The future of MarTech is here — sort of
Snowflake Summit 2024 was another whirlwind of innovation and inspiration. It’s been valuable to connect with industry leaders and customers to hear first-hand about the challenges and opportunities shaping the MarTech landscape.
Needless to say, 2024 hasn’t been a dull year. From the raging debates around the true definition of “composability,” the demise of third-party cookies, Snowflake’s recent marketing cloud launch, and the continuous development of AI in applications, our space continues to shift — and ever more so toward the goal of being able to gather, access, and activate quality customer data to deliver the ultimate personalized marketing experience.
