REPORT

The Modern Marketing Data Stack 2026

How marketers become agents of change in an AI-driven world

A new report follows the evolution of the martech ecosystem:

AI is in everything and agentic AI promises to transform workflows even further.
The balance of marketing data privacy is shifting (again).
Data gravity continues to exert its pull, transforming martech.

The Beginning of End-to-End AI

As AI fully infuses the martech stack, the next step will be to connect individual processes to empower automated agents to take action. Organizations are getting their data and first-generation AI tools in order, which drives them to their agentic future:

Improved AI creative capabilities will demand the refining power of performance data.
Multimodal AI models will use text, image, video, voice, even gameplay to unify messages across channels and formats.
Measurement in the AI age requires multiple models to avoid new data silos and vendor lock-in.

AI agents are on the horizon, and both the tech itself and marketers will advance a step at a time.

New Perspective, New Stack

Typically, the modern marketing data stack is centered on vendors and how solution providers frame their value. This year, the modern stack continues to shift focus toward the goals of enterprise marketers and the actual work they’re doing.

From the marketer’s perspective, a new tech ecosystem emerges:

The build vs. buy dilemma is dead. Marketers are approaching data, AI and architecture on their own terms, combining tools they build with tools they buy.
A new category — data collaboration — reflects marketers’ increasing interest in better monetizing their data while retaining control of it.
LLMs now command a place in the stack as tools for powerful and unique use cases.
Underlying it all, a unified, secure AI and data foundation provides crucial insights and the ability to collaborate across the entire marketing ecosystem.

Understand the evolved martech stack, and the vendors pioneering the way, in the new report.

Data Gravity Grounds the Modern Stack

“Data gravity,” the increasing preference to manage enterprise data in a unified platform rather than in a cascade of tooling silos, is how marketers drive better campaigns. The result is new opportunities and greater agility:

The embrace of composable stacks gives marketers agility and control without vendor lock-in.
Especially in the fast-moving AI era, marketers need to be able to swap in specific solutions as needs and opportunities evolve.
With data centralized within the enterprise, CDPs are evolving into orchestration layers tied more tightly to engagement platforms.

A centralized data foundation empowers marketers to build a better view of each customer, leading to greater personalization and smarter, faster decision-making.

Privacy: Be Good to Your Audience

Another driving factor: Consumer concerns about privacy and how their personal data is used are not going away, even as data-hungry technologies are continually created and refined. Marketers are sorting through mixed signals:

Third-party cookies haven’t gone anywhere, and digital fingerprinting is poised for a comeback.
The regulatory landscape is chaotic, as regions, nations and states chart different approaches to personal data.
First-party data remains hot — particularly the unstructured kind.

Using powerful technology to build strong relationships and consumer trust will require personalization, innovation and sometimes restraint.

Download the Report

Methodology

The goal of this research was to pinpoint the technologies that have garnered a substantial and active customer base within Snowflake. The study spanned a 12-month period, aligned with the Snowflake fiscal year 2025 (Feb. 1, 2024 to Jan. 31, 2025), evaluating usage data and related trends from over 11,100 Snowflake customers. The process was as follows:

Identifying technologies in the marketing data stack

We assessed the use of marketing technologies by Snowflake’s active customers during the analysis period.

Active customers were defined as those who:
- Held either a capacity or an on-demand/self-service contract with a valid end date, and
- Generated revenue for Snowflake within the past year
The technologies considered for the analysis were required to meet the following criteria:
- The technologies considered for each evaluated category had to be active members of the Snowflake Partner Network (SPN), have a comparable agreement in place with Snowflake, or be Snowflake Marketplace providers that have agreed to the relevant Marketplace terms and conditions.
Companies mentioned in the large language models (LLM) category represent providers with LLMs available in Snowflake AI Data Cloud via Snowflake Cortex AI and were not evaluated by Snowflake for the modern marketing data stack.
Vendors in the marketing cloud category have been evaluated based on a variety of factors, including Snowflake consumption and their presence in the industry and customer marketing data stacks.

Categorizing technologies based on their type of Snowflake consumption

As Snowflake continues to enhance its platform capabilities and offer various application deployment models, vendors integrate with the AI Data Cloud in diverse ways to serve different purposes. To accurately assess market leadership and adoption levels from the lens of our customer base, specific metrics were applied based on the type of Snowflake consumption. The analysis accounted for:

Technologies using Snowflake for data integration, transformation and analysis workloads
Technologies utilizing Snowflake’s collaboration workloads to integrate their product offerings other than data collaboration solutions
Technologies utilizing Snowflake’s collaboration workloads to provide a data collaboration offering, associated with the “collaboration” category of this report

Identifying key metrics for measuring success of marketing tools

To accurately measure the adoption success of marketing tools within each category in the stack, specific metrics were analyzed based on how the partner technologies leveraged Snowflake’s capabilities.

Metrics for technologies using Snowflake for data integration, transformation and analysis workloads were:
- Total number of active customers using the technology, and
- Total credit consumption by the technology on Snowflake, and
- The percentage growth of both categories for the 12-month trailing period, in comparison to the prior 12-month trailing period
Metrics for technologies leveraging Snowflake’s collaboration capabilities to integrate their product offerings other than data collaboration solutions:
- Total number of stable edges that include the technology. Stable edges are the ongoing relationships between data providers and consumers of data. A stable edge is defined as a data share that has produced at least 20 transactions in which compute resources are consumed and such consumption results in recognized product revenue over two successive three-week periods (with at least 20 transactions in each period).
- Total credit consumption is driven by data shares that the technology uses on Snowflake
- The growth of both of these for the 12-month trailing period, in comparison to the prior 12-month trailing period
Metrics for technologies leveraging Snowflake’s collaboration workloads to provide a data collaboration offering, associated with the “collaboration” category of this report:
- Total number of stable edges that include the technology
- Total credit consumption is driven by data shares that the technology uses on Snowflake
- Total number of unique consumers of the data collaboration technology defined as at least one stable edge established between a provider and a consumer

Analyzing growth figures

We included all active capacity and self-service customers as of Feb. 1, 2024, who generated positive revenue for Snowflake over the subsequent year. Growth percentages reflect the increased usage of each category’s tools over the immediate 12-month trailing period between Feb. 1, 2024, and Jan. 31, 2025, compared to the previous 12-month period. By following this methodology, we aimed to provide a clear picture of the technologies gaining traction among Snowflake’s customer base.

Creating a penetration index for Snowflake technologies

We developed an index to illustrate the market penetration and usage depth of technologies based on their interaction with Snowflake. The calculation uses weighted criteria tailored to different types of Snowflake usage:

Technologies using Snowflake for data integration, transformation and analysis capabilities:
- Breadth (40%): Number of active customers using the technology on Snowflake over the 12-month period of analysis
- Depth (40%): Total credit consumption by the technology on Snowflake over the 12-month period of analysis
- Growth of breadth and depth:
  - (10%) Percentage growth of the total number of active customers using the technology for the 12-month trailing period, in comparison to the prior 12-month trailing period
  - (10%) Percentage growth of the credit consumption by the technology for the 12-month trailing period, in comparison to the prior 12-month trailing period
Technologies utilizing Snowflake’s collaboration workloads to integrate their product offerings other than data collaboration solutions:
- Breadth (40%): Number of stable edges of the technology on Snowflake over the 12-month period of analysis
- Depth (40%): Total credit consumption by the technology on Snowflake over the 12-month period of analysis
- Growth of breadth and depth:
  - (10%) Percentage growth of the total number of stable edges of the technology on Snowflake over the 12-month trailing period of analysis, in comparison to the prior 12-month trailing period
  - (10%) Percentage growth of the consumption by the technology for the 12-month trailing period, in comparison to the prior 12-month trailing period
Technologies utilizing Snowflake’s collaboration workloads to provide a data collaboration offering, associated with the “collaboration” category of this report:
- Breadth (70%):
  - (40%): Number of stable edges of the technology on Snowflake over the 12-month period of analysis
  - (30%): Number of consumers integrated through the technology offered by the vendor
- Depth (30%): Total credit consumption by the technology on Snowflake over the 12-month period of analysis
This index provides a comprehensive view of both the market reach and the intensity of technology usage within Snowflake’s ecosystem.

Rank/select the marketing technologies from 1 to N, where the lower number (ranking) is more favorable. Combine the full list of technologies across both groups and normalize this ranking between 0-100. (A score of 100 would be the technology ranked first across every metric.)

Leaders represent the top technologies with the highest index in each category. We are identifying vendors as leaders if they meet the following criteria:
- All but collaboration categories:
  - Ranked in the top three in their category
  - Or technology index is within 87% of the average index from the top three vendors in their category
- Collaboration category:
  - Ranked in the top three in their category
  - Or technology index is within 94% of the average index from the top three vendors in their category
Ones to Watch were selected based on their strong standing, and additional factors such as strong recent momentum in the market, innovative technology or approach with Snowflake, or have recently demonstrated strong customer capabilities.