The Modern Marketing Data Stack Report

Modern Marketing Data Stack

As marketers adapt to profound trends—the arrival of generative AI and large language models (LLMs), the convergence of adtech and martech, and greater attention to privacy issues—the right technology stack is essential to great marketing.

Snowflake analyzed what its customers use most often to enhance marketing data analytics and more accurately measure performance and ROI.

The second edition of our report, The Modern Marketing Data Stack, identifies leaders and “ones to watch” across the 10 capabilities that compose today’s marketing data stack, and addresses the strategic imperatives that affect how they unify, analyze, and activate data to help boost revenue.

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THE FORCES SHAPING MARKETING STRATEGY
AND TECH INVESTMENT

One year after we launched the first report, the Modern Marketing Data Stack has evolved, reflecting the relentless pace of change.

The report looks at the leading technologies used by 8,100+ customers in the Snowflake Data Cloud to power their marketing stack. For this year’s report, we break out foundational data technologies, including AI, from the marketing-specific tools. And our findings reflect trends such as the rapid convergence of adtech and martech (see below), the heightened importance of data measurement (and activation), privacy challenges, and more.

Artificial Intelligence and Machine Learning:
The Emergence of LLMs

The impact of LLMs will be pervasive, to say the least, and the most obvious effect on marketing will be productivity. According to this year’s report, adoption of AI and ML tools by Snowflake customers is up 15.5%, but that’s only the beginning.

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Adtech and Martech Convergence:
Four Forcing Factors

The technologies supporting advertising and marketing were established independently, but as data silos fall, those adtech and martech tools have started to come together. Overall, the convergence represents the move toward a more integrated and data-driven approach to marketing and advertising. Four realities largely drive this shift:

1. The media landscape is frenetic and fragmented.

2. So are the tech solutions meant to help marketers navigate that landscape.

3. Inefficiency costs money.

4. Business leaders are eager to cut expenses.

Data Privacy:
Navigating the Challenges

Marketers want to unify data from multiple sources to have a complete view of their customers, and to effectively market to them across the entire customer journey. But rising consumer concerns and government rules and regulations around privacy demand a responsible approach.

New techniques and technologies are emerging, particularly the use of data clean rooms that allow data to be shared in a secure, privacy-preserving way, while applying governance policies that take consent and access permissions into account.

Methodology
The goal of this research was to identify the technologies that have developed a significant, active customer base within Snowflake. The analysis was conducted over a 12-month period, from April 4, 2022, to April 3, 2023, looking at more than 8,100 Snowflake customers. The process was as follows:

Identify the full list of technologies for marketing data stack:
- We looked at Snowflake’s active customers’ use of marketing technologies during the analysis period. Active customers are defined as:
  - A customer with either a capacity or an on-demand/self-service contract, with a contract end date that has not passed.
  - A customer that has generated revenue for Snowflake in the last year.
- The technologies considered as part of the four categories of Data Stack Foundational Tools must be active members of the Snowflake Partner Network (SPN), or have a comparable agreement in place with Snowflake. The technologies for the 10 categories of the Marketing and Advertising Domain Specific Tools and Platforms must either be active members of SPN, or be Snowflake Marketplace Partners that have agreed to the Marketplace Terms and Conditions.
- Growth figures included all active Capacity and Self Service customers as of April 4, 2022, with positive Snowflake revenue during the year ending April 3, 2023. Percentages reflect increased customer consumption of the respective tools within each category in April 2023, as compared to the consumption of those same tools in April 2022.
Split the technologies based on their type of Snowflake usage: The multiple workloads that exist in Snowflake, combined with the optionality of different application deployment models available in Snowflake, means that vendors integrate with the Data Cloud in different ways and for different purposes. To accurately evaluate market leadership and adoption levels, particular metrics were applied to providers based on the type of Snowflake consumption. Specifically, the analysis consisted of splitting the technology providers into two separate categories: Technologies that use Snowflake’s workloads for data integration, transformation, and analysis; and technologies using Snowflake’s collaboration workload. The overlap for tools operating on both sides was less than 0.5%.

Identify key metrics needed to measure success of different marketing tools for each category.
- The metrics for technologies using Snowflake’s core workloads for data integration, analysis, and transformation were:
  - Total number of active customers using the technology on Snowflake
  - Total credit consumption the technology uses on Snowflake
- For technologies using Snowflake’s collaboration capabilities:
  - Total number of stable edges that include the technology. Stable edges are the ongoing relationships between 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 driven by data shares that the technology is using on Snowflake.
  - Total spend on Snowflake, as consumption dollars, as a way to credit managed applications and tools that are delivering to customers, albeit without data sharing.
Generate a ranking based on the type of Snowflake usage that illustrates the level of market penetration achieved by the technology, and complement it with how deep that usage is. The calculation is based on the following weighted criteria:
- Technologies using Snowflake’s core workloads for data integration, analysis, transformation:
  - Breadth (50%): number of active customers
  - Depth (50%): total credit consumption
- Technologies using Snowflake’s collaboration capabilities:
  - Breadth (40%): number of stable edges
  - Depth (40%): total credit consumption from shares
  - Spend (20%): consumption dollars, as a pointer for breadth of adoption of managed applications besides the data sharing usage
- Data enrichment category:
  - Breadth (100%): Number of stable edges, to prioritize measuring collaboration for enrichment purposes rather than size of different organizations’ data sets.
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.
- Ones to Watch did not necessarily follow the leaders in their standing, but were selected based on multiple factors such as strong recent momentum in the market, innovative technology or approach with Snowflake, or have recently demonstrated strong customer capabilities.