Five Data-Driven Marketing Trends to Watch in 2025

This is our third annual Data-Driven Marketing Trends to Watch (see 2024 and 2023) piece, and it feels like the changes we can expect in the coming year will be the most disruptive so far.  The major themes of the trends for marketers in 2025 haven’t changed from previous years. These are roughly:  AI, Blockchain/Web3, Data Cloud, and Measurement. What’s different today is the accelerating pace of development and consumer adoption of Generative AI (GenAI). Let’s unpack these Five Trends to know about in 2025 and how to best handle as a data-driven marketer.

1) AI Has Entered the Consumer Journey

Usage of GenAI platforms like ChatGPT, Claude, Perplexity, and Grok has become mainstream with people using it for a variety of reasons from summarizing content to directly answering specific questions to writing code to generating images and videos.  

As marketers, we are particularly interested in how GenAI is impacting the consumer journey, since consumers and their journey are central to our marketing strategies. We know that today, nearly half of GenAI users have made purchases based on AI-driven recommendations. Some GenAI engines have recently enabled the ability for consumers to place orders via the GenAI engine interface, without going to the retailer’s website.  The next logical step will be to empower GenAI (likely in the form of agents) to make purchases on behalf of consumers based on their prompts. 

What To Do About It:

• The implication is that every brand needs to understand and influence what the major GenAI engines are perceiving about their brand and products. Tools and resources are being built today to provide this information.  Most notably, check out BrandRank.AI
• These new tools should be piloted by brands to augment three legacy use cases: 1) Search Engine Optimization => GenAI Engine Optimization 2) Brand Health Tracking => GenAI Brand Sentiment Tracking and 3) Voice of Customer Analysis => GenAI-as-a-Customer Analysis to influence product development and consumer experience designs

2) AI + Web3 Enables New Consumer Networks and Experiences

The concept of Web3 has been a loose idea of the next iteration of the internet characterized by concepts & technologies like: decentralization, user empowerment & ownership, public blockchains, cryptocurrencies, NFTs, gaming, virtual reality, and metaverse experiences. Some of these things have grown tremendously (e.g. Bitcoin, stablecoins) while others experienced muted interest and investment in 2024 (e.g. NFTs and metaverse).

AI has inserted itself deeply into this Web3 realm and a whole set of new things are beginning to emerge. Below are several examples and developments that demonstrate consumer interests and some focal points in this space:

• Character.ai: AI powered chatbot service where users create characters and engage in human-like text conversations. This platform has grown to 28 Million Monthly Active Users with 18 Million unique chatbots created and the company is worth an estimated $2.5BN. Note: Real risks exist as these new platforms develop as evidenced by this tragedy which demonstrates the need to monitor and control AI for safety.
• Zerebro: An AI Agent that autonomously creates content, distributes it across both social platforms and blockchain ecosystems while launching financial tokens, building a large audience and brand.  Original content includes: X posts (>100K followers), music on spotify (29K monthly listeners), and NFTs. Read the Zerebro whitepaper for an overview of the project and system design.  
• TruthTerminal: An AI Agent that generates X posts, and autonomously accepted a $50K Bitcoin investment from Marc Andreesen, which it autonomously used to launch a memecoin that rose to a $300 Million valuation. Here is the full story and discussion.  
• Futureverse: A platform, creator toolkit, and set of immersive experiences for users built around a combination of metaverse, gaming, AI, digital identity, and blockchain. Futureverse has secured partnerships with high-profile brands like Wimbledon, FIFA, Mastercard, and collaborations with cultural icons like Snoop Dogg, Timbaland, and Keanu Reeves.  Their manifesto and whitepaper provide an in-depth overview of their vision and technical platforms. 

What To Do About It:

• Marketers should follow this space and experience some of the new things that emerge as a way to understand where consumer interest and attention is headed
• Brands may consider advertising or partnership opportunities with projects that gain traction with their target audiences
• Brands should also consider experimenting with launching similar projects and consumer facing AI Agents to create content and engage with consumers as a way to build their brands

3) AI Agents to Transform Marketing Operations & Digital Orchestration

Development and interest in AI Agents has skyrocketed in the past year with applications for both consumers (see items 1 and 2 above) and knowledge workers broadly. The big opportunity for Marketing teams is in more effectively orchestrating the digital operations of modern marketing technology stacks. This is beautifully articulated by Scott Brinker in his recent post which describes the evolution of marketing technology stack designs and the existing gap around integration of platforms that AI agents are uniquely positioned to solve. 

Modern, data-driven marketing is all about capturing and curating data to inform relevant and meaningful communications with consumers. The complexities around integrating this data from disparate sources, resolving identities while protecting privacy, transforming the data to prepare it for usage, and actually making use of data in a consumer communication, are many. This is where our team at Transparent spends the bulk of its efforts helping clients to solve this set of problems. The next and most promising development to tackle these complexities is AI Agents applied to marketing technologies and marketing operations workflows.

What To Do About It:

• The promise AI Agents to help solve the above is a large one and we are still in the early days of applying. As such, Marketers should be experimenting with these new technologies today and setting up proof of concepts to really understand the potential for their brand within their marketing technology stack and their marketing operations.
• This LI post from our very own Aaron Fetters best describes the two things marketers should do to get set up for success:  
  • 1) Workflow Mapping: by documenting key workflows including the enabling people, roles, process, platforms, and data
  • 2) Data Preparedness: by establishing a data strategy to prioritize data-driven marketing use cases, the data requirements, and the plan to gather and prepare this data for usage

4) Data Clouds Generate a Gravitational Pull

More and more enterprises continue to move into cloud based data infrastructures. The advantages for marketers include: better facilitation of data governance & privacy, limited data copying and proliferation, better access and sharing of enterprise data outside of marketing, enablement of clean room & data collaboration while protecting privacy, clearer sources of enterprise data truth, more efficient processing by bringing the compute to the data (vs the other way around), and the composable nature of being able to design a custom stack based on best in class applications that are part of the larger cloud ecosystem. 

This comprehensive guide from Snowflake further unpacks these areas by articulating a useful classification of the core capabilities of a modern marketing data stack along with the leading vendor partners by Marketing Tools & Platforms and Data Tools & Platforms.

The idea of Data Gravity is that once a data cloud infrastructure is set up, the value it enables kicks off a virtuous cycle of incentivizing marketers to pull more and more data into their centralized data cloud. We observe this phenomena with our clients who benefit today and are best positioned to leverage their data first for the newest AI powered applications in the near term.  

What To Do About It:

• Marketers must first set a data strategy to clarify the data requirements for every priority data-driven marketing use case
• Work with Enterprise Technology to establish a Data Cloud Infrastructure if not already in place
• Explore Data Clean Room and Data Collaboration use cases. Many brands start by renting data cloud infrastructures to enable data collaboration use cases even when a full enterprise data cloud has yet to be established.

5) Marketers Seek to Unify Fragmented Measurement

Full funnel marketing seeks to deploy communications that influence every stage of the consumer journey. This is an effective approach that involves executing many different marketing channels, tactics, and creatives across publishers.  The complexity in full-funnel activation requires measurement that accounts for the nuances of each communication, while leveling up and unifying the measures into a normalized view under a holistic strategy. This is the big challenge we’ve noticed that marketers are looking to tackle now and in the near term. 

Although the cookie may never completely crumble, measurement techniques in recent years have sought to solve for signal loss as cookies and other digital identifiers became less active and less persistent through the consumer journey. Marketing Mix Models became the go-to technique for broad and holistic measurement, while MTA became less relevant due to this signal loss. Today, marketers understand that there is not a single technique that can effectively measure all activations, rather a variety of techniques are required. The challenge is making sense of all of these measures and connecting each of these back into a larger unified measurement and marketing effectiveness program.  

What To Do About It:

• 1: Set Your Measurement Strategy: This consists of identifying your objectives and key results, standardizing your metrics & KPIs, and connecting with each stakeholder group (typically Finance, Marketing Executives, Marketing Analytics, Brand & Creative teams, and Channel & Performance teams) in your enterprise to gather & prioritize their measurement use cases. This requires a one time design that should be updated annually.  
• 2: Enable Planning: Scenario planning tools to balance expected ROIs with sales volume growth, Measurement Plans that establish objectives, metrics, and techniques for each activation, learning agendas that specify open questions, and experimentation plans each play a role in effective planning. These should occur prior to deploying your marketing campaigns.
• 3: Optimize: Tools to measure and optimize should include a broad and holistic approach (e.g. Marketing Mix Models), a faster and more granular approach (e.g. Incrementality), Direct Tracking (e.g. ad platform tools and/or web analytics), and Brand Tracking & Brand Lift. These should be used on a monthly, weekly, or daily basis depending on the tool.

Conclusion

We hope that you’ve found these trends to be informative and useful as you set your strategies and innovation plans for the year. It is truly an exciting time to be a marketer in 2025 as disruptive technologies like AI are set to really change the ways we gain information, consume content, shop, and work.  

Here’s to a peaceful and prosperous 2025!