According to Deloitte’s 2026 The State of AI in the Enterprise Report, 34% of marketing leaders are transforming their daily operations with agentic AI. The following use cases cover a deeper level and deliver measurable business outcomes that appear in customer stories rather than survey charts. They reveal how companies deploy AI, use customer data, decisioning, and marketing automation to improve results one interaction at a time.
The use cases below come from companies running these programs on the Hightouch Agentic Marketing Platform. Each story shows how marketing teams incorporate AI into existing programs across customer journeys and campaigns, with customer data at the center of every decision.
The stories also point to a common pattern. The most effective AI in marketing use cases rely on two foundations:
- Customer data
- A brand context layer for safe AI output
The pattern across these stories is consistent: the strongest AI marketing programs produce results that compound over time because both foundations are in place.
Highlights
- The highest-impact use of artificial intelligence in marketing improves decision-making, not just content production. Customer stories from WHOOP, Otrium, and Fundrise show measurable gains tied to personalization, acquisition, and conversion.
- AI Decisioning helps marketers use AI to determine the next best action for each customer. As every interaction generates new outcome data, performance improves over time.
- Integrating AI with unified customer data allows marketing teams to focus on strategy, customer needs, and marketing goals rather than on manual campaign execution.
Productivity vs. revenue-driving use cases
According to Gartner research, marketers expect AI automation to grow from 16% of marketing work in 2026 to 36% by 2028.
Most marketing teams start out by using generative AI for content drafting, subject line variants, and image generation. Delegating repetitive tasks to AI helps busy teams increase productivity and focus on higher-value tasks, but streamlining workflows is the bare minimum of what AI tools can do.
At the 2026 Gartner Marketing Symposium/Xpo, Kristina LaRocca-Cerrone, a VP Analyst for Gartner, said,
*“The CMOs who win won’t just manage AI. They will integrate it into how marketing leads the enterprise. That’s how marketing becomes a value engine — not just a delivery function — in the age of AI.” *
When organizations tap into revenue-driving AI solutions, they can build individual-level decisioning, agentic execution across channels, and outcomes that improve with every interaction. These are the use cases that appear in customer stories with measurable lifts.
1. WHOOP: 10% cross-sell lift with AI Decisioning
WHOOP achieved a 10% lift in cross-sell conversions with AI Decisioning. The goal was to decide which offer to present, when to present it, and where to present it for each individual member.
That challenge came from the way cross-sell programs worked before. WHOOP had access to rich behavioral data, including member activity, recovery, and sleep patterns, but cross-sell campaigns still relied on segment-level logic, which could not match offers to individual members.
The use case focused on cross-sell decisioning at the individual level. Instead of treating members in the same segment alike, the system used predictive decisioning to evaluate behavioral history and select the product offer, timing, and channel most likely to drive conversion.
To power those decisions, WHOOP used Hightouch’s AI Decisioning inside Lifecycle Marketing Studio. AI Decisioning trains the reinforcement learning model on member behavior, optimizing cross-sell conversion as the north star metric.
Each decision worked toward the same goal: increasing the likelihood of a successful cross-sell.
The outcome was a 10% lift in cross-sell conversions.
Aoife O’Driscoll, lifecycle marketing lead at WHOOP, says,
“It would take years to get to the level of insight that we've garnered in a matter of weeks.”
The result depended on more than the model itself. The Composable CDP supplied the unified, real-time member profile needed for AI integration. Without that, the model would have been making decisions with only part of the picture. With it, WHOOP could use its customer data to support more informed decision-making across every member interaction.
2. Otrium: growth acquisition efficiency with Ad Studio
Otrium increased conversions by 15% and reduced campaign launch time by 70%. It wanted more performance marketing volume in the ad creative. It did not want to lose brand consistency. At the same time, customer data was spread across multiple systems.
The use case focused on on-brand ad creation at a performance-marketing scale. Rather than relying on platform-native lookalike audiences, Otrium wanted targeting built from actual customer behavior and data-driven audience insights.
To support their marketing efforts, Otrium used Hightouch’s Ad Studio for on-brand ad and content generation. Their Customer Studio helped them build audiences from first-party data. Meanwhile, the Match Booster increased match rates across Google and Meta.
Philip Sonneveldt, head of growth at Otrium, says,
“We didn't need to be strict with our prompting; we could provide a generic request and get the right output almost immediately.”
The outcome was 15% more conversions, 70% faster campaign launches, and stronger campaign efficiency.
It worked because ad performance depends on audience quality. First-party audiences built in Customer Studio give marketers stronger inputs than broad platform-native lookalikes because they reflect actual customer behavior rather than predicted behavior.
3. Fundrise: 1:1 personalization at investor scale
Fundrise reported a substantial lift in win-backs and a 4x increase in investments compared to previous campaigns after adopting AI Decisioning. The company serves a mass-affluent investor audience with different financial goals, interests, and behaviors. A segment such as "young investors" could not capture the context behind each individual investor.
Fundrise used personalized lifecycle communication across email, web, and in-app channels. The goal was to choose the right message, offer, and timing for each investor.
To support that goal, Fundrise turned to Hightouch’s AI Decisioning for individual-level decisioning and Customer Studio for audience segmentation and marketer-accessible audience building. Underneath both sat a Composable CDP. This provided the unified investor profile data needed to inform every decision.
The outcome went beyond improved campaign performance.
Fundrise moved from segment-based personalization to investor-level personalization, using predictive decision-making so each interaction reflected an investor’s unique context and behavior.
As Lindsay Kaplan, senior director of Lifecycle Marketing at Fundrise, explains:
“This shift has been a turning point for our team. Rather than being bogged down in building triggered journeys or executing batch campaigns, we’re digging into investor needs and how we can best serve them.”
Why did it work? The marketing team retained control of strategy and brand voice. AI Decisioning handled the volume of individual decisions that a marketer-led team could not make on its own. This is the manager of agents operating model in practice.
4. Fullspan Health: brand-safe personalization for 3 million+ subscribers
Fullspan Health replaced 30 condition-specific newsletters with one personalized Healthline Digest for more than three million subscribers. The program increased email unique CTR by 11.2% and reactivated 29.8% of dormant subscribers.
The lifecycle team had the audience data needed to identify overlap across the 30 lists, but extracting and using it required manual work. Hightouch agents analyzed the lists in 15 minutes and found that 25% of subscribers appeared on more than one, giving the team a clear basis for content that reflected each subscriber’s condition mix.
After adopting Hightouch’s Agentic Marketing Platform, Fullspan Health built the digest in Hightouch Lifecycle Marketing Studio, where the platform selects content modules based on each subscriber’s condition mix. The team created the template, design, and HTML in the platform, then added brand, editorial, and clinical guardrails before reviewing and approving the output.
Lindsey Allison, director of consumer marketing at Fullspan Health, says,
“Our team acts as the strategic lead…and the platform handles the specialized execution.”
The workflow shows how customer data and brand knowledge work together in content production. Customer data determines which modules each subscriber receives, while brand, editorial, and clinical guardrails keep the output within Fullspan Health’s standards and leave final approval with the team.
5. Thumbtack: proactive insight and 10x faster campaign launches
Thumbtack reduced campaign cycles from 4–6 weeks to days and cut cross-team coordination from about 40 hours to 10. The lifecycle team also increased on-brand, personalized variants from one or two per campaign to more than 20.
Before Hightouch, campaign launches involved five or more teams, and learning what worked after launch required another request and another wait. The team also lacked a self-serve way to test audience size, behavior differences, or a personalization angle before committing resources, so many ideas moved forward on assumptions or stayed in the backlog.
Hightouch Lifecycle Marketing Studio sits on Thumbtack’s BigQuery data and brings its brand guidelines, campaign history, and best practices into the workflow. Marketers can validate audience assumptions while a campaign takes shape, generate email and push assets against existing templates, and review experiment results without waiting on separate teams.
Alex Goldstein, senior lifecycle marketing manager at Thumbtack, says,
“The most surprising part was working with the agent to build conviction in a strategic approach.”
This creates a practical learning loop between audience insight, campaign production, and measurement. Thumbtack’s marketers still set the strategy, define creative direction, and decide what ships, while the platform handles the analysis and production work that once depended on cross-team handoffs.
The stories are the proof. The foundations are the reason
A common mistake in AI marketing is treating AI like a speedy production assistant. The higher-leverage use is as a decisioning layer that learns from every customer interaction.
WHOOP’s cross-sell lift, Otrium’s campaign efficiency, and Fundrise’s investor-level personalization all depended on the same two foundations — customer data that made decisions smarter, and brand knowledge that kept outputs safe. Without both, AI remains a production shortcut. With both, each campaign gives the next decision better context.
Want to see the platform behind these use cases? Explore Hightouch’s Agentic Marketing Platform.
FAQs
Q1: What are the most impactful AI in marketing use cases?
The most impactful use cases of AI in marketing change decision-making, not just content production. Individual-level decisioning, brand-safe creative generation, and proactive intelligence produce compounding gains. They learn from customer behavior, campaign outcomes, and brand context over time.
Q2: How does AI decisioning improve marketing performance?
AI decisioning improves marketing performance by helping marketers make faster decisions for each customer. It evaluates which content, offer, channel, and timing are most likely to produce the desired outcome.
Hightouch AI Decisioning uses reinforcement learning and AI capabilities to improve future decisions as more interaction data enters the system.
Q3: How does using AI in marketing improve paid media performance?
AI for marketing improves paid media performance by connecting creative generation and audience targeting to first-party customer data. This allows campaigns to reach the audience at the right time with the right messaging.
With Hightouch: Ad Studio generates on-brand creative connected to first-party audience data. Customer Studio builds those audiences from behavioral and transactional signals in the warehouse. Match Booster increases match rates across Google and Meta so the right audience actually sees the ad.
