Lifecycle marketing has always been about delivering the right messages, in the right places, at the right times to guide customers to take specific actions with your brand. The right email can turn a one-time buyer into a loyal customer. The right push notification can drive a crucial subscription upsell that doubles lifetime value.
Historically, marketers have defined journeys manually—step-by-step flows designed to lead audiences down a carefully planned path. Predefined journeys are great for structured and predictable campaigns that require tight control. But as the number of customers, products, and engagement channels grows, these predefined journeys often become bloated with complex "if/else" logic and split tests that limit optimization - more personalization = more time building rules.
In 2025, marketing has evolved with AI. Lifecycle marketers are replacing key predefined journeys with AI Decisioning, which uses reinforcement learning and AI agents to determine the best way to engage each customer individually, continuously optimizing for outcomes like conversions, retention, and lifetime value. AI Decisioning is uniquely desiged to handle complex, ongoing, dynamic campaigns at scale.
Journeys and AI Decisioning each have their strengths and weaknesses. Understanding when to use one over the other will help you build smarter campaigns and drive better results. Let’s break it down.
Use predefined journeys for precision and control
Journeys are exactly what they sound like: a series of triggers and steps that map out which channels, messages, and times to engage with cutomers. Journeys are predictable, structured, and manually created and modified by marketers.
Journeys are like trains on pre-laid tracks. You design the route, schedule the stops, and control the pace. Once the journey starts, every customer follows a predefined path, ensuring consistency and reliability.
Pros & cons of journeys
Pros
Predictable: You define every aspect of the journey including channels, timing, subject lines, and content.
Total control: Every ruleset, image, and line of text is defined by your team, ensuring strict adherence to brand guidelines.
Cons
Static: Journeys don’t adapt to changing customer behavior without manual intervention.
Time-intensive: Managing complex journeys across multiple segments, behaviors, and offers takes significant effort.
Limited experimentation: A/B testing is restricted by human bandwidth and the complexity of setting up statistically significant experiments.
When to use static journeys
- Transactional messages: Order confirmations, shipping updates, and other automated communications where precision is key.
- Educational sequences: Structured onboarding journeys where information must be delivered in a fixed order.
- Short-term batch campaigns: Seasonal promotions like Black Friday, where there isn’t enough time for AI Decisioning to optimize.
How Petsmart orchestrates journeys for 65M+ members
Learn how Petsmart runs their award-winning Treats Rewards program on Hightouch, sending 4 billion emails annually across 1000+ unique audiences to drive incremental sales.
Learn more
Use AI Decisioning for personalization, scale, and impact
AI Decisioning flips the script. Instead of manually curating each step of a journey, you give the AI your goals, content, and guardrails. The AI then determines the best engagement strategy for each customer—dynamically.
This approach is outcome-focused and designed for evergreen campaigns where personalization and continuous optimization are key. If journeys are like trains on fixed tracks, AI Decisioning is like a fleet of self-driving cars—each customer’s journey adapts based on live behavior, engagement history, and preferences.
Pros & cons of AI Decisioning
Pros
1:1 personalization: Messages, channels, and send times are dynamically tailored based on customer behavior and AI learnings.
Self-improving: AI Decisioning continuously experiments and optimizes results over time.
Outcome-oriented: Every decision is driven by goals like conversions and retention, rather than rigid rules.
Guardrails for control: Marketers define the creative, guardrails, and audience parameters to ensure brand consistency while maximizing outcomes.
Cons
Less predictable: While you control which channels and messages can be used across audiences, the AI determines the optimal variation per customer.
Requires a learning period: AI Decisioning improves over time. Short-term campaigns may not allow enough time for optimization to outperform a well-structured batch journey.
When to use AI Decisioning
- Repeat purchase campaigns: Deliver hyper-targeted product recommendations based on customer behavior and preferences.
- Loyalty & engagement programs: Nurture customers with personalized incentives and content to drive retention.
- Cross-sell & upsell campaigns: Recommend the best next product, subscription tier, or service based on usage and purchase history.
- Cart abandonment campaigns: Dynamically test messaging, timing, and channels to bring customers back to complete their purchase.
- Renewal & retention campaigns: Optimize renewal offers based on pricing sensitivity and customer engagement.
- Winback campaigns: Identify and re-engage lapsed customers with personalized offers tailored to their likelihood of reactivation.
Check out our comprehensive list of the best use cases for AI Decisioning →
How WHOOP drove +10% incremental conversions swtiching from predefined journeys to AI Decisioning
Learn how WHOOP uses reinforcement learning and AI agents to dynamically test and personalize cross-sell offers for each customer, driving incremental sales while freeing up the team to focus on strategic marketing.
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Where does Hightouch fit in?
We believe marketers shouldn’t have to choose between static journeys and AI-driven optimization. Instead, Hightouch empowers your to leverage both approaches while unlocking the full potential of their customer data:
- AI Decisioning: AI Decisioning operates as the brain over your marketing channels, conntinuously determining the best engagement strategy for every customer.
- Journeys: When you do need a predefined journey, a customer engagement platform like Iterable or a platform agnostic solution like Hightouch Journeys enables you to use all of their data to build cross-channel campaigns.
With Hightouch, you get the precision of journeys and the power of AI Decisioning, allowing you to use the optimal engagement strategy for every campaign.
Conclusion
As a lifecycle marketer, the choice isn’t predefined journeys versus AI Decisioning—it’s about knowing when and how to use each effectively:
- Use AI Decisioning for personalized, always-on optimization at scale.
- Use predefined journeys for structured, predictable campaigns that require full control.
With the right strategy—and the right tools—you can create seamless, high-impact experiences that keep your customers engaged for the long haul.
Want to learn more?
Schedule a call with a solutions engineer to learn more.
