Overview
AI Decisioning (AID) is a system for automating marketing decisions at the individual user level.
The core unit in AI Decisioning is an agent. Agents replace traditional marketing campaigns. Instead of designing a fixed journey or running manual A/B tests, you create an agent that combines:
- Target audience
- Desired outcomes (e.g. purchases, sign-ups)
- Creative assets (such as email subject lines, SMS copy, push notifications, or images)
- Guardrails (frequency caps, timing windows, eligibility rules)
Once configured, the agent uses event data—like purchases, clicks, or app opens—as feedback signals. Over time, it learns which messages, channels, and timings are most effective for different users.
You control the inputs and rules. Agents never create new content or act outside the audiences, goals, and guardrails you define.
Contact your Hightouch team to learn more about enabling AI Decisioning.
How agents works
Agents use your event data, such as purchases, email clicks, app opens, and page views, as feedback signals. These signals indicate which actions lead to positive outcomes. By analyzing them over time, agents learn which messages, offers, and channels are most effective for each type of user.
As they learn, agents automatically reduce the use of messages that don’t perform, reinforce those that do, and adjust their strategy for each individual.
Each agent follows a continuous cycle:
- Collect inputs – Audience, goals, creative, and guardrails
- Decide – Which message to send, when, and through which channel
- Deliver – Send via your connected tools (e.g., Braze, SFMC, Iterable)
- Measure – Capture outcomes like purchases, sign-ups, or engagement
- Learn – Refine future decisions based on results
This process runs automatically for every user, enabling personalization at scale.
Why use AI Decisioning?
Managing lifecycle campaigns manually often means building long sets of rules or running repeated A/B tests. Agents handle this automatically, based on the audiences, goals, and creative options you define.
With AI Decisioning, you can:
- Personalize every send: An agent can determine whether a lapsed customer should receive a discount email, a push notification, or a reminder SMS.
- Find the right timing: Agents can decide whether a user is more likely to respond in the morning, evening, or after certain behaviors.
- Learn what works: Track which messages, channels, and times drive conversions, and let agents adjust based on results.
- Scale experimentation: Agents run many small experiments in the background without requiring you to set them up manually.
Best use cases
AI Decisioning is most useful for lifecycle campaigns where user behavior varies and is difficult to manage with fixed rules. Common examples include:
- Onboarding – Encourage new users to complete their first key action
- Win-back – Re-engage lapsed or inactive users with the right offer
- Cross-sell or upsell – Suggest complementary products or upgrades
- Referral – Prompt high-value users to invite friends
- Retention – Keep engaged users active with tailored experiences
Each agent is designed around an outcome (such as purchases, referrals, or sessions). Agents continuously learn which combinations of message, channel, and timing work best for each segment.
Key features of AI Decisioning
| Feature | What it does | When to use |
|---|---|---|
| Agents | Define goals, audiences, message options, and guardrails | Every campaign starts here |
| Actions | Add creative content (emails, SMS, etc.) and test variants | After creating an agent |
| Inspector | Preview past and upcoming actions for real users | After creating actions |
| Collections | Dynamically recommend personalized products or content | After creating actions |
| Insights | Analyze performance by user, message, or timing and optimize campaigns based on results | After an agent launches |
| Configuration | Define workspace-wide defaults such as access and time zones | Set up once per workspace |
Understand what’s working with AI Insights
AI Insights shows how well your agents are performing and why. As agents run background experiments, Insights highlights the most important trends across:
- Conversion breakdowns by segment (e.g. state, loyalty tier, device type)
- Creative performance by variant, channel, or tag
- Timing insights showing top-performing send windows
- Outcome summaries including lift, statistical significance, and winning group
This helps answer questions such as:
- Which products are driving the highest conversions among new users?
- What subject lines perform best with users aged 25–34?
- Are mobile users more responsive to push notifications or SMS?
Insights provide more depth than standard A/B testing by showing why a campaign performs well and how to apply those learnings across agents.
Next steps
Login to your Hightouch account to get started with AID. Please contact your Hightouch team to learn more.