Why Attend

As AI becomes more relevant inside Marketo, one of the biggest opportunities is not just content generation. It is using AI to clean, normalize, categorize, and enrich the data that powers segmentation, scoring, routing, personalization, and reporting. In this session, Marketo Champions will share practical frameworks for applying AI to operational data challenges, including form fill classification, attribution categorization, job title to persona matching, and phone number formatting. These are the kinds of low-risk, high-reward use cases that can create immediate value while also helping prepare your instance for broader AI adoption.

You will also learn when to use real-time AI processing inside Marketo versus when to use the OpenAI Batch API for larger backfills and database cleanup projects. The session specifically covers Batch API workflows, real-time processing approaches, privacy considerations, and how to remove PII before sending data to AI systems. Whether you are just beginning to explore AI in Marketo or looking for more scalable operational use cases, you will leave with ideas and patterns you can apply right away.

Description

This session focuses on practical ways to use AI for data categorization and normalization at scale in Marketo. Learn how AI can be applied to real operational problems such as identifying suspicious form fills, standardizing attribution values, mapping messy job titles into usable personas, and formatting phone numbers for downstream activation. The session will also cover how to think about implementation patterns, including when to process records in real time through Webhooks and Self-Service Flow Steps, and when to use the OpenAI Batch API for bulk processing and historical backfills.

Our Champions will also walk through privacy and governance considerations, including removing or anonymizing PII and understanding safe ways to integrate Marketo with AI. Along the way, we will share practical examples, implementation considerations, and common tradeoffs so attendees can build a more AI-ready Marketo instance without overcomplicating their architecture.

Agenda

• Introduction & the AI-Data Foundation Connection

  • Why some of the best AI use cases in Marketo are operational, not just generative

  • Overview of the use cases and implementation paths we will cover

  Low-Risk, High-Reward AI Use Cases

  • Form fill classification and suspicious lead detection

  • Attribution categorization for cleaner reporting and segmentation

  • Job title to persona matching for better scoring and targeting

  • Phone number formatting for SMS readiness and enrichment workflows

  OpenAI Batch API for Scale and Backfills

  • When Batch API makes sense versus synchronous processing

  • Export from Marketo, process externally, and import results back

  • Cost, scale, and operational considerations for large record volumes

  Realtime AI Processing in Marketo

  • Using Webhooks for real-time AI-driven decisions

  • Using Self-Service Flow Steps to extend Marketo workflows

  • How to decide between real-time and bulk processing approaches

  Privacy, PII Removal, and Safe AI Implementation

  • Removing or masking sensitive data before processing

  • Key privacy considerations when sending data to AI systems

  • Practical guidance for more responsible AI usage in Marketo operations

  Performance, Key Takeaways & Q&A

  • Ways to improve AI output quality over time

  • Key lessons for building an AI-ready Marketo instance

  • Final Q&A and practical next steps

Target Audience

• Marketo Users: Professionals already using or considering Marketo who want to expand their marketing capabilities.

• Marketing Operations Professionals: MOPs teams responsible for Marketo administration and data quality

• Marketo Administrators: Those managing database architecture, integrations, and technical infrastructure

• AI/Automation Adopters: Organizations preparing their Marketo instance for AI-powered capabilities

• Data-Conscious Marketers: Teams looking to improve data quality, reporting accuracy, and campaign effectiveness