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Simplify the experience of Data 360 Segmentation with Conversational AI Agents

www.salesforceblogger.com· ·Intermediate ·Admin ·4 min read
Summary

Data 360 introduces AI-powered conversational agents that simplify creating and managing customer segments by eliminating manual data model navigation and SQL queries. These agents allow marketers to use natural language to build segment rules, check member inclusion, identify overlaps, inspect failures, and optimize schedule times, improving efficiency and confidence. This new approach transforms complex segmentation tasks into intuitive workflows accessible to business users, reducing errors and redundant marketing efforts while increasing trust in data-driven decisions.

Takeaways
  • Use conversational AI to create segment rules without needing deep data model knowledge.
  • Leverage segment overlap checks to avoid redundant targeting and identify upsell opportunities.
  • Verify segment membership and troubleshoot exclusions proactively with AI agents.
  • Inspect segment failures in a self-service manner with actionable AI recommendations.
  • Optimize segment run schedules using AI-driven timing recommendations.

In the world of data-driven marketing, precision and efficiency are essential. For business users, creating and managing the customer segments that power their campaigns is a foundational task, however it’s often more complex than it needs to be, with manual analysis, and time-consuming troubleshooting. Addressing the gaps in segmentation The task of creating a segment for a campaign looks easy, but can be challenging. First, building the segment itself sometimes requires understanding the underlying data model, like choosing which  Data Model Objects (DMOs) hold the proper attributes . Then once a segment is built, new questions arise: does this segment audience exist already in some other segment? Why did a specific member not qualify? Why did the segment fail to run? Did the segment contain the members I am looking for? Previously, answering these questions required navigating the data model, creating manual SQL queries, comparisons in Data Explorer or Query builder.

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