--- schema_version: "1" id: 86d695fd52ebf2ab1a222f0f1c784a60a7cf84a6d6b2210d79a6ca09cfa90879 title: Topic Classification collection: admin version: current locale: en-us portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_ai_predictive_model_classify.md canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_ai_predictive_model_classify.htm&release=264.0.0&type=5 source_site: help.salesforce.com content_type: documentation content_hash: 2d9e9878f2a77c70b088df608088401da467bbc6c9be2a6be7f24997907201f3 description: Use topic classification in Data 360 to organize unstructured text such as reviews, case comments, or survey responses, into meaningful categories. To evaluate records for classification, the model applies a trained language model to a selected field. For each record, the model assigns a topic label and a confidence score. Data 360 adds these outputs to your dataset. Apply topic classification in reporting and queries. products: - Data 360 release: "264" --- # Topic Classification Use topic classification in Data 360 to organize unstructured text such as reviews, case comments, or survey responses, into meaningful categories. To evaluate records for classification, the model applies a trained language model to a selected field. For each record, the model assigns a topic label and a confidence score. Data 360 adds these outputs to your dataset. Apply topic classification in reporting and queries. ![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_note.png) Note All topic classification models and algorithms use the new runtime. Review these topic classification goals. - Classify text into categories—for example, billing, product issues, or feature requests. - Standardize how text data is organized across datasets. - Identify trends and patterns by topic. - Segment data based on topics for targeted engagement. - Enrich datasets with topic labels and confidence scores. ## Use Cases Forecasting supports various use cases.

TYPE	USE CASE	WHAT DOES IT SOLVE
Marketing	Segment Audiences	To create more targeted campaigns, group customers by interests or topics.
	Analyze Campaigns	To understand what messaging resonates, classify responses and engagement by topic.
	Strategize Content	Identify themes across emails, web, and social channels.
Service	Track Issues	To speed up resolution, automatically categorize support cases, such as billing or technical issues.
	Route Cases	To speed up resolution, automatically categorize support cases, such as billing or technical issues.
	Manage Escalations	To handle cases faster, flag sensitive or high-priority topics, such as complaints or disruptions.
Sales	Analyze Deal Insights	To identify key topics, such as pricing, objections, or competitors, analyze emails, and call transcripts.
	Route Leads	To assign leads to the right team, classify inbound inquiries by product, industry, or use case.
	Upsell and Cross-Sell	Surface high-intent topics, such as demo requests or pricing discussions.

## Considerations Before you apply a topic classification model, review these considerations. - Overlapping or ambiguous categories reduce accuracy. - Very short or unclear text is harder to classify. - Model performance depends on the quality and relevance of input data. - The model is multilingual and supports text in multiple languages. ## Limitations Before you use topic classification, review these limitations. - Define clear and distinct topic categories for better accuracy. - Use text data that reflects actual customer language. - Review and refine categories periodically as business needs evolve. - Combine topic classification with sentiment analysis for richer insights. - Chunk the long text before you pass it through the model. Topic classification works best on short, intent-rich text up to 512 tokens