Customer Feedback App | AI In Software Development
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In this video, we’ll explore how to use AI columns to enrich customer communications data, turning unstructured emails into highly usable insights. This method is perfect for non-mission-critical data or when you want AI to process existing datasets automatically. We’ll also recap the difference between AI Actions and AI Columns, and share tips for building more intelligent apps with both approaches.
🔑 Key Takeaways:
AI Actions vs. Columns: Use actions for human-editable data and columns for automatic, ongoing enrichment.
Data Enrichment: AI columns extract summaries, sentiment analysis, demographics, and more from unstructured emails, providing instant insights for reporting and triaging.
Automatic Data Structuring: AI saves hours of manual labor by turning raw data into structured insights, which can be used for dashboards, sorting, and filtering.
Generative Text: Automate response drafting to speed up customer support workflows.
💡 Tips for Using AI Columns:
1) Combine Actions & Columns: Use actions like text generation to streamline workflows alongside AI columns further.
2) Process Historical Data: Apply AI columns to existing data, copy results to a static column, and remove the AI column if it is no longer needed.
3) Bulk Upload Data: You can save time by adding new data to tables with AI columns using CSV or Excel uploads.
This app demonstrates the power of AI to turn customer feedback into actionable insights, reducing time and improving decision-making.
Timestamps:
0:00 – Intro
1:05 – Enriching Customer Emails with AI Columns
3:22– Tip 1: Use Actions & Columns
4:02 – Tip 2: Processing Historical Data
4:37 – Tip 3: Bulk Uploading Data
#AIColumns #CustomerFeedback #DataEnrichment #AIForBusiness #AutomatedWorkflows #GlideAI
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