Development of TaggAI - AI Retention Platform

Panha Kim

TaggAI – AI Retention Platform

Client: Tagg AI, Year: 2025, Scope: AI-Powered Personalized Recommendation

💡 The Challenge

D2C brands often struggle with low customer retention. Traditional methods—generic email blasts and manual follow-ups—consume time, lack personalization, and miss opportunities for repeat sales. This results in high acquisition costs and weak brand loyalty.

🚀 The Solution

We designed and developed TaggAI, an AI-powered retention platform that transforms how eCommerce brands engage with their customers. The system delivers personalized, timely messages triggered by real-time customer behavior, social trends, and seasonal events.
Instead of one-size-fits-all marketing, TaggAI provides automated, context-aware communication—ensuring customers receive the right message, at the right moment, across the right channel.

✨ Key Features

Auto Restocking Alerts → Alerts customers when their frequently purchased items are running low.
Trend-Based Suggestions → Surfaces hot-selling products by analyzing social buzz + market demand.
Real-Time Telegram Updates → Keeps internal teams and suppliers instantly aligned.
AI-Generated Messaging → Creates human-like, tailored messages that boost conversions and repeat sales.

🛠 Tech Stack

Dify: Workflow automation & orchestration
OpenAI GPT: Personalized, natural content generation
Telegram API: Real-time notifications and team sync

🌍 Impact

From research, design, AI integration, and launch, we delivered the full end-to-end solution. Today, TaggAI enables D2C brands to:
Increase customer retention with personalized engagement
Boost repeat purchases through data-driven messaging
Save teams hours of manual work with automation
Build stronger brand loyalty through timely, relevant touchpoints
TaggAI redefines retention marketing, turning one-time buyers into long-term customers, all on autopilot.
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Posted Aug 29, 2025

Developed TaggAI, an AI-driven retention tool for personalized marketing.

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Timeline

Mar 10, 2025 - Mar 24, 2025

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