销售记忆助手
Android app by Topshark Technology Co., Ltd. Tools · Topshark Technology Co., Ltd
- Store rating
- Unknown
- Store rating count
- Unknown
- Download price
- Free to download
- In-app purchases
- Not listed in captured metadata
- Version
- 1.0.0
- Listing last refreshed
- 2026-09-14
View the original store listing
Store description excerpt
In the sales process, have fragmented communications with clients via WeChat, email, and DingTalk ever caused you to forget details, lose leads, and miss orders? "Sales Memory Assistant" is a personal productivity tool specifically designed to solve this pain point. It doesn't change your communication habits; it simply saves key conversations with a single click when needed. All records are automatically and clearly aggregated by client, forming a complete communication timeline, allowing you to easily trace the flow of information and enhance professionalism and client trust. Core Functions: 📝 One-Click Archiving: Copy/share conversations from any platform such as WeChat, email, and DingTalk, and save them locally with one click. 🧠 Intelligent Aggregation: Automatically categorizes by client name, generating a complete communication timeline, eliminating fragmented information. 🔍 Lightning-Fast Search: Keyword search instantly locates historical conversations, eliminating the need to search through chat logs. 🛡️ Local Priority: All data is stored only on your phone, ensuring privacy and security. 📤 Flexible Export: Supports exporting conversations as documents for convenient reporting and archiving. Applicable Scenarios: Quickly archive key communication points after sales visits. Review historical conversations at any time when following up with clients to avoid missing commitments. Clearly convey the communication flow to clients during team collaborations. Our Commitment: No data upload: All records are stored locally on your device. No ad interruptions: Focus on efficiency, no irrelevant information pushed. Continuous iteration: Continuously optimize the experience based on user feedback.
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