This template centralizes the entire lifecycle of customer grievances, allowing support teams to move beyond scattered emails and rigid spreadsheets. It provides a structured environment to log tickets, assign them to agents, and monitor progress from "New" to "Closed" without losing context.
The system connects four key elements: Users (customers and agents), Products, Complaints, and Resolution Steps. Because these tables are linked, you can instantly see every complaint associated with a specific SKU or view a support agent's entire interaction history with a single click.
Advanced fields like "Sentiment Analysis" and "Suggested Response" prepare your data for automation. You can configure AI to assess customer tone and draft replies, reducing manual effort for your team.
Spreadsheets handle simple lists well, but they fail when tracking complex support workflows involving multiple stakeholders and detailed history logs.
Unlike flat spreadsheets that rely on fragile VLOOKUPs, Softr Databases use native relational connections. This means a complaint is legally linked to a customer and a product, ensuring data integrity. You can easily roll up total complaints per product without writing complex formulas or worrying about broken cell references as the dataset grows.
This template includes devoted structures for tracking resolution steps and urgency levels, ensuring high-priority issues are never buried in a grid. With Database AI agents, you can automate the tedious parts of support, such as analyzing complaint sentiment or generating ticket summaries, directly within your records.
Manage customers and support staff roles with contact info and avatars
Catalog of offerings linked to complaint volume and SKU details
Analyze tickets with AI sentiment detection and suggested responses
Log intervention actions and history to resolve customer grievances
This template is designed for service-oriented teams who need structure without the complexity of enterprise helpdesk software.
Adapt the template to your specific support workflow in seconds. You might add a "Warranty Status" field to the Products table or modify the "Action Type" options in Resolution Steps to match your company's standard operating procedures.
Don't start from scratch—upload your existing customer lists, product catalogs, and historical complaint logs via CSV. This allows you to transition from legacy spreadsheets to a relational system immediately.
Turn this database into a fully functional client portal where customers can log in to submit tickets and view their status. Using the interface builder, you can create specific views for agents to manage their queues while ensuring customers only see their own data via granular users and permissions. This separates your internal data structure from the public-facing experience.
A complaint management database is a structured system for logging, tracking, and resolving customer issues. Unlike a simple list, it links complaints to specific customers, products, and resolution steps, providing a complete history of every interaction and ensuring no grievance slips through the cracks.
No-code databases allow support teams to build production-ready tools without relying on engineering resources. You get the power of a relational database—ensuring data integrity and scalability—with the flexibility to easily modify fields (like status options or urgency levels) as your support process evolves.
AI can significantly speed up response times by analyzing data as it arrives. Using Database AI agents, you can automatically detect customer sentiment (e.g., Angry vs. Neutral) and generate suggested responses in the database, allowing agents to review and send faster.
Yes, this database forms the backend for a powerful support portal. Using Softr's interface builder, you can create a secure app where customers log in to see only their tickets, while support agents access a master dashboard to manage the global queue and assign tasks.
Yes, you can copy and use this template for free. Softr's free plan includes database functionality, making it easy to start managing your support tickets immediately. As your team grows, higher-tier plans offer increased record limits.
Spreadsheets often suffer from data duplication and broken formulas when multiple agents try to edit them simultaneously. A database enforces structure—status fields remain consistent, and "resolution steps" stay linked to the correct ticket—making it far more scalable and reliable for team collaboration.