Customer Interview Google Sheets Alternative

Your Customer Interview database at a glance

This template centralizes your customer discovery calls, participant details, and qualitative research in one structured space. It connects individual interview logs directly to customer profiles and synthesized findings, helping product teams turn conversations into clear decisions.

Organize research seamlessly across four linked tables: Users, Customers, Interviews, and Insights. Instead of hunting through messy document links, connect call transcripts directly to feature requests and usability issues.

Native AI fields analyze your research automatically. The database summarizes long transcripts into three bullet points, detects call sentiment, and searches the live web to fetch company descriptions for interviewees.

Why a Google Sheet fails as a user research repository

Google Sheets is great for quick notes, but user research breaks down when pasted into flat rows. Long transcripts clutter cells, anyone can accidentally overwrite critical findings, and there is no native way to extract recurring themes across dozens of interviews.

What a structured database changes

A relational database gives every piece of research a defined place. Transcripts, recordings, and dates stay formatted correctly, while linking interviews directly to customer profiles and overarching product insights without fragile cross-sheet lookups.

Permissions keep feedback secure while allowing researchers to log notes freely. This is exactly what Softr Databases are designed for, giving you a structured backend that can power interactive team dashboards. You can also connect an existing Google Sheet as a secondary data source if needed.

What you can do with this template

Map feedback directly to product roadmaps by categorizing logged insights as feature requests, pain points, or praise. Every insight tracks its source interview, keeping the original voice of the customer just one click away.

Built-in Database AI agents automate analysis by generating executive summaries and tagging transcript sentiment instantly upon record creation.

Who is this Customer Interview database for

• Product Managers: Prioritize backlogs by linking concrete user feedback directly to roadmap items.
• UX & User Researchers: Centralize discovery call recordings, full transcripts, and participant directories cleanly.
• Product Marketing Teams: Identify customer quotes, sentiment patterns, and competitive pain points.
• Founders & Operators: Keep track of continuous discovery calls across early-stage customer segments.

How to take it further

1. Customize the database
Adapt the database to match your exact research framework. Add custom insight categories like pricing feedback or technical blockers, adjust role permissions, or modify AI prompts to focus on specific product questions.

2. Import your existing data
Migrate past user research instantly using CSV bulk uploads. You can also connect external scheduling tools or call recorders via API to sync new interview metadata automatically as discovery calls wrap up.

3. Build a full app around it
Turn this database into an interactive research hub for your company. Use the AI app generator to create a custom portal with granular users and permissions, giving executives summary views while researchers get dedicated call submission forms.