BYOBot

Customer Feedback Automation

Automate Customer Feedback Analysis

NPS and survey coding, theme extraction, sentiment tracking, review monitoring, routing: describe your feedback sources and get a portable agent spec. First build free.

Code NPS responses Summarize survey results Track sentiment over time Monitor reviews Route feedback Draft close-the-loop replies

What You Can Automate

📋
Survey & NPS Analysis
Code open-ended responses into themes and drivers, and turn a spreadsheet of comments into findings a team can act on.
🧩
Theme Extraction
Cluster feedback from every source into the handful of patterns that recur, ranked by how often and how loudly.
📈
Sentiment Tracking
Score sentiment over time so a slow slide in how customers feel shows up as a trend line, not a gut feeling.
⭐
Review Monitoring
Watch new reviews across your channels, flag the ones that need a reply, and draft a response in your brand's voice.
🔀
Feedback Routing
Send each piece of feedback to the team that owns it, product, support, or billing, with the context attached.
↩️
Close-the-Loop Drafts
Draft follow-ups to customers who flagged a problem, so critical feedback gets a human reply instead of silence.

Tools It Works With

Typeform Google Forms Delighted Zendesk Intercom Google Sheets Slack Notion Help Scout

Where It Runs

💬
AI Chat Tool
Run it in any chat AI
Paste survey exports or a batch of tickets into Claude, ChatGPT, or Gemini with a BYOBot spec and get back the themes, the sentiment read, or the summary. No OAuth required.
🖥️
Browser Agent
Agent gathers the feedback
A browser agent pulls responses from your survey and support tools and assembles the analysis, without a developer wiring exports first.
⚙️
Automation Stack
Fully automated feedback loop
Wire the spec into your stack so new responses get coded, routed, and summarized on a schedule and the insight lands in Slack.

Build Your First Feedback Agent

Describe how you analyze feedback. Get a portable spec. Run it wherever the responses live.

$25 USD
S$34 SGD · 5 builds per pack · first build free
Build your feedback agent →
No account. No code. Works with any survey or support tool.

Who Uses This

Customer Success Customer Support UX Researchers Product Managers Founders Knowledge Base Ecommerce Operations

Customers tell you exactly what to fix, constantly, across surveys, reviews, and support tickets, and most of it is never read. Not because teams do not care, but because reading a thousand free-text NPS comments and turning them into a ranked list of themes is a full day nobody has. So the feedback piles up, the same complaint recurs for two quarters, and the fix that would have moved retention waits behind a backlog of noise. The analysis is a pattern task, and pattern tasks are automatable.

BYOBot turns feedback analysis into a portable spec: a structured file that defines the sources, the way you code and cluster responses, and the output you need. Build the NPS-coding spec once and run it by pasting an export into a chat AI, pointing a browser agent at your survey tool, or wiring your stack to code responses as they arrive. Your theme taxonomy lives in the file, so the coding is consistent instead of drifting with whoever ran it last. It feeds the customer success workflows and sharpens churn risk automation with the reasons behind the churn.

Start with whichever source has the most unread volume, usually open-ended survey responses or support tickets, and get it clustering into themes. Once the coding runs, sentiment tracking and routing follow the same shape, and the loop closes: feedback becomes a ranked list, the list becomes fixes, and the customer who flagged the issue gets a reply. Research teams turning this into deeper studies can hand off to the UX researcher workflows for synthesis.

Common Questions

BYOBot automates the analysis of open-ended feedback at volume: coding NPS and survey responses into themes, extracting recurring patterns across sources, tracking sentiment over time, monitoring reviews and flagging replies, routing feedback to the owning team, and drafting close-the-loop follow-ups. If the task reads free-text feedback and produces themes, scores, or routing, it can become an agent.
Coding automation reads each open-ended response, assigns it to the themes in your taxonomy, and identifies the driver behind the score. Because your taxonomy lives in the spec, coding stays consistent across runs instead of shifting with whoever did it last. A thousand comments become a ranked list of what to fix, in minutes rather than a lost day.
Yes. Sentiment automation scores feedback as it arrives and trends it across weeks or months, so a gradual decline in how customers feel appears as a line on a chart rather than a hunch. You see the shift early, while there is still time to respond, instead of discovering it in a quarterly review.
It works across survey and support sources including Typeform, Google Forms, Delighted, Zendesk, and Intercom, because the portable spec maps your analysis logic rather than one tool's API. Feedback scattered across several tools gets analyzed with one consistent method.
Yes. It flags responses that need a human reply, especially critical or at-risk feedback, and drafts a follow-up in your voice with the context attached. Your team reviews and sends. Closing the loop is what turns a complaint into a retained customer, and it is the step teams skip when the volume is high.
No. Paste survey or ticket exports into an AI chat tool for instant themes, run a browser agent that gathers responses from your tools, or connect the spec to your automation stack for scheduled coding and routing. You can start with zero integration and automate the loop later.