Two weeks into your beta, your feedback lives in eleven places. There's a Slack channel where testers drop one-liners at 1 a.m. There's a Google Form with 240 responses. There's a support inbox, a Notion page someone started and abandoned, three calls you recorded but never transcribed, and a spreadsheet a teammate maintains by hand and updates "when there's time."

Somewhere in that pile is the one bug that's quietly killing your activation rate, and the three feature requests that keep showing up in different words. But you can't see them, because reading 500 scattered comments and tagging each one by hand is a two-day job nobody wants to start. So the pile grows, the loudest tester wins, and you ship based on the last thing you happened to read.

UserTesting's research on beta programs puts the average mid-stage program north of 500 individual feedback points, and most product teams admit they never systematically process more than a fraction of it. The insight isn't missing. It's just buried.

You don't build the system. You describe it.

Here's the shift. The old way of fixing this was to build a tracker: open a board, add columns for source and type and severity, write the formulas, set up the views, then start the manual tagging marathon. That's still hours of setup before you've learned a single thing.

The new Dotallio is chat-first. You describe the outcome you want in plain language, and Dotallio assembles the whole thing — the board, the right columns, the categories, the views, even sample rows — and then helps you fill and analyze it. Drop in your raw feedback as a CSV, paste a wall of Slack messages, or attach a screenshot of a survey, and it structures the mess for you.

And everything it produces is a real, editable, version-controlled artifact. The board, the summary doc, the chart, the "you spoke, we listened" message — you can refine any of them, roll back a version, and share each with your team or the public. You're not generating throwaway output. You're building something that stays alive.

A real session: from pile to triage in a few prompts

Let's walk through it the way you'd actually type it.

Prompt 1 — build the machine:

Create a beta feedback board for my app. Columns for the raw feedback text, the source (Slack, email, survey, call), the tester's name, the date, plus AI columns for feedback type (Bug / Feature Request / Usability / Praise / Confusion), sentiment (positive / neutral / negative), severity (high / medium / low), and the affected feature. Add a Kanban view grouped by feedback type.

Dotallio creates the board with all of those columns already typed correctly — single-select for the categories, date for the date, AI-filled columns for type, sentiment, severity, and affected feature — and sets up the Kanban view. No column-by-column clicking. The structure shows up assembled.

Prompt 2 — pour in the chaos:

Here's the export from our feedback form. Import these 240 rows and put each comment in the raw feedback column.

You attach the CSV. Dotallio imports it, maps the columns, and lands every comment in the right place. If your raw feedback is a photo — a whiteboard from a user interview, a printed survey, a screenshot of a Slack thread — vision OCR reads it and structures the text into rows instead of you retyping.

Prompt 3 — let AI do the tagging:

Fill the feedback type, sentiment, severity, and affected feature columns for every row based on the comment text.

This is where the two-day job collapses. The AI columns run across all 240 rows in bulk and classify each one: this is a Bug, negative sentiment, high severity, affects Onboarding. That one's a Feature Request, neutral, medium, affects Reporting. Because every cell is a real artifact in a real column, you can open any row, see why it was tagged that way, and correct it — and your correction sticks.

Prompt 4 — find the gold:

Cluster the negative feedback by affected feature, count how many testers mentioned each, and write me a summary doc of the top 5 themes with example quotes for each.

Dotallio produces a doc artifact — a ranked rundown of your five biggest pain themes, each with a count and real verbatim quotes pulled from the rows. Now the pattern you couldn't see is on one page. The "minor" export bug that twelve different people complained about in twelve different ways is suddenly theme number one.

Keeping it alive after the first pass

A static snapshot ages out the moment the next wave of feedback arrives. The point of doing this in Dotallio is that the machine keeps running.

AI columns re-run on new rows. Every comment you add later gets typed, scored, and routed automatically — paste tomorrow's Slack batch and it's triaged by the time you've finished pasting.

Smart Workflows handle the multi-step work. At higher "smart" levels, you can describe a flow like "when feedback is tagged high-severity Bug, draft a clear repro-and-impact summary and route it into the engineering board" — and have it run on demand, on a button, or when a board event fires. You can also point web research at a vague complaint to enrich it: pull the linked help article, check whether a referenced competitor actually does the thing the tester wants, and drop that context into the row.

Charts make the trend legible. Ask for a pie chart of sentiment by week, or a flow of how a bug report moves from inbox to fix, and you get a Mermaid chart artifact you can drop into a stakeholder update.

Versioned artifacts mean nothing is lost. That top-5-themes doc you generated in week two? Regenerate it in week six and compare versions to see what got better, what got worse, and what new theme crept in. Dot keeps the history so you don't have to.

What this looks like on a Tuesday

You're a solo founder three weeks into beta. Friday afternoon you export the form, paste the week's Slack into a new batch, and snap a photo of the sticky notes from Wednesday's user call. Four prompts later you have 60 new rows, all tagged, clustered into themes, with a one-page summary sitting next to last week's so you can see the trend line.

The summary tells you sentiment around onboarding dropped, and the cluster shows seven people hit the same dead end on step three. That's your sprint. You didn't read 60 comments to find it; you described what you wanted and read the answer. Then you ask Dotallio to draft a short "you flagged this, here's what we're fixing" note for the seven testers, and you've closed the loop before the weekend.

That's the difference between feedback you collect and feedback you actually use.

Why this is better

• Setup is a sentence, not an afternoon. You describe the board and the categories; Dotallio assembles them, correctly typed, with views ready.
• The tagging marathon disappears. AI columns classify type, sentiment, severity, and affected feature across hundreds of rows in bulk — and re-run on every new row.
• Patterns surface on their own. Ask it to cluster, count, and quote, and the buried theme becomes a one-page doc.
• Messy inputs are fine. CSV, pasted chat, PDFs, or a photo — vision OCR and import turn raw mess into structured rows.
• Everything is a living artifact. Boards, docs, charts, and messages are editable and version-controlled, so you can refine, roll back, and compare over time.
• Triage keeps running. Smart Workflows and AI columns route and enrich new feedback on demand, so the machine doesn't go stale after the first pass.

Ready to turn your pile into product gold?

Stop letting the loudest tester set your roadmap and the rest of the feedback rot in eleven tabs. Describe the feedback machine you want, drop in your raw mess, and let Dotallio classify, cluster, and summarize it into something you can actually act on — then keep it alive as the next wave rolls in.

Try Dotallio Free and turn your next batch of beta feedback into your next great release.