Feedback metrics for a portfolio of products

Four numbers for every product

Track four numbers for each product, in the same order every month: unique people who wrote in during the last 30 days, open items, average rating with its count, and the direction of the 30-day trend. That set is enough to compare products without building a reporting system of your own.

Open items are the sum of Planned and In progress. They show the work you have promised and not yet delivered. New items are different. They show what you have not read yet, so track them in the daily check instead of the monthly review. Write the export date next to every monthly number, so figures from different months are never compared by mistake.

Read the 30-day chart for direction

The dashboard shows a 30-day chart of feedback volume for each product. Read it for shape, not for exact values. A steady line with a single spike on the day after a release tells you the release caused reports. A line that climbs for three weeks tells you something is accumulating, even if no single day looks alarming.

Pair the chart with the counts by type. If bugs rise while ideas stay flat, the product is getting harder to use. If ideas rise while bugs stay flat, customers are settling in and asking for more, which is usually a healthier sign.

Open items show the backlog you carry

Open items measure how much promised work sits in front of you. A product with three open items is easy to finish. A product with thirty is carrying a backlog that will shape every planning decision. Compare open items with the weekly time you actually have for each product. If the backlog is ten times bigger than what you can clear in a month, the feedback is telling you to close or plan items more honestly, not to add more.

The average rating needs a count next to it

The average rating is useful only with enough ratings behind it. Three ratings can swing the average by a full point, and a product with ten ratings can still be noisy. Always write the rating count next to the average in your monthly sheet. When the count is small, treat the average as a hint and rely on the text of the messages.

Metrics that mislead across products

Some numbers look useful and make the comparison worse:

• Total messages across products. A chatty app with a large audience will always win. Compare each product with its own history instead.
• Praise count as success. Praise is a signal to protect something, not a score. Read it, but do not reward a product for having it.
• Average rating from very few people. See the section above. A small count makes the average look more certain than it is.
• Message volume during a launch. Launch weeks spike for reasons that have nothing to do with product health. Mark launch weeks in your sheet and read them separately.

A monthly sheet with one row per product

Keep one spreadsheet with one row per product, and update it on the first working day of each month. Use the numbers from the dashboard and the unique-people count from your export. The rows below are illustrative, to show the layout:

Product	Open items	Average rating (count)	Unique people, 30 days	Trend
Scheduler	4	4.5 (12)	9	Flat
Invoicing	11	3.9 (5)	6	Bugs rising
Notes app	2	4.8 (31)	14	Ideas rising

The Trend column is where you write one sentence about what changed and why. A row without that sentence is a number nobody will act on.

Which numbers should drive a decision?

Use the unique-people count and the open items together. Unique people tell you how widely a product matters, and open items tell you how much work is already waiting. A product with many unique people and a small backlog is a strong place to spend the next week. A product with few people and a large backlog needs a cleanup before it needs new work.

Review the sheet with the same person each month if you can. A sheet that changes hands every quarter loses its meaning, because each new reader may define the Trend column differently. Put a short note at the top that defines each column, so anyone reading the sheet in six months knows what the numbers measure.

How to get these numbers in Escuta Produto

Each product has its own inbox and dashboard view. Open the product, read the status counts for open items, then read the average rating and its count. The 30-day chart and the counts by type sit in the same view. For unique people, export the month's CSV and count distinct email addresses or names in a spreadsheet. Where people did not give an email, count rows with clearly different text, and note in your sheet that the count is an estimate. For the setup side, the hosted page docs explain how each product collects its messages. The way to choose which product to work on shows how to turn these four numbers into a decision. The weekly routine for five products explains when to read each row.