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When to analyze customer reviews: a monthly habit and five extra moments

Analyse customer reviews once a month on a fixed day, and again at five moments: after a launch, after you change a supplier, formula or packaging, when a product’s rating drops, before you plan the next range or release, and after your busiest season. Reading and replying happen daily; analysis means counting what reviews are about, and counting needs a batch big enough to show a pattern.

What this comes down to

  • Replying is daily work; analysis is counting topics across a batch, and it needs enough reviews to show a pattern.
  • A fixed monthly day turns analysis into a habit instead of something that happens after a bad week.
  • Analyse right after any change to the product, so a new problem is caught while the old stock is still selling.
  • Compare periods with the same topics and the same length, and use mentions per hundred reviews, not raw counts.

SellerSort Team · Updated

Reading is daily. Analysis is not.

Reading a review tells you about one customer. Analysis tells you how many customers share the same problem, and whether that number is growing. The first is how you reply; the second is how you decide what to fix.

Analysing too often makes every week look like a trend: three complaints about a zip in five days feel like a crisis, and may be three out of three hundred. Analysing too rarely means a real problem ships for a season. A monthly batch sits between the two for most stores.

The baseline: one fixed day a month

Pick a day, the first Monday for example, and export the previous month’s reviews. The fixed day matters more than the exact date: a habit survives a busy month, and a well-meant when we get time does not.

If a month brings only a handful of reviews, patterns will not show at that size. Widen the window to a quarter and keep the same day.

Five moments to analyse outside the schedule

When to run an extra review analysis
MomentWhat you are looking for
After a launch, once the first batch of reviews is inProblems the testing missed, while stock can still be adjusted
After a change of supplier, formula or packagingNew complaints that did not exist before the change
When a product’s rating dropsWhich topic caused it, and since when
Before planning the next range or releaseThe most requested fixes and features, counted
After your busiest seasonShipping and service strain that normal months hide

Comparing before and after a change

The most useful analysis is a comparison. To make it fair, keep three things the same: the list of topics, the length of each period, and the unit. Raw counts mislead when sales change, so use mentions per hundred reviews.

An illustration, not real figures: a mug maker switches packaging supplier. In the three months before, arrived broken appears in 2 of every 100 reviews; in the three months after, 9 of every 100. Total reviews went up too, which is why the raw count alone would have looked like normal growth.

What you need before the first run

  1. An export of your reviews. The export guide covers the main platforms.
  2. A short, fixed list of topics, such as fit, quality, shipping, instructions and price, used the same way every month.
  3. A sheet with one row per month and one column per topic.

The Review Analyzer assigns topics, sentiment and severity to each review and lets you define up to 10 custom labels, so the topic list stays the same from month to month. Paste up to 30 reviews free; larger files use credits, one per review.

Questions

How often should you analyse customer reviews?

Once a month on a fixed day for most stores, widening to a quarter if a month brings only a handful of reviews. Add an extra run after launches, product changes, rating drops, and your busiest season.

What is the difference between reading reviews and analysing them?

Reading is looking at one review to understand and answer it. Analysing is counting what a batch of reviews is about, so you can see which problems are common and whether they are growing.

How do I compare reviews before and after a product change?

Use the same topic list and periods of the same length on both sides, and compare mentions per hundred reviews rather than raw counts, because the number of reviews changes with sales.

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