What this dashboard is for
The Reviews dashboard shows the customer reviews left on your Papaya-served checkout flow — the star rating, any comment, and whether the diner was redirected onward to leave a public review (e.g. on Google).
Open it when you want a quick read on customer sentiment, or to scan recent comments for specific praise or complaints.
Where reviews come from
Whenever a customer pays with the Papaya checkout flow, they're offered a rating prompt at the end. If they leave a rating (1–5 stars) and optionally a comment, it's saved to customer_reviews. If they rate the experience highly, Papaya can also redirect them onward to leave a public review on a platform like Google — the % Redirected KPI shows how often that handoff happens.
1. # Reviews
Total reviews received in the selected date range. Every star rating counts, whether or not a comment was left.
2. Average Rating
Simple average of all ratings in the range, on a 1–5 scale. Rounded to two decimal places.
3. # Comments
Number of reviews that included a written comment (not just a star rating). Empty comments and the placeholder "" are excluded.
4. % Redirected
The share of reviewers who were redirected onward to leave a public review (typically Google), as a percentage of all reviews.
How it's calculated: SUM(redirect = true) ÷ COUNT(*). The redirect flag is set on the review record at the moment the redirect happens. A higher number means more of your happy customers are being funnelled into public reviews.
5. Ratings
Horizontal bar chart with one row per star rating (1, 2, 3, 4, 5) showing how many reviews landed at each level. The distribution shape tells you whether you have a "ceiling" (lots of 5s, no 4s — common when the prompt is easy to dismiss with five stars) or a normal spread.
6. Reviews & Avg Rating | Daily
A combo chart: bars are the number of reviews per day, the line on top is the average rating that day.
Reading it: a single bad day jumps out as a dip in the line. A new operational issue (slow service, missed orders) usually shows up here first, days before it becomes a trend.
7. Reviews & Avg Rating | Weekly
Same chart, aggregated by week (Monday start). Better for spotting trends — daily noise smooths out.
8. Reviews & Avg Rating | Monthly
Same chart, by calendar month. Use for longer-term sentiment direction.
9. Reviews | Detail
Every review in the range, newest first. Columns: date, rating, customer name (if left), the comment text, and a tick if the reviewer was redirected to leave a public review. Empty comment cells just mean the diner only rated.
Reading it: scan the comments at the top to catch anything actionable from the last few days. Sort by Rating ascending if you want to see the worst ones first.
How reviews are stored
Source table —
customer_reviews. One row per review.Date field —
created(the timestamp the review was submitted).Outlet attribution — every review is tagged with the outlet where the cheque was paid.
Rating range — 1 to 5, integer values.
Empty comments — the comments KPI and the detail table treat an empty string and the literal placeholder
""as "no comment".Redirect flag — a boolean on the row. It's set when the reviewer is funnelled to a public review platform.
Filters
Outlet — pinned to your outlet when the dashboard is embedded in the Papaya merchant portal.
Date — the range over which to count reviews. Defaults to a recent window.
What this dashboard does NOT show
Public Google / Tripadvisor reviews — only reviews left through Papaya's own checkout prompt are recorded here.
Per-item or per-channel review breakdown — reviews are attached to the cheque as a whole, not to individual items.
Customer profile / repeat-customer linking — reviews are anonymous unless the customer voluntarily entered their name.
Operational metrics that might explain a bad review (service time, errors) — those live in the POS audit log, not here.