One number per venue, built only from its Google reviews, part of the more than 1.7 million public reviews we read across Melbourne. We detect and remove fake five-star reviews, average what's left, then pull thin-sample scores toward the review-weighted average across all scored venues, so a near-perfect score from only a handful of reviews is pulled down toward that average. No recency weighting, no paid inputs. No restaurant pays to move it. Here's exactly how it works.
Step 1 · De-faked average. Take the Google reviews we've stored for the venue (up to 500 per venue per import), remove the ones our fake-detection flags as suspicious five-star reviews, and average the star ratings that remain.
Step 2 · Downward-only volume weighting. Blend that average with the review-weighted average across all scored venues, using a prior worth about 25 reviews against the venue's full Google review count, and keep whichever is lower. A venue with thousands of reviews keeps its own average; a high average from only a handful of reviews is pulled down toward the all-venue average. Volume can only lower a thin-sample score, never inflate it.
That final number is the Curateria Score. A venue with only a handful of valid reviews (under ten) is scored with low confidence. A venue we haven't scored yet shows its Google rating as the Curateria Score until we do.
The score is built from a venue's Google reviews. Before averaging, we run fake-review detection and exclude reviews flagged as fake (it targets suspicious five-star reviews and considers each reviewer's own review history). The remaining star ratings are averaged into a de-faked mean.
We then apply downward-only volume weighting: the de-faked mean is blended with the review-weighted average across all scored venues, using a prior worth about 25 reviews against the venue's full Google review count, and we keep whichever is lower. This stops a near-perfect score built on a handful of reviews from outranking a strong, heavily-reviewed venue. It can only ever lower a thin-sample score, never lift it.
That is the entire calculation. The score is not weighted by review recency, is not adjusted for individual reviewer history, and does not fold in Instagram, Reddit, menu prices or a paid tier. Any of those, if we add them later, will be documented here first. A venue we haven't scored yet simply shows its Google rating until we do.
Every score is recomputed from the Google reviews we've stored for the venue (up to 500 per venue per import), with the volume weighting read against the venue's full Google review count. We don't hand-tune individual scores, and no restaurant pays (directly or indirectly) to move their number.
Venues may pay for Sponsored positions in Discover search results. Those positions are always labelled Sponsored and sit separately from the merit-ranked list. Sponsored positions are the only way a venue can pay for position in results; display ads and affiliate links are always labelled too. None of them ever change a Curateria Score, a curated list, or the merit order of search results. (Paid partners can also show a Verified or Premium Partner badge, which likewise never moves the score or the ranking.)
When a restaurant is verified by venue (claimed by the actual operator), their listing gets a chip and a few partner-only surfaces. Their score is unaffected. The chip exists so diners know who's answering the comments, not to bias the math.
Sample size matters: a venue with only a handful of valid reviews (under ten) is scored with low confidence, and the volume weighting keeps a thin-sample score from outranking a well-reviewed one. We'd rather be honest about thin data than fake a confident number.
It's an aggregate signal across a venue's reviewers. A 4.7 means that across the Google reviews we read, this restaurant has a high average rating once fake reviews were removed. It does not mean you, on a Tuesday, in a bad mood, will love it. Personal taste is personal.
It's not influenced by partners. Restaurants who claim their listing get tools to respond to reviews and update their hours. Claiming a listing does not buy a higher score or a better rank in any list. The wall between the editorial product and the partner product is the whole point of the brand.
Filter by suburb, cuisine, vibe, or score. Scores are built the way this page describes; a venue we haven't scored yet shows its Google rating until we do.