Half of Superhosts are one bad review from losing it
Plenty of people have counted how many Airbnb listings sit above 4.8. Nobody publishes the number that actually matters to a host: how many of those are clinging on by a single review. We measured it across 51,484 listings in the UK and Ireland.
of listings clearing the 4.8 Superhost line would fall below it
after one 1-star review
Put the other way round: of every two hosts who currently meet the rating requirement, one is a single bad stay from not meeting it. Widen the question to two bad reviews and the figure reaches 72.8%.
What we measured
Every listing in five UK and Ireland cities with at least 10 reviews, which is the review floor Airbnb itself applies to Superhost. That leaves 51,484 listings. For each one we reconstructed the total number of stars awarded from the displayed rating and review count, then solved exactly how many 1-star reviews it could absorb before its average dropped below 4.8.
That last step is the part usually skipped. "Percentage above 4.8" is easy and tells a host nothing about their own risk. The buffer is the number they can act on.
| City | Listings | Above 4.8 | Zero buffer | Median buffer |
|---|---|---|---|---|
| London | 37,772 | 52.5% | 56.0% | 0 |
| Edinburgh | 4,567 | 63.8% | 28.8% | 2 |
| Greater Manchester | 3,444 | 54.8% | 45.8% | 1 |
| Bristol | 1,805 | 63.2% | 40.3% | 1 |
| Dublin | 3,896 | 56.1% | 43.0% | 1 |
| All five | 51,484 | 54.3% | 50.8% | — |
"Zero buffer" is the share of listings already above 4.8 that one 1-star review would push under. "Median buffer" is how many 1-star reviews the typical qualifying listing in that city could absorb.
London is both the hardest and the most fragile
London has the lowest share of listings clearing 4.8, at 52.5%, and the highest share of those sitting on zero buffer, at 56.0%. Its median qualifying listing has no margin at all. Edinburgh is the mirror image: 63.8% clear the line and only 28.8% of them are one review from losing it, with a median buffer of two.
The likeliest explanation is review volume rather than hospitality. A listing with 300 reviews can absorb several bad ones; a listing with 15 cannot. Dense, high-turnover markets have many newer listings with thin review counts, and thin review counts are what make a rating brittle.
Why 4.8 is so unforgiving
The threshold sits near the ceiling of the scale, and that asymmetry does the damage. A 5-star review lands only 0.2 above the line. A 1-star review lands 3.8 below it. One bad review therefore carries nineteen times the weight of a good one, and no amount of goodwill changes the arithmetic.
This is also why "just get more 5-star reviews" is weak advice. Recovering from a single 1-star review at 4.8 takes nineteen perfect stays. At 4.9, for Guest Favorite, it takes thirty-nine.
Your own number. Enter your rating and review count below and you will see your exact buffer, or exactly how many 5-star stays stand between you and 4.8.
The other end of the distribution
45.7% of listings sit below 4.8. Most are a long way off, but 2,915 of them, 12.4% of those below the line, are within five consecutive 5-star reviews of reaching it. For a listing taking regular bookings that is weeks of work, not months, and it is the group for whom the next quarterly assessment is genuinely winnable.
At the top, 32.0% of all listings measured sit at 4.9 or above, which is the entry condition for Guest Favorite. Entry condition, not guarantee: that badge also weighs category ratings, cancellations and how a listing compares with similar ones nearby.
Method, in full
Source data is Inside Airbnb, used under a Creative Commons Attribution 4.0 licence. We used the June 2026 snapshots for London, Edinburgh, Greater Manchester, Bristol and Dublin, taking two fields per listing: the overall review score and the number of reviews.
A displayed rating is rounded, so the true total of stars awarded sits in an interval rather than at a point. We take the nearest whole star-sum consistent with the displayed rating and review count, then solve the closed form for how many 1-star reviews keep the mean at or above the threshold. No simulation is involved and the result is exact for a given star-sum. The same code runs inside our own rating calculator, so the study and the tool cannot disagree.
What this study cannot tell you
These are all-time ratings. Airbnb assesses Superhost on the trailing 12 months, which the public data does not break down by star. For a host whose recent reviews match their history the two figures agree. For one who has improved, or slipped, they do not. Every figure here should be read as "the rating guests see", not "the figure Airbnb will assess".
Rating is one of four requirements. Superhost also needs a 90% response rate, under 1% cancellations and 10 completed stays. We can see the rating and the review count, so "clears 4.8" is not the same as "is a Superhost".
Snapshots, not live data. Everything here is from June 2026 and five cities. It describes those markets at that moment, not Airbnb globally.
Frequently asked questions
How many Airbnb listings have a 4.8 rating or higher?
Across 51,484 UK and Ireland listings with at least 10 reviews, 54.3% had an all-time rating of 4.8 or above. Roughly a third, 32.0%, were at 4.9 or above, which is the Guest Favorite line.
What does it mean to have zero buffer on Airbnb?
Your buffer is the number of 1-star reviews you could receive before your average falls below the threshold. A buffer of zero means a single 1-star review takes you under 4.8. It is not the same as being close to 4.8: a listing at 4.81 with few reviews and a listing at 4.85 with slightly more can both have zero buffer.
Why is the 4.8 Superhost threshold so fragile?
Because it sits near the top of the scale. A 5-star review lands only 0.2 above the line while a 1-star review lands 3.8 below it, so one bad review has nineteen times the pull of a good one. The higher the threshold, the less headroom each new review buys.
Does this use the same rating Airbnb assesses Superhost on?
No, and that is the study's main limitation. The public data carries the all-time rating, while Airbnb assesses Superhost on the trailing 12 months. For a host whose recent reviews match their history the two agree; for one who has improved or slipped, they do not.
Reusing this
The figures are free to quote with a link back to this page. If you want a city we have not covered, or a cut we have not published, get in touch and we will run it. The underlying source data is public and the method is described above in enough detail to reproduce.
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