Hi, thanks for your interest in how we calculate an experience's ranking score. It's at the core of Rankers so I'm pleased you're curious.
The ranking score percentage is used to compare and sort experiences in ranking tables. It is not necessarily a direct measurement of the quality of a particular experience as rated by its customers. I've found it a useful tool to allow me to find the best experiences with confidence. But I've also found it important to read the customer reviews before making any final judgements!
We calculate an experience's ranking score using a multi-factor data model instead of a raw data average (mean). This model takes into account several important questions. For instance - is there a trusted body of reviews? What is the age of a review and is the review from a credible source?
Below you'll find details around some of the important factors that went into calculating the ranking score for Orange Sheep.
If you have any questions or comments about our ranking score calculation please get in touch at info@rankers.co.nz. We don't believe this is perfect or complete so we're always interested in ways we might make improvements.
Orange Sheep
Valid Reviews
122 Valid Reviews
The Orange Sheep experience has a total of 132 reviews. There are 122 valid reviews that are included when calculating the ranking score and 10 invalid reviews that are excluded from the calculation. Reviews can be excluded only when a reviewer is not verified or after an investigation by our team determines the reviewer is not genuine.
Within these 122 valid reviews, the experience has 1 face-to-face review collected during interviews by our team.
Below is the distribution of ratings for the 122 valid reviews:
| Rating | Count | Percentage | |
|---|---|---|---|
| 10/10 | 36 |
|
30% |
| 9/10 | 28 |
|
23% |
| 8/10 | 15 |
|
12% |
| 7/10 | 16 |
|
13% |
| 6/10 | 6 |
|
5% |
| 5/10 | 9 |
|
7% |
| 4/10 | 2 |
|
2% |
| 3/10 | 4 |
|
3% |
| 2/10 | 1 |
|
1% |
| 1/10 | 5 |
|
4% |
78.03% Average
The raw data average (mean) for all the Orange Sheep valid reviews is 78.03% and is based on 122 valid reviews. This value is not used to calculate the ranking score and it only provided here as a comparison to the weighted average.
Weighted Average
84.75%
Rankers calculates a weighted mean as a base average on which we can improve. Individual review's ratings are given a weight based on several factors. The weight of a review determines the overall impact it'll have on the final weighted average.
Recent reviews have more weight as they are more relevant and reflect the experience as it currently operates. Over time reviews become less relevant and loose their impact on the ranking score.
Low rating reviews carry slightly less weight. This dampens the effect of very low ratings for every experience across the board. This is especially important when the experience has few reviews overall and a single negative rating can grossly mischaracterise an experience. Consistent poor reviews will still result in the experience receiving a comparitively low ranking score.
Credible sources provide reviews that can be trusted. If we have verified a reviewer is genuine via a face-to-face meeting then the review carries additional weight.
| Reviewer | Rating | Age | Relative Weight |
|---|---|---|---|
| Daniel Gleeson. | 10/10 | 70 days | 100% |
| Jan | 8/10 | 131 days | 97% |
| Westysdownunder | 9/10 | 131 days | 98% |
| Martin | 9/10 | 190 days | 97% |
| Mireille & Philippe | 7/10 | 221 days | 91% |
| Sol | 10/10 | 221 days | 97% |
| Matt Minter | 1/10 | 221 days | 39% |
| Richard Bennett | 9/10 | 251 days | 96% |
| Mark Jenkison | 5/10 | 251 days | 74% |
| Hugo ELIE | 10/10 | 282 days | 96% |
| Chelsea 🌸 | 10/10 | 282 days | 96% |
| Bella | 10/10 | 282 days | 96% |
| Rory M | 8/10 | 282 days | 94% |
| Eline | 8/10 | 465 days | 86% |
| Cassie | 10/10 | 465 days | 88% |
| Nick | 6/10 | 496 days | 74% |
| Lucy | 9/10 | 496 days | 85% |
| Viktoria | 9/10 | 496 days | 85% |
| Arlene | 10/10 | 524 days | 84% |
| Alan | 3/10 | 524 days | 46% |
| Dhanu | 7/10 | 555 days | 77% |
| Xavier | 8/10 | 555 days | 81% |
| Fredrik | 10/10 | 555 days | 83% |
| Dora | 10/10 | 555 days | 83% |
| Ellen | 10/10 | 586 days | 80% |
| Sinead | 9/10 | 586 days | 80% |
| Emily | 8/10 | 586 days | 79% |
| Elena Martin | 9/10 | 586 days | 80% |
| Barry | 5/10 | 616 days | 60% |
| Ellie | 9/10 | 647 days | 75% |
| Laura | 9/10 | 677 days | 73% |
| Unhappy camper | 5/10 | 830 days | 46% |
| Leonie | 9/10 | 861 days | 57% |
| Nigel Rawlings | 6/10 | 890 days | 47% |
| Steph | 10/10 | 921 days | 51% |
| Reb | 3/10 | 921 days | 28% |
| Jane | 10/10 | 921 days | 51% |
| Sina Goetzfried | 10/10 | 952 days | 48% |
| Sophie Moore - Tauranga New Zealand | 10/10 | 982 days | 45% |
| Larissa | 7/10 | 982 days | 42% |
| Victoria | 6/10 | 1013 days | 36% |
| Ayla | 10/10 | 1013 days | 42% |
| Cholly | 9/10 | 1013 days | 42% |
| Nita | 9/10 | 1043 days | 39% |
| Dylan | 7/10 | 1074 days | 34% |
| Rambo23 | 10/10 | 1166 days | 29% |
| Donna | 10/10 | 1166 days | 29% |
| Taylor Russell | 8/10 | 1166 days | 29% |
| Whitney | 9/10 | 1196 days | 27% |
| Charlie | 10/10 | 1196 days | 27% |
| Travel | 1/10 | 1227 days | 10% |
| Katie Edser | 8/10 | 1227 days | 24% |
| Emmy | 10/10 | 1227 days | 25% |
| Giovanna Sedglach | 10/10 | 1227 days | 25% |
| E&P | 7/10 | 1255 days | 21% |
| Vish | 8/10 | 1286 days | 21% |
| Stacey & Mike | 9/10 | 1286 days | 21% |
| Kendra | 10/10 | 1317 days | 19% |
| Hanna | 6/10 | 1317 days | 16% |
| Sophie | 10/10 | 1317 days | 19% |
| Janice | 9/10 | 1317 days | 19% |
| Didde | 9/10 | 1317 days | 19% |
| Mckenzie Galbraith | 8/10 | 1317 days | 19% |
| Becky | 10/10 | 1347 days | 17% |
| Caolan Harvey | 6/10 | 1347 days | 15% |
| Mil | 9/10 | 1347 days | 17% |
| BelgianHobbit | 10/10 | 1347 days | 17% |
| Liz | 10/10 | 1500 days | 10% |
| Hannah | 5/10 | 1561 days | 6% |
| James | 8/10 | 1592 days | 7% |
| Annelies Geerts | 10/10 | 1592 days | 7% |
| Brigit Pratt | 7/10 | 1620 days | 6% |
| Maddi | 10/10 | 1651 days | 6% |
| Erna | 7/10 | 1743 days | 4% |
| Ryan | 10/10 | 1865 days | 4% |
| Thomas neil | 9/10 | 1957 days | 4% |
| Laura | 5/10 | 1985 days | 3% |
| Kirsty B | 10/10 | 1985 days | 4% |
| Amber | 9/10 | 1985 days | 4% |
| Alydia | 9/10 | 1985 days | 4% |
| Dan | 9/10 | 2077 days | 4% |
| Abi | 7/10 | 2108 days | 3% |
| Justine | 9/10 | 2138 days | 4% |
| Justine | 10/10 | 2230 days | 4% |
| Sven Huber | 6/10 | 2322 days | 3% |
| John Heather | 10/10 | 2322 days | 3% |
| Grant | 3/10 | 2322 days | 1% |
| Thangs | 8/10 | 2322 days | 3% |
| Aggie | 10/10 | 2351 days | 3% |
| Jason Furness | 10/10 | 2351 days | 3% |
| Sophie Winter | 10/10 | 2351 days | 3% |
| Howie | 7/10 | 2351 days | 3% |
| Amanda | 7/10 | 2382 days | 3% |
| Noreen | 7/10 | 2382 days | 3% |
| Sabine | 9/10 | 2382 days | 3% |
| Fran | 4/10 | 2413 days | 2% |
| Lucie | 10/10 | 2443 days | 3% |
| Sarah | 9/10 | 2474 days | 3% |
| Libby | 8/10 | 2474 days | 3% |
| JirkaR | 8/10 | 2688 days | 3% |
| Clara | 9/10 | 2688 days | 3% |
| Travelgirl | 8/10 | 2716 days | 2% |
| Joe | 7/10 | 2747 days | 2% |
| Enjoy | 9/10 | 2747 days | 2% |
| Bart | 1/10 | 2747 days | 1% |
| Maureen Barlow | 2/10 | 3039 days | 0% |
| Laura Clay | 8/10 | 3053 days | 2% |
| Leong Mee Yee | 5/10 | 3114 days | 1% |
| Roberto Pascucci | 4/10 | 3114 days | 1% |
| Karen Scott | 5/10 | 3151 days | 1% |
| Chris Nugent | 7/10 | 3348 days | 1% |
| Chanelle Weller | 5/10 | 3376 days | 1% |
| Lynda Mauro | 1/10 | 3477 days | 0% |
| Sally Roach | 1/10 | 3477 days | 0% |
| Ina and Max | 7/10 | 3490 days | 0% |
| Becky and James | 3/10 | 3578 days | 0% |
| Erin Stafferton | 5/10 | 3667 days | 0% |
| Crystal Ritchie | 9/10 | 3713 days | 1% |
| Russell Opland | 9/10 | 3731 days | 1% |
| Heng Sing Teh | 7/10 | 3757 days | 0% |
| Helena Bond | 7/10 | 3788 days | 0% |
| Tony Geary | 10/10 | 3794 days | 0% |
Adjustments
Several adjustments to the weighted average are added to improve relevancy and credibility. These adjustments apply equally to all experiences that meet the criteria.
Sample Size Adjustment
No Adjustment
A reasonable number of reviews are necessary in order for the average to be credible and for an experience to take a prime position within the ranking tables. As such, experiences with only a few reviews have a moderated score. This does not mean that the experience or the reviews can't be trusted. The Orange Sheep experience has plenty of reviews and does not meet the criteria for any adjustment.
Recent Reviews Adjustment
-0.43% Adjustment
There may be an adjustment if this experience hasn't received any reviews within the last 125 days. However the Orange Sheep experience does not meet the criteria for any adjustment.
In addition, an experience's ranking score may be adjusted for each day there is no new ranking. After 1 day the adjustment comes into effect. The maximum number of days that can be adjusted for is 200 days. Due to the seasonal nature of many businesses, this adjustment is applied dynamically throughout the year.
The Orange Sheep experience has been adjusted for 43 days. Adjustments are according to the following table.
| Days | Adjustment |
|---|---|
| … | … |
| 40 | -0.40% |
| 41 | -0.41% |
| 42 | -0.42% |
| 43 | -0.43% |
| 44 | -0.44% |
| 45 | -0.45% |
| 46 | -0.46% |
| … | … |
Balancing Adjustment
1.96% Adjustment
Every experience's review score is adjusted to balance out the disproportional number of negative reviews that are contributed.
You won't be surprised to learn that disgruntled customers are more likely to leave a review than happy ones. They are motivated to share their experience and warn others. We consider this a good thing and it's why reading the reviews is important. However we've learned it can misrepresent the experience in a more overall sense.
We apply a balancing adjustment to counteract this effect and ensure the ranking score is a more fair representation of the experience. This adjustment is applied equally to all experiences.
Final Ranking Score
86%
The final ranking score once any adjustments, ratings, and rounding has been applied. This value is recalculated each day and a short rolling average is applied. Therefore it may not be precisely accurate based on the other values presented.