G'day, 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 Blue Pools Track.
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.
72 Valid Reviews
The Blue Pools Track experience has a total of 73 reviews. There are 72 valid reviews that are included when calculating the ranking score and 1 invalid review 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.
Below is the distribution of ratings for the 72 valid reviews:
| Rating | Count | Percentage | |
|---|---|---|---|
| 10/10 | 20 |
|
28% |
| 9/10 | 24 |
|
33% |
| 8/10 | 18 |
|
25% |
| 7/10 | 6 |
|
8% |
| 6/10 | 3 |
|
4% |
| 5/10 | 1 |
|
1% |
| 4/10 | 0 |
|
0% |
| 3/10 | 0 |
|
0% |
| 2/10 | 0 |
|
0% |
| 1/10 | 0 |
|
0% |
86.81% Average
The raw data average (mean) for all the Blue Pools Track valid reviews is 86.81% and is based on 72 valid reviews. This value is not used to calculate the ranking score and it only provided here as a comparison to the weighted average.
57 Face-to-Face Reviews
The Rankers team meets with travellers while they’re in New Zealand and conducts face-to-face surveys. These reviews, in our opinion, are the most trusted in the industry and represent a critical control sample. To our knowledge, we are the only travel review website in the world that has gone to this extent.
More about face-to-face reviews
Within the 72 valid reviews, the experience has 57 face-to-face reviews collected during interviews by our team.
Below is the distribution of ratings for the 57 face-to-face reviews:
| Rating | Count | Percentage | |
|---|---|---|---|
| 10/10 | 13 |
|
23% |
| 9/10 | 20 |
|
35% |
| 8/10 | 17 |
|
30% |
| 7/10 | 6 |
|
11% |
| 6/10 | 1 |
|
2% |
| 5/10 | 0 |
|
0% |
| 4/10 | 0 |
|
0% |
| 3/10 | 0 |
|
0% |
| 2/10 | 0 |
|
0% |
| 1/10 | 0 |
|
0% |
86.67% Average
The raw data average (mean) for all the Blue Pools Track face-to-face reviews is 86.67% and is based on 57 face-to-face reviews. This value is not used to calculate the ranking score and it only provided here for comparison purposes.
78.43%
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 |
|---|---|---|---|
| Mike Fricker | 6/10 | 911 days | 100% |
| Lucy | 10/10 | 1520 days | 22% |
| Andrew Hammond | 8/10 | 2585 days | 7% |
| Flatlanders | 5/10 | 2769 days | 5% |
| Katrina | 10/10 | 3223 days | 5% |
| Samantha Brewin | 10/10 | 3265 days | 5% |
| Magdalena | 10/10 | 3574 days | 3% |
| Luuk Kienhorst | 6/10 | 3578 days | 3% |
| Sammy Kerrod | 9/10 | 3580 days | 3% |
| Chris Schmolz | 9/10 | 3585 days | 3% |
| Colin Fisher | 7/10 | 3585 days | 3% |
| Katrina Sedl | 8/10 | 3585 days | 3% |
| Shay | 10/10 | 3742 days | 2% |
| Jaime Alarma Olmos | 8/10 | 3851 days | 2% |
| Kirsten Helsgaun | 8/10 | 3851 days | 2% |
| Valerie Bernardini | 9/10 | 3853 days | 2% |
| Navina | 10/10 | 3853 days | 2% |
| gonzalo caldiz | 9/10 | 3853 days | 2% |
| Juan Viscegle | 7/10 | 3857 days | 2% |
| Sydney Lupton | 7/10 | 3866 days | 2% |
| Mira Huckfield | 9/10 | 3870 days | 2% |
| Lili Souris | 9/10 | 3873 days | 2% |
| Flo Egger | 10/10 | 3875 days | 2% |
| Remi Lopez | 9/10 | 3883 days | 2% |
| Wil Goes | 8/10 | 3889 days | 2% |
| Dorothy | 10/10 | 3894 days | 2% |
| Lisa | 8/10 | 3903 days | 2% |
| Brandon Patton | 10/10 | 3906 days | 2% |
| Ferry and Carlyn | 10/10 | 3909 days | 2% |
| Wayne Brew | 7/10 | 3914 days | 2% |
| Sandy Stamp | 6/10 | 3926 days | 1% |
| Monika Dippel | 8/10 | 3938 days | 2% |
| Sabine | 9/10 | 3938 days | 2% |
| Philipp | 8/10 | 3959 days | 1% |
| Tom Reber | 9/10 | 4064 days | 1% |
| Nina Gottselig | 9/10 | 4276 days | 0% |
| Cora and Franzi | 9/10 | 4311 days | 0% |
| Claudia Hillebrand | 8/10 | 4568 days | 2% |
| Andrea Sole | 7/10 | 4570 days | 2% |
| Sybille Willenbrock | 9/10 | 4617 days | 2% |
| Viola | 8/10 | 4622 days | 2% |
| Anne and Steve Bartlett | 9/10 | 4646 days | 2% |
| Andrea Beck | 10/10 | 4654 days | 2% |
| Claudia | 10/10 | 4657 days | 2% |
| shaynne thompson | 10/10 | 4929 days | 2% |
| Stella Thoben | 10/10 | 4962 days | 2% |
| Justin Leest | 8/10 | 4964 days | 2% |
| Anna Neuenfeldt | 10/10 | 4966 days | 2% |
| Francois Marchar | 10/10 | 4970 days | 2% |
| Mike Edwards | 9/10 | 5035 days | 2% |
| Kevin Desjandino | 10/10 | 5037 days | 2% |
| N Zitscher | 10/10 | 5053 days | 2% |
| James Darren Tennant | 8/10 | 5062 days | 2% |
| Thomas & Ruth Hardmeier | 9/10 | 5342 days | 2% |
| damaca | 9/10 | 5507 days | 2% |
| Margit and Corein Groenevelt | 8/10 | 5677 days | 2% |
| Fredrik Thornell | 9/10 | 5681 days | 2% |
| Ian & Phyllis | 8/10 | 5683 days | 2% |
| Diane Johnston | 8/10 | 5684 days | 2% |
| Fiona Crossley | 9/10 | 5691 days | 2% |
| Robert Smith | 9/10 | 5710 days | 2% |
| Gillian de Vries | 8/10 | 5712 days | 2% |
| Robert Haidt | 8/10 | 5712 days | 2% |
| Leontine van Laar | 9/10 | 5714 days | 2% |
| Quin | 8/10 | 6025 days | 2% |
| Polil | 10/10 | 6042 days | 2% |
| Arnold | 7/10 | 6047 days | 2% |
| Rod C | 9/10 | 6054 days | 2% |
| Trude | 9/10 | 6058 days | 2% |
| Sievers | 9/10 | 6059 days | 2% |
| Jackie | 9/10 | 6075 days | 2% |
| Belinda Godhard | 10/10 | 6081 days | 2% |
No Adjustment
Several adjustments to the weighted average may be added to improve relevancy and credibility. Blue Pools Track does not meet the criteria for any of these adjustments to apply.
3.46% 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 folk 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.
82%
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.