Ranking Score Explained

Hey, 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 Te Kauwhata Domain.

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.

Cymen Crick's avatar

Cymen Crick

Rankers Owner

Te Kauwhata Domain

Valid Reviews

70 Valid Reviews

The Te Kauwhata Domain experience has a total of 76 reviews. There are 70 valid reviews that are included when calculating the ranking score and 6 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.

Below is the distribution of ratings for the 70 valid reviews:

Rating Count Percentage
10/10 30
43%
9/10 16
23%
8/10 16
23%
7/10 4
6%
6/10 1
1%
5/10 2
3%
4/10 0
0%
3/10 0
0%
2/10 0
0%
1/10 1
1%

88.14% Average

The raw data average (mean) for all the Te Kauwhata Domain valid reviews is 88.14% and is based on 70 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

88.60%

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
Martin 10/10 49 days 100%
Marie 10/10 110 days 99%
Ella 10/10 141 days 99%
Toni 10/10 171 days 98%
Mladen Savov 10/10 414 days 90%
Angie Johnson 9/10 414 days 89%
Cam an 5/10 445 days 67%
Ro 7/10 445 days 82%
rae 9/10 475 days 86%
Krys 9/10 475 days 86%
Cucamest 10/10 506 days 85%
Millie 9/10 536 days 83%
Jill 8/10 659 days 73%
Guest 9/10 689 days 72%
Nadja 10/10 780 days 65%
Dee 7/10 811 days 57%
Brie 6/10 811 days 53%
Ruta 1/10 841 days 23%
Malcolm Greenhalgh 8/10 872 days 55%
Jan 8/10 872 days 55%
Sara 8/10 933 days 49%
Bobbie 10/10 964 days 46%
Christa 10/10 1025 days 40%
wvdbos 8/10 1055 days 37%
sarah penney 9/10 1055 days 37%
Steve Hawes 10/10 1086 days 35%
Camila 10/10 1086 days 35%
Joakim 8/10 1114 days 32%
Anya 10/10 1114 days 33%
Odette 10/10 1114 days 33%
Caroline 9/10 1114 days 32%
Kate 9/10 1145 days 30%
Adrian 10/10 1145 days 30%
Geri Ng 10/10 1176 days 28%
Emily 8/10 1206 days 25%
Dave 10/10 1237 days 23%
Laura Jarry 8/10 1237 days 23%
Chloe 8/10 1329 days 17%
Eyisha 7/10 1359 days 15%
Jose 10/10 1451 days 11%
Emma 9/10 1451 days 11%
Lucy 10/10 1510 days 9%
Joe 10/10 1510 days 9%
Roque 10/10 1844 days 3%
Aj 10/10 1936 days 3%
Shannon 10/10 1967 days 3%
Karen 9/10 1997 days 3%
Stefan Hohmann 10/10 2181 days 3%
Merche 9/10 2210 days 2%
Silly American 10/10 2241 days 2%
Gap year 10/10 2272 days 2%
Christina 8/10 2272 days 2%
Jun 9/10 2302 days 2%
Lisa 9/10 2302 days 2%
Bartezz 8/10 2302 days 2%
Ancient Uncle 10/10 2333 days 2%
Marty 8/10 2363 days 2%
Johannes 8/10 2547 days 2%
Georgia Trompf 9/10 2606 days 2%
Trudy Worboys 10/10 2606 days 2%
Liv 10/10 2637 days 2%
The Flip Flop Family 10/10 2727 days 1%
CHA LEMAY 9/10 2881 days 1%
Fivetogether 9/10 2912 days 1%
Muhammad fayadh Mad jamil 8/10 2939 days 1%
Flavia Confalonieri 7/10 3014 days 1%
Lucy Winfield 5/10 3138 days 0%
Nathan Lal 8/10 3144 days 1%
Lucile Gendre 8/10 3234 days 0%
Christine Allgaier 10/10 3287 days 0%

Adjustments

No Adjustment

Several adjustments to the weighted average may be added to improve relevancy and credibility. Te Kauwhata Domain does not meet the criteria for any of these adjustments to apply.

Balancing Adjustment

1.20% 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.

Final Ranking Score

90%

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.