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 Touchdown Car Rentals.
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.
Touchdown Car Rentals
Valid Reviews
43 Valid Reviews
The Touchdown Car Rentals experience has a total of 45 reviews. There are 43 valid reviews that are included when calculating the ranking score and 2 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 43 valid reviews:
| Rating | Count | Percentage | |
|---|---|---|---|
| 10/10 | 41 |
|
95% |
| 9/10 | 2 |
|
5% |
| 8/10 | 0 |
|
0% |
| 7/10 | 0 |
|
0% |
| 6/10 | 0 |
|
0% |
| 5/10 | 0 |
|
0% |
| 4/10 | 0 |
|
0% |
| 3/10 | 0 |
|
0% |
| 2/10 | 0 |
|
0% |
| 1/10 | 0 |
|
0% |
99.53% Average
The raw data average (mean) for all the Touchdown Car Rentals valid reviews is 99.53% and is based on 43 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
99.87%
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 |
|---|---|---|---|
| KOH KL | 10/10 | 25 days | 100% |
| Kerrie | 10/10 | 116 days | 99% |
| Daniel | 10/10 | 300 days | 95% |
| Rick Kothari | 10/10 | 756 days | 67% |
| Gregor Potts | 10/10 | 1790 days | 5% |
| Danny.T | 10/10 | 1974 days | 5% |
| Tracey Feldcamp | 10/10 | 2005 days | 5% |
| Nicholas Thompson | 10/10 | 2096 days | 4% |
| Alex | 10/10 | 2155 days | 4% |
| Diana, Pittsburgh PA, USA | 10/10 | 2247 days | 4% |
| Kathy Probets | 9/10 | 2461 days | 4% |
| Michael Teasdale | 10/10 | 2673 days | 3% |
| Nick G | 10/10 | 2704 days | 3% |
| Tamsin Wilkins | 10/10 | 2735 days | 3% |
| Mike David | 10/10 | 2765 days | 3% |
| Kevin O'Neill | 10/10 | 2947 days | 3% |
| George Lucas | 10/10 | 3100 days | 3% |
| Campbell Gibson | 10/10 | 3130 days | 2% |
| Liam Glubb | 10/10 | 3191 days | 2% |
| Hani Girgis | 10/10 | 3191 days | 2% |
| Christian Cunneen | 10/10 | 3282 days | 2% |
| enthusejohn | 9/10 | 3282 days | 2% |
| andy jamieson | 10/10 | 3374 days | 2% |
| Grace Hopkins | 10/10 | 3404 days | 2% |
| Tiffany Boa | 10/10 | 3435 days | 2% |
| Paul McNamara | 10/10 | 3466 days | 2% |
| Caroline Griffin | 10/10 | 3466 days | 2% |
| Craig Richmond | 10/10 | 3616 days | 1% |
| Pete Robson | 10/10 | 3616 days | 1% |
| Murray Quartly | 10/10 | 3647 days | 1% |
| M Factor Events | 10/10 | 3708 days | 1% |
| Rupert Deans | 10/10 | 3831 days | 1% |
| Laura Alleway | 10/10 | 3861 days | 1% |
| Sue Seeley | 10/10 | 3953 days | 1% |
| Tony Gloag | 10/10 | 3953 days | 1% |
| Anna Jenkins | 10/10 | 3981 days | 1% |
| Shane Farrell | 10/10 | 4012 days | 1% |
| Simon Adams | 10/10 | 4104 days | 1% |
| Catherine Forsey | 10/10 | 4134 days | 0% |
| Maree Harris | 10/10 | 4134 days | 0% |
| Tim | 10/10 | 4196 days | 0% |
| Regan Tullett | 10/10 | 4226 days | 0% |
| Logan McMillan | 10/10 | 4377 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 Touchdown Car Rentals experience has plenty of reviews and does not meet the criteria for any adjustment.
Recent Reviews Adjustment
-2.71% Adjustment
Recent reviews reflect the experience as it currently operates. This means it's important to get fresh reviews. Some experiences discovered they could get a few good reviews and then, resting on their laurels, discourage any further reviews. This adjustment stimulates experiences to be positively involved in the review generating process and discourages them from manipulating the ranking system in this manner.
What constitutes a recent review is based on the how old it is, what type of experience it is applied to and and what time of year it currently is. Due to the seasonal nature of many businesses, what is considered recent is dynamically adjusted throughout the year.
There may be an adjustment if this experience hasn't received enough reviews within the last 41 days. The Touchdown Car Rentals experience has 1 recent ranking. Adjustments are according to the following table:
| Recent Reviews | Adjustment |
|---|---|
| 0 | -3.00% |
| 1 | -2.63% |
| 2 | -1.50% |
| 3 | -0.38% |
| 4 | -0.00% |
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 Touchdown Car Rentals experience has been adjusted for 4 days. Adjustments are according to the following table.
| Days | Adjustment |
|---|---|
| … | … |
| 1 | -0.02% |
| 2 | -0.04% |
| 3 | -0.06% |
| 4 | -0.08% |
| 5 | -0.10% |
| 6 | -0.12% |
| 7 | -0.14% |
| … | … |
Balancing Adjustment
0.24% 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
96%
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.