Hi there, 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 Lumsden Information Centre.
If you have any questions or comments about our ranking score calculation please get in touch at email@example.com. We don't believe this is perfect or complete so we're always interested in ways we might make improvements.
72 Valid Reviews
The Lumsden Information Centre experience has a total of 76 reviews. There are 72 valid reviews that are included when calculating the ranking score and 4 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 72 valid reviews, the experience has 3 face-to-face reviews collected during interviews by our team.
Below is the distribution of ratings for the 72 valid reviews:
The raw data average (mean) for all the Lumsden Information Centre valid reviews is 90.69% 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.
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.
|Kate in NZ||10/10||44 days||99.69||100%|
|Jane Lawrence||9/10||195 days||93.97||94%|
|Anni Heltti||10/10||309 days||84.87||85%|
|Tania Baird||9/10||348 days||80.81||80%|
|Keith & Kay Finlayson||10/10||379 days||77.24||77%|
|Kathryn Torkington||1/10||532 days||40.26||38%|
|Megan Belanger||10/10||560 days||50.36||49%|
|Boris Clémençon||10/10||591 days||45.25||43%|
|Jonas R.||10/10||683 days||31.9||29%|
|Katharina Pisarew||9/10||931 days||9.26||6%|
|Luis Vigil Vidal||10/10||939 days||8.86||5%|
|Dennis Hesse||10/10||943 days||8.66||5%|
|Tori De||1/10||956 days||5.88||2%|
|Marketa Weisserová||10/10||969 days||7.52||4%|
|Yanzhi Cheng||10/10||1031 days||5.65||2%|
|Joe Trigg||9/10||1035 days||5.57||2%|
|Jenny Jaye||10/10||1051 days||5.31||2%|
|Victoria Smith||10/10||1102 days||4.99||1%|
|Poppy Ritchie||10/10||1131 days||4.93||1%|
|Judy Aspinall||9/10||1216 days||4.76||1%|
|Rosanna Leeming||7/10||1277 days||4.23||0%|
|Matt Downey||7/10||1288 days||4.21||0%|
|Frankie Winsor||9/10||1304 days||4.59||1%|
|Lisa Al Agam||10/10||1316 days||4.57||1%|
|Thomas Jan Geelen||6/10||1330 days||3.77||0%|
|Audrey Zarlenga||10/10||1361 days||4.48||1%|
|Theo Mallais||10/10||1403 days||4.4||1%|
|Puneet Mishra||10/10||1406 days||4.39||1%|
|Derek Drost||7/10||1417 days||3.98||0%|
|Simon Liehout||9/10||1443 days||4.32||1%|
|Philippa Buchanan||9/10||1498 days||4.21||0%|
|Rita Ashby||8/10||1535 days||3.93||0%|
|Connie Hopper||9/10||1577 days||4.06||0%|
|Tatiana Rochereau||9/10||1586 days||4.04||0%|
|Andre Evers||9/10||1589 days||4.03||0%|
|David Elliott||8/10||1596 days||3.82||0%|
|Bernadette Arnet||9/10||1633 days||3.95||0%|
|Zdenda Barvinek||9/10||1679 days||3.86||0%|
Several adjustments to the weighted average may be added to improve relevancy and credibility. Lumsden Information Centre does not meet the criteria for any of these adjustments to apply.
The final ranking score once rounding has been applied. This value is cached and recalculated each day. Therefore it may not be precisely accurate based on the other values presented.
If you have any questions or comments about our ranking score calculation please get in touch at firstname.lastname@example.org.