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 firstname.lastname@example.org. We don't believe this is perfect or complete so we're always interested in ways we might make improvements.
75 Valid Reviews
The Lumsden Information Centre experience has a total of 79 reviews. There are 75 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 75 valid reviews, the experience has 3 face-to-face reviews collected during interviews by our team.
Below is the distribution of ratings for the 75 valid reviews:
The raw data average (mean) for all the Lumsden Information Centre valid reviews is 91.07% and is based on 75 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.
|Teesh K||10/10||27 days||99.88||100%|
|Kate in NZ||10/10||150 days||96.43||96%|
|Jane Lawrence||9/10||301 days||85.64||85%|
|Anni Heltti||10/10||415 days||72.71||72%|
|Tania Baird||9/10||454 days||67.34||66%|
|Keith & Kay Finlayson||10/10||485 days||62.73||61%|
|Kathryn Torkington||1/10||638 days||27.81||25%|
|Megan Belanger||10/10||666 days||34.16||32%|
|Boris Clémençon||10/10||697 days||30.1||28%|
|Jonas R.||10/10||789 days||19.84||17%|
|Katharina Pisarew||9/10||1037 days||5.53||2%|
|Luis Vigil Vidal||10/10||1045 days||5.4||2%|
|Dennis Hesse||10/10||1049 days||5.34||2%|
|Tori De||1/10||1062 days||3.78||0%|
|Marketa Weisserová||10/10||1075 days||5.06||2%|
|Yanzhi Cheng||10/10||1137 days||4.92||1%|
|Joe Trigg||9/10||1141 days||4.91||1%|
|Jenny Jaye||10/10||1157 days||4.88||1%|
|Victoria Smith||10/10||1208 days||4.78||1%|
|Poppy Ritchie||10/10||1237 days||4.72||1%|
|Judy Aspinall||9/10||1322 days||4.56||1%|
|Rosanna Leeming||7/10||1383 days||4.04||0%|
|Matt Downey||7/10||1394 days||4.02||0%|
|Frankie Winsor||9/10||1410 days||4.38||1%|
|Lisa Al Agam||10/10||1422 days||4.36||1%|
|Thomas Jan Geelen||6/10||1436 days||3.6||0%|
|Audrey Zarlenga||10/10||1467 days||4.27||1%|
|Theo Mallais||10/10||1509 days||4.19||1%|
|Puneet Mishra||10/10||1512 days||4.18||1%|
|Derek Drost||7/10||1523 days||3.79||0%|
|Simon Liehout||9/10||1548 days||4.11||1%|
|Philippa Buchanan||9/10||1604 days||4.0||0%|
|Rita Ashby||8/10||1640 days||3.74||0%|
|Connie Hopper||9/10||1683 days||3.85||0%|
|Tatiana Rochereau||9/10||1692 days||3.83||0%|
|Andre Evers||9/10||1695 days||3.83||0%|
|David Elliott||8/10||1701 days||3.62||0%|
|Bernadette Arnet||9/10||1739 days||3.74||0%|
|Zdenda Barvinek||9/10||1785 days||3.65||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 email@example.com.