New Info on TripAdvisor Algorithm that Drives Popularity Index


Update: April 29 – Please note that Kevin Carter of TripAdvisor has reached out to advise me that some of the information in the French article isn’t totally accurate so please know that some of the factors he mentions below might not be correct. Please also see Kevin’s comment below.

Clients are always asking how TripAdvisor determines the hotel rankings on the TripAdvisor Popularity Index. I have written on the topic before based on information that I have pulled from multiple sources, but I just read an interview (in French) with Guillaume Thevenot, who manages hotel relationships in Northern Europe for TripAdvisor, that provides more detail.

In the article, he includes the following items that affect ranking:

  1. “Freshness” – A recent review will carry more weight than an older review (We knew this.)
  2. Whether other users found reviews about the property ‘helpful’ (Didn’t know this!)
  3. The profile of the review author – Long-standing TripAdvisor members carry more weight (We didn’t know this!)

Very helpful! Now we can add these items to other factors that have been mentioned before, including:

  1. Number of reviews
  2. Quality of reviews (Ratings)
  3. Other content on the Web

Does anyone have more info? Please share below.

3 responses to “New Info on TripAdvisor Algorithm that Drives Popularity Index”

  1. Had a negative review one time and I sent a private message to the guest. In our written exchange he informed me that his stay was from over 2 years ago, although he posted a different date on the actual review. I sent a message to TA to advise them this. The review came down and the guest told me later than he received an email saying his review was removed due to “fraud”…..

  2. The TripAdvisor Popularity Index takes into account the quantity, quality, and recency of TripAdvisor traveler content and of other opinions available on the Web. We would like to clarify, however, that the quote attributed to Mr. Thevenot is not an accurate characterization of the Popularity Index as it is currently designed.
    Kevin Carter

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