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Will Artificial Intelligence spell the end of the TripAdvisor Model?

Travel and Hotel Reviews…love ‘em or hate ‘em, they’re here to stay. The question just begs to be asked though…just how long will the user-generated model of referrals really last?

TripAdvisoris used as an example in this article because its simply too big and too well established to ignore. However this piece is not aimed at the company (to be perfectly fair, I love TripAdvisor and have used it on many occasions to find and book accommodations in strange and foreign lands). There are various other travel and hotel booking websites, guides and online travel agencies that also incorporate user reviews to add an element of trust and ‘referral credibility’ to their products.

Image Source: Compete Inc. “Consumer Generated Content in Travel” 2007. Not surprisingly, 82% consumers in the survey indicated they trust other consumer opinions over what a hotel had to say about itself. But interestingly enough, even now, less than 70% really trust the information and barely 51% feel that TripAdvisor content is unbiased.

One thing is certain – consumers would trust other consumers over hotel / company marketing departments any day. “Trust” of course, is the key word here. That trust is based on avoiding bias and the faith that the even though you’ve never met the other consumer, there’s a fair chance that there is an element of truth and perhaps even ‘objectivity’ in the review. But what happens when you can no longer trust other consumers? What if those consumers were in fact…no longer consumers…but computers? Artificial Intelligence may just cause the ‘run on the bank’ that brings the house of cards down for online review sites. Here’s a great prediction I received recently from Jeffrey Frankel following a LinkedIN conversation on  previous articles (ref “5 Web trends that will change Hotel Internet Marketing”):

Currently: The numerous hotel review websites with user generated content (especially TripAdvisor) wield an enormous influence on a company’s brand and sales potential. The review and rating systems incorporated into these websites provide potential guests with an immediate impression of the property that sometimes stems from disgruntled guests and even unscrupulous competitors. TripAdvisor’s claim of being able to detect fraudulent reviews is merely a PR front. As a result of a low rating, a hotel’s online distribution channel can be severely weakened.

Within 5 Years: Using some basic data about a property, AI software is able to create thousands of unique and creative reviews in a matter of seconds at little or no cost. The reviews can be designed to be positive to increase a hotel’s ranking or negative to affect a competitor. While this type of software may one day reduce the relevance of user generated reviews for all industries, what does an internet marketing professional do until that time?

Of note, the software I mentioned is not theoretical. One such product, Virtual Storyteller, is already in the lab and I am confident this technology will advance rapidly.

Jeffrey presents a great example of just what we may be heading towards. Of course, the obvious fact is that advanced software AI will never make company blurbs more trustworthy compared to hotel guest reviews on sites like TripAdvisor, however they MAY just cause enough concern that consumers no longer trust online reviews as much as they do today. These developments will certainly require a change in the way we seek guidance in the future. Consumers may revert to tapping into trusted circles only and relying on old-fashioned ‘offline’ advice. Or these concerns could lead to more refined online technologies that integrate segmented social networking, CRM and referral management (Ref: Hotel Referral Marketing – Hotel Guests are a key Distribution Channel of the future).

Other key issues that we desperately need to address include:

  • Verifying identity and bias of reviewers It’s good to have legal restrictions on falsifying reviews, but just HOW do you control them owners and employees who (surprise surprise!) blatantly ignore usage guidelines. Some sites already stipulate that only those who’ve booked and consumed a product, e.g. hotel bookings, through their site are allowed to review that product.
  • Breaking through the clutter – In a presentation about TripAdvisor at the Travel Distribution Summit ‘07, Marc Charron reported that TripAdvisor reviews had grown from about 100,000 (Oct 02) to about 6.7 million (by Oct 06) in a short span of 4 years. Forum posts had reached that number in barely 2.5 years by April 07. There are well over 90,000 posts every week and the most active TripAdvisor member had posted almost 15,600 posts! Not only is this a LOT of information, but you have to question the long term objectivity of frequent posters (where does the urge to help others end and ego take over?). Also, if an individual hotel has over a 1000 reviews, what’s the likelihood that potential bookers can benefit from the wisdom that all those reviewers have to offer, save the most recent you’d be bothered to read plus an average calculated rating? There has to be some way of intelligently organizing the content of all these posts and opinions to make them less clunky, thereby allowing users to examine and probe more efficiently and intuitively based on individual research needs.
  • Relevance and Matching – A young newly married couple going on their first vacation abroad, who’ve gotten a superb full-board package deal from their travel agent and have never stayed in a 5 Star deluxe property may have very different things to say about the same hotel as compared to say, a high-powered frequent-traveller business DINKS (double-income-no-kids) couple travelling on a short beach break to recover from the stresses of work. Plus their future visits to that same hotel may be for entirely different purposes. Review sites and indeed the online consumer review methodology needs considerable refinement in order to capture every element of the demand curve’s long tail and make it more relevant by context and purpose.

These are but a few concerns that travel review and consumer opinion sites have to tackle. I’m sure they’ve been asking themselves the very same questions…after all, only those that find the best answers will survive and thrive in times to come.


6 comments on “Will Artificial Intelligence spell the end of the TripAdvisor Model?

  1. Let me tell you that i am impressed with your blog. I see the link in one site that recomended this blog and it´s a nice a recomendation. Congratulations.
    I have one blog to with travel and hotels.
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  2. Great perspective. I agree that customers would trust fellow customers than the marketing departments of companies any day!


  3. Thanks for the information, it's definitely a big plus for anyone to know!


  4. i like article.


  5. this is great, thanks for posting this.


  6. Relavance and matching is the best thing done by se experts because google gives more weight-age for relavance 


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