Crowdsourcing is defined as the process of obtaining needed services, ideas, or content by soliciting contributions from a large group of people, specifically from an online community, rather than from traditional employees or suppliers. TripAdvisor, a Boston metro area based giant is doing exactly that and capitalizing on customer reviews and tips provided by the general public.<\/p>\n
Nowadays TripAdvisor takes pride in being the largest travel community in the world, reaching 375 million unique monthly visitors. On the base of the data and reviews that were gathered since February 2000 TripAdvisor developed models for monetization and now offers \u201c\u00a0a wide variety of travel choices and planning features with seamless links to booking tools that check hundreds of websites to find the best hotel prices\u201d. None of their current successes (IPO, revenues, etc.) would have been possible without the crowd knowledge.<\/p>\n
So how did they convince the crowds to share their experience and review on their website? At the beginning TripAdvisor gathered information from guide books, newspapers and magazines. On the top of the page they had a big button saying \u201cVisitors add your own review\u201d. Apparently customers like to have an outlet for their views, complains, and appreciations, quickly the amount of users generate content surpluses the external \u201cprofessional\u201d one.<\/p>\n
TripAdvisor utilized digital technology to allow users easily rank hotels and restaurants using the star system and provide an \u201cessay type\u201d review. Users provide some personal data about their preferences and type of travel which allows TripAdvisor to calcify the reviews and provide more relative content. For example, I can get reviews from couples who were looking for a romantic getaway rather from families with kids.<\/p>\n
One of the struggles TripAdvisor has is to make sure the reviews are genuine and are not generated by the hotel owners. They scan reviews and blacklist hotels with multiple \u201csuspicious\u201d reviews about them.<\/p>\n
Having genuine information about the hotels brought more readers to the site which in turn, wrote their reviews as well and the platform grew. Indirect and direct network effects come into play.<\/p>\n
As TripAdvisor grew and accumulated data, reviews about hotels, resturants and location, its power grew as well as the barriers for entry for potential competitors grow the bigger the site is. People view TripAdvisor as the place you go to compare hotels or get real reviews about a hotel. If you spend time on the website researching a hotel the probability you would book it through this website increases, especially if the prices you are offered there are competitive.<\/p>\n
The more the network grew the more reviews TripAdvisor accumulated. More data points make the start rating more accurate.<\/p>\n
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Recent Washington Post article states that :\u201d This summer, the annual study \u201cPortrait of American Travelers,\u201d by travel marketing company MMGY, highlighted the barreling trend of user-generated content. Forty-one percent of about 2,800 respondents said they visited a travel review site for destination information, up 7 percent from last year. Only 37 percent said they relied on friends and family for trip ideas. In addition, more than half of the participants said they trust review sites over ratings by such established opinionators as AAA and Forbes.\u201d<\/p>\n
Nowadays TripAdvisor works closely with other booking websites to generate additional profit streams. It recently announced a \u201croom booking\u201d deal with Priceline.<\/p>\n
Moreover, hotels are utilizing the start system and physically display their TripAdvisor star rank at the hotel lobbies.<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
TripAdvisor utilizes having genuine information about the hotels to bring more readers to the site which in turn, write their reviews as well and the platform grows attracting more hotels to partner with TripAdvisor. Indirect and direct network effects come into play. <\/p>\n","protected":false},"author":93,"featured_media":1518,"comment_status":"open","ping_status":"closed","template":"","categories":[672,426,535],"class_list":["post-1517","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-crowd-sourcing","category-direct-network-effect","category-indirect-network-effect"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/leveraging-the-collective-intelligence-and-effort-of-digital-crowds\/","yoast_head":"\n