China’s vibrant social media environment has quickly become a crucial part of travel shopping. As travelers increasingly share their experiences, and shoppers turn for advice to those who have gone before them, user reviews play a big role in the purchase decision. Competition is hot among intermediaries to attract an expanding number of traveler reviews. This report, the first of its kind focusing on the Chinese travel market, examines the role and impact of
traveler review content on China’s online travel ecosystem.
FREE presentation deck and audio recording of the August 13 corresponding webinar comes with your report purchase (download link is sent in your report purchase confirmation). Or download for free HERE.
This report examines the following:
- The role and impact of traveler reviews on China’s online travel market
- The extent to which travelers in China post hotel reviews and where they post them
- The volume of traveler reviews posted on traveler review websites, metasearch sites and online travel agencies (OTAs), and how this has trended over 2012 and 2013
- The sentiment of online traveler reviews through semantic analysis with Brand Karma
- Key social travel benchmarks – buzz and social travel advocacy index (STAI) – to gauge social travel performance in terms of review volume (buzz) and sentiment scoring (STAI) for hotels
- Introduction Methodology
- Key Findings
- Traveler Review Data Methodology
- Hotel Star-Rating Classification
- City Tiers
- Benchmark Indices Buzz and STAI
- Social Media Travel in China
- Traveler Reviews Activity
- Online Travel Agencies vs. Metasearch vs. Traveler Review Websites
- Review Volume by Site
- Review Volume Buzz
- Buzz by Star Rating
- Buzz by City Tiers and Chinese and International Brands
- Traveler Reviews Sentiment
- STAI by Star Rating
- STAI by Chinese and International Brands
- The Five Highest and Lowest Brands by STAI
Traveler Reviews and Social Media in China leverages consumer survey data from Phocuswright's China Consumer Travel Report (September 2013). Phocuswright also partnered with Brand Karma to analyze traveler reviews posted on social travel sites, leading metasearch sites and OTAs using Brand Karma's proprietary technology for measuring review volume and semantic analysis.
Traveler Review Data Methodology
Phocuswright and Brand Karma analyzed more than 1.2 million traveler reviews posted by travelers across five travel sites – three OTAs, one traveler review site and one metasearch site – over 2012 and 2013. Each review is tied to a specific hotel brand and property in China. The 1.2 million reviews represent 1,279 properties – including local and international hotel brands across all service categories – in 217 cities in China. The reviews analyzed are a sampling. Figures that include review volume amounts reflect the sample used for this study. They should not be interpreted as the total volume of reviews on any of the websites included in this research.
Brand Karma interprets how consumers perceive brands by analyzing brand sentiments on travel review sites, OTAs, discussion forums and influential blogs. Brand Karma applies text analysis and natural language processing to examine all statements within a hotel review to determine what product or service is being discussed and whether the guest's sentiment toward that product or service is positive, negative or neutral. The technology can detect subtle differences in expression. For example, a comment describing a hotel's breakfast buffet as "delicious" is scored more favorably than one describing it as "pretty good." Brand Karma combines these scores to calculate a review's overall "net quality score." This result is mapped to an index of -100 to +100.
Hotel Star-Rating Classification
Phocuswright and Brand Karma collaborated to develop a select sample of hotels for the Chinese lodging industry. Properties included in the analysis of traveler-generated reviews spanned all hotel classes, from one-star to five-star.
While star-rating classifications vary globally, in China they are especially lacking in consistency and standardization – and with the exception of the international five-star standard, they often differ greatly from the classifications in other markets. For this study, star ratings for each property were developed from an average rating from the websites analyzed.
The overall sample includes a larger share of four- and five-star properties. Two- and three-star properties account for just 15% of the total supply, four-star properties account for 28%, and five-star properties represent 57%. For international brands, the top two categories account for more than 90% of supply. The study sample also includes more international than domestic brands: Two in three rooms belong to non-Chinese brands.
Post-reform development in China has been uneven for decades in several ways; one of the most evident is the disparity between growth and development in the country's eastern metropolitan areas compared to that in the rest of the country. Although the whole country is undergoing rapid change, a group of four cities – Beijing, Shanghai, Guangzhou and Shenzhen – occupies a leading position in financial and commercial development. These four are treated together in this study as Tier 1 cities (the designation they are commonly given). Tier 2 cities are those with a population between 2 million and 10 million – 39 cities altogether. The 174 Tier 3 cities are those with a population of less than 2 million.
Benchmark Indices: Buzz and STAI
Buzz: The "buzz" metric represents the number of reviews/mentions of a hotel brand. It provides an index of activity or volume, but not of sentiment. In other words, while activity may be positive, negative or neutral, the volume of activity is itself important, regardless of sentiment quality. This report defines buzz as the number of reviews per month for every 100 rooms of a hotel brand, so as to account for brands with more properties or with a higher average number of rooms per property.
Social Travel Advocacy Index (STAI): Based on the net quality score generated by Brand Karma, Phocuswright developed an index to track overall traveler sentiment across all reviews. STAI represents the average monthly net quality score for the hotel brand and star-rating category. STAI is weighted to account for the brand's share of total hotel review volume and star category. For example, suppose Brand A, a three-star hotel brand, has a STAI of 20 with 1,000 reviews, and Brand B, also a three-star brand, has a STAI of 40 but only 500 reviews. The STAI score for the three-star category would place more weight on Brand A because it has more reviews.