Nevada knows what it’s doing, California may not, and Texas hits the sweet spot when it comes to hotel reviews.

Love it or hate it? 5 Star or 1 Star? Reviews are one of the most significant inputs in a customer’s buying decision. This sentiment is especially true when it comes to booking hotels. Based on a relatively small set of reviews, we can quickly tell whether a particular hotel is stay-worthy or should be avoided entirely. However, can they tell us something more than that? This question intrigued us, and here’s what we found after combing through 400,000+ hotel reviews.

Hotel reviews are an interesting case study of the hidden gems that lie in web data. A lot of people review hotels online, and they do so across many different websites. We know that more positive reviews for a hotel equate to an increase in business for that hotel. In fact, a recent study from Cornell University’s School of Hotel Administration showed that customers are twice as likely to book a hotel with positive reviews as they are a hotel with negative reviews. A second study showed that revenue is strongly correlated with reviews. However, we wondered what would happen if we zoomed out and looked at the data state-by-state. Are some states better at generating reviews? Does a higher tourism budget result in more reviews?

To answer these questions, we studied and analyzed our Business Data that included 437,787 hotel reviews, collected from 60 unique review sites. The review data includes the name and geography of the hotel, along with review text, date, and ratings. We also added demographic and economic data, such as population and tourism budget (collected from third-party sources), in our analysis.

Winners and Losers

Oklahoma & Idaho are surprising winners while the DC-VA area suffers.

Top 10 States Bottom 10 States
Hawaii (4.54) Washington D.C. (2.77)
Nevada (4.27) Virginia (3.10)
Oklahoma (4.23) Mississippi (3.45)
Idaho (4.23) Maine (3.57)
New Jersey (4.21) Washington (3.60)
New Hampshire (4.18) Tennessee (3.61)
Massachusetts (4.15) Connecticut (3.64)
Arizona (4.14) Delaware (3.67)
Alabama (4.13) New Mexico (3.68)

A good place to start looking for insights is to zero in on the top 10 states by average rating. Here, we see some expected and some not-so-expected results. Hawaii’s hotels are basking in the warm, sunny glow of a chart-topping 4.54-star rating, while Oklahoma & Idaho tie at a surprising 3rd place, each with a 4.23-star rating.

Looking at the bottom 10 states, D.C. and VA come in at the very depressing averages of 2.77 and 3.10, respectively. This average is way outside the norm, which could hint that something is off with the hotel industry in this area. It also hints at an opportunity, though. If hotels aren’t meeting customer expectations in this area, then there’s a clear market need. Larger hotel franchises may want to consider what they can do to leapfrog their competition here.

Another interesting insight is that most states’ average ratings are between 3.8 and 4.2. If we consider 3 stars to be average on a 5-star scale, then this suggests one of two possible scenarios: most states (and hotels) are outperforming expectations, OR most reviewers have a bias toward 4 stars. In any other setting, receiving 3 stars out of 5 may be a good thing but according to our hotel reviews data, receiving 3 stars in this context is actually pretty bad. Businesses may need to re-assess their prior findings when taking these ratings into account.

Populated States Have More Reviews

Nevada may have more tourists posting reviews, while visitors to Michigan are silent.

Let’s start with something simple: how does the number of reviews scale with each state’s population? Conventional wisdom would dictate the more populous the state, the more hotel reviews you’re going to see.

Datafiniti used its Business Data to analyze 400,000 hotel reviews and learn how they scale with each state’s population.

The chart above supports this hypothesis, but some states sit way outside this trend. States like Nevada, New York, and Texas generate an abnormally high number of reviews based on their population. On the other hand, other states, like Michigan, Washington, and Pennsylvania, are doing very poorly when it comes to generating hotel reviews for their population. In general, you’ll see states that outperform are those states that are typically considered more “touristy.” Given the importance of reviews on consumer behavior, it may make sense for some states to encourage travelers to post reviews actively.

Higher Tourism Budgets Correlate with More Reviews

California looks good until you look more closely. Is Hawaii an inefficient spender?

Let’s try a different metric. How does a state’s tourism budget relate to its hotel reviews? In some sense, we can use this as a crude proxy to see how well each state’s tourism department is helping generate business for hotels.

Datafiniti used its Business Data to analyze 400,000 hotel reviews and learn how a state's tourism budget correlates to those reviews.

We again see some states doing incredibly well and some not so well. Several states like Nevada and New York are getting a lot of bang for their buck, whereas other states like Hawaii, Illinois, and Michigan might want to look at better ways of spending that money.

One interesting note: California looks like it’s doing well. It’s producing 960 reviews per million dollars. It’s doing better than most, but other states (e.g., Georgia producing 2,036 reviews per million dollars) are doing much, much better. For a state with such a large tourism budget, it would probably be worth California’s time to study how these states are making use of their budget.

Data Is Wonderful

We find data like this incredibly exciting. By analyzing hotel reviews in aggregate, across 60 websites, we can spot some critical trends. These are essential insights for businesses and policymakers alike, and it’s all out there on the web, just waiting for someone to transform it into actionable data.

Even though 400,000+ hotel reviews are a large data set, it’s still small in comparison to the amount of total data available on the web. Even with just this data, we found how review volume moves with population and state spending. We also learned which states are outliers on these metrics.