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Inside Disney Resort Reviews - Is The Magic Still Alive?

Disney resort reviews show a mix of audience emotions, even as Walt Disney World celebrates its Golden Anniversary this year. Having completed 50 glorious years, the Magic Kingdom remains one of the top entertainment and vacation planning destinations in the world.

The media has been abounding with stories suggesting that the happiest place on earth may not be as magical as it used to be. So do other customer forums. And yet, others suggest that despite its challenges, Disney resorts still remain an all-time favorite.

Considering the barrage of these conflicting stories online, we decided to use Repustate’s machine learning (ML)-driven sentiment analysis platform, Repustate IQ, to analyze Disney resort reviews and comments, and see for ourselves.

What Insights Did Repustate IQ Show About Disney Resort Reviews?

The best approach to truly understanding brand experience is by analyzing customer comments from different data sources. In this case, we decided to use two of the top platforms for consumer reviews - Google, and Reddit - mainly because of the difference in the nature of their audience.

While Google is mostly used by casual visitors, forums like Reddit are used by avid customers who discuss and share details of their experiences with fellow enthusiasts with great passion. Thus, sentiment derived from both groups can vary a great deal. This makes the data diverse, which is great for an accurate depiction of overall and aspect-based brand sentiment.

Disney Resort Reviews On Google

Repustate’s feature-rich Google review analyzer, Repustate IQ, extracts buried customer sentiment from the data it pulls from Google. In this case, we looked for Disney resort reviews for the Orlando theme park. Below are some of the key insights we got.

1. Fluctuating Sentiment Trend Patterns

We saw that the customer sentiment trend based on Google reviews of Disney Florida from mid-2019 clearly showed a spike in customer review (activity), and then a sudden dip during the Covid pandemic lockdowns by mid-2020. Business slowly picked up and reached its peak, beginning by mid-2021, and then slowing down again. Data points on the dashboard showcase the exact date when the reviews were written pertaining to which the sentiment is derived. It also shows that activity for Disney’s 50th-year celebrations is yet to pick up speed. Perhaps, that’s why offers and celebrations have been extended to March 21, 2023.

Disney World Google Reviews Showing Fluctuating Sentiment Trend Patterns

Businesses can monitor such trends to find out the reasons behind spikes and dips. More often than not there is a simple explanation. But when there is a consistency in some patterns that emerge periodically, then a company needs to find out the factors that are causing such trends.

2. Overall Positive Brand Sentiment

The overall sentiment pie-chart for Disney resort reviews in Florida shows a high positive sentiment at 73%, 21.4% negative sentiment, and 5.6% neutral sentiment. The sentiment trend can also be viewed as a bar graph for more clarity.

This goes to show that the customer demography using Google reviews is mostly happy with their experience at Disney, albeit there are some factors that need improvement.

Disney World Google Reviews Show Overall Positive Brand Sentiment

3. Overall Positive Sentiment Based On Language/Ethnicity

Repustate’s Google analyzer automatically detects various languages in the data. In this case, it identifies 10 different languages as seen in the pie chart below. The platform thus tells you customer sentiment based on the language used to write the reviews. In this case, we know that customers from all backgrounds seemed to have a similar experience at the resort.

This might be good news for Disney, given that the organization has come under fire recently for insensitivity towards the indigenous community in their performances.

Disney World Google Reviews Show Overall Positive Sentiment Based On Language/Ethnicity

When clicking on the Spanish language bar for negative sentiment, Repustate IQ shows the Spanish comments from which it has automatically detected the topics most relevant in the comment.

It is important to note that Repustate IQ analyzed Spanish in its native format. It did not use translations as most other sentiment analysis tools do. This approach increases the accuracy of results because machine translations can dilute the meaning of the original language.

Disney World Google Reviews Analyzed for Spanish Speakers

4. Staff and Price Are The Most Commonly Talked About Aspects

The model identified and extracted various aspects of people’s experience from the Disney resort reviews. It also showed us the trend in which these aspects like appearing, spiking, and dipping.

As you can see, data points showcase what the aspects are about. In the below image, we see that people were talking the most about “staff” during March 2022, followed by price. Sentiment analysis of these aspects will reveal further, why customers mentioned staff so often.

Disney World Google Reviews Show Sentiment With Most Talked Topics

5. Discovering Aspect Sentiment

Going deeper into aspect-based sentiment, we see how much positive, negative, and neutral sentiment there is about each aspect. This is the granular explanation you need in order to come up with tangible strategies for improving customer experience.

Once you get this aspect-based sentiment graph, you might want to analyze the reasons behind it. Repustate IQ enables you to do this by giving you a clear picture of negative, positive, and neutral sentiments regarding each aspect. When you click on the sentiment bar, you can easily see what those actual comments are.

Disney World Google Reviews Analyzed for Aspect-based sentiment analysis

Let us keep to the example of the aspect “staff”. And see why there is negative and positive sentiment.

Positive Sentiment

Clicking on the positive sentiment reveals the following aspects about staff and the comments. We can see that all comments talk about the great service.

Disney World Google Reviews Reflecting Postive Reviews for Staff

Negative Sentiment

Let us see what we can discover when we click on the Negative Sentiment.

Disney World Google Reviews With Negative Sentiment for Staff

From these comments, we can see that people were not really unhappy with the staff (rude, curt, unhelpful) but rather with the service that was being provided, which seemed to be haphazard (AC not working, charged incorrectly, etc.). Cleanliness was an issue too, which was attributed to the cleaning staff.

Thus we see that without an actual granular analysis, there is no way to find out the ground reality behind customer complaints. Machine learning helps with this aspect tremendously, allowing you to prioritize efforts towards bettering your service.

Repustate has helped MNC's, banks, governments, and hotels extract business insights from their customer data. We can help you, too.

Disney Resort Reviews On Reddit

Analysis of customer sentiment about Disney World, Florida on Reddit and subreddit forums was equally important to get a more balanced view of brand sentiment. So, to begin with, we decided to use the phrase “lost its magic” on a Reddit post dedicated to Disney. We further narrowed the analysis down to a time period of mid-September 2022. Let’s see the results we got.

1. Vastly Different Sentiment Scores Compared To Google

The first thing we observed was that the sentiment score was vastly different from the sentiment scores we found on Google reviews.

This was not surprising, given that Reddit users are more fanatical in their approach to brands, being more avid customers, and so more detailed in their comments. They also have higher expectations than casual visitors.

Disney World Reddit Reviews Show Very Poor Sentiment

2. “People” Was The Most Commonly Used Word, “Price” Came Much Later

Diving deeper, we wanted to see what the emerging topics seemed to be in the Reddit post that had 700+ comments. We observed that the community talked the most about “people”, which had 85 comments, “time”, with 20 comments, “price”, with 16 comments, and so on.

A manual analysis of the data showed that users were using the same word “people” while talking about experiences, guests, crowd, staff, visitors, etc. Time and Price, which were the next most-used phrases revealed that it was mainly about the long wait-times and increased ticket and room prices at the resort.

Clearly, people were mentioning crowds, inconvenience, and how costly the resort had become. We then checked to see if there were similar stories in the media about how Disney was becoming exorbitantly pricey, and there they were.

Disney World Reddit Reviews Common Entities

3. “Staff” and “Price” Were The Most Talked About Aspects, Similar To Google Reviews

This insight showed that even though “people” and “Disney” were the most talked about words and phrases, it was actually about money (price) and service (staff) that the comments were about.

Disney World Reddit Reviews Aspect-based Sentiment analysis

To dig deeper, we clicked on the aspect “price” showing at 35.4% to see what comments comprised that particular portion of the graph.

We saw that people were concerned that Disney was increasing its prices, while service was declining. Customers felt they were being overcharged for shoddy service. Some were even wondering whether Disney was being preferential in its treatment of guests by deliberately increasing prices to keep certain customer populations outs.

Disney World Reddit Reviews Shows Negative Reviews about Staff

This was a surprising element considering that Disney has always tried to position itself as a children’s haven regardless of color, creed, or background, albeit struggling to keep up with the times.

What was also insightful was the fact that Google review results had shown that customers from all ethnicities had mentioned a mostly positive experience. Thus, further reinforcing the importance of deriving sentiment from more than one data source for brand insights.

4. Different Aspect Sentiments Than Those From Google

Aspect by sentiment too revealed different insights from those found on Google. It showed that only 43% of users had positive sentiments with regard to the staff, compared to 63% on Google reviews. Similarly, only 39% felt they got their money’s worth, compared to 50% of visitors who wrote Disney resort reviews on Google.

Disney World Reddit Reviews Show Overall Negative Sentiment

5. Aspect Co-occurrence Shows Price & Staff

Aspect co-occurrence data insights were in the same vein. They showed that the aspects “price” and “staff” occurred at the same frequency.

This tied in with the manual analysis of comments that showed that people talked of rising costs at the resort (prices for rooms, rides, activities, restaurants, and other attractions) while facing a decline in service and convenience.

Learn more about Reddit sentiment analysis.

Disney World Reddit Reviews Aspect Co-occurance

See how Repustate's Sentiment analysis solution can help you overcome customer feedback challenges with our cutting-edge AI technology.

To Sum Up

As can be seen from the above analysis, multiple data sources reveal many different facets of customer experience and motivations, all of which can greatly affect brand reputation. You get several hidden insights that can be invaluable to not only your strategy for continuous improvement but also in cultivating a loyal customer base.

Given the many advantages of machine learning algorithms, sentiment analysis of customer reviews is truly one of the best ways in which one can not only conduct market research in a fraction of the time traditional research takes, but also find actionable insights to increase business efficiency.

Behind The Scenes Of Repustate IQ

Repustate IQ uses machine learning to analyze data, regardless of its format. It can analyze social media listening data that includes videos and comments, as well as news articles, news videos, podcasts, surveys, and so on. This way you can receive customer experience analysis insights, whatever your data source.

The sentiment analysis model is trained for each industry individually using training data from that particular industry. This is important because if aspect models are not based on your industry type, it will greatly hinder the insights. For example, the model for a banking client will be very different from a restaurant, and vice versa.

In this case, sentiment analysis on the Disney resort reviews was done in the following steps.

  • Data collection

Data was collected from the customer review data sources. In this case, Google. We simply pasted the Google URL directly into the dashboard. You could also download the comments and upload the data as a .csv file.

  • Data processing

Various ML tasks such as native natural language processing (NLP), named entity recognition (NER), semantic clustering, and such analyzed the Disney data and extracted all the relevant data points, categorizing them into topics, themes, and aspects.

  • Sentiment analysis

Each aspect was scored between -1 to +1, with the total tally given to you in percentile form showing the overall brand sentiment as well as the aspect-based sentiment. These included customer sentiment regarding service, cleanliness, food, drinks, etc.

  • Insight Visualization

All the insights were presented on the Repustate IQ dashboard in user-friendly form. The sentiment analysis dashboard allows you to set alerts for notifications for any keyword, hashtag, or brand mention as well. You can also customize sentiment rules in case you need to alter aspects.

Take a quick tour of Repustate's Sentiment mining solution.

Conclusion

Like any savvy organization, Disney knows how critical it is to stay in tune with its audience’s reactions. It’s no surprise that the company has been embracing machine learning increasingly to analyze customer experience at its resorts in order to understand, predict, and improve customer experience.

Explore machine learning to grow your business too. Make insightful discoveries through Repustate IQ as we did for Disney resort reviews. Leverage TikTok insights, Instagram social listening, YouTube comments analysis, or insights from any of the other various data sources we cover for customer intelligence.

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