My colleague Kelly McGuire recently teamed with Associate Professor Breffni Noone at The Pennsylvania State University to study the role of reviews and ratings and price on purchase decisions in the hotel sector.
Their findings confirmed the relationship linking ratings and reviews with quality and value perceptions of hotel room purchases that they'd found in a previous study.
While their research focused on the hospitality industry, it's not a stretch to see how negative reviews can impact purchase decisions in other industries.
Kelly summarized the four biggest takeaways from their study as follows:
Reviews and price are the most important influencers of choice. While consumers did pay attention to aggregate ratings, TripAdvisor rank, and, to a lesser extent, brand, positive reviews contributed the most to consumer choice behavior followed by lower price.
Negative reviews remove you from the choice set. Period. Lower price or higher ratings do not overcome the impact of negative reviews. Consumers simply will not choose a hotel with negative reviews. Hotels that are in this unfortunate situation should focus energies on improving their reputation.
Consumers prefer to pay a lower price. While consumers would go for a higher-priced hotel when the reviews and ratings were better than the alternatives, all things being equal, they will look for the lowest price. Hotels need to understand their position relative to their competition both on reputation and on price in order to take advantage of any pricing power associated with positive UGC (user-generated content).
Consumers only notice high ratings and rankings. Our results showed that consumers only notice ratings and rankings when they are high as compared to other choices. Consumers do not place any value on the comparison between low and mid-level ratings and rankings.
As you think about what this might mean for your organization, your first thought might settle on how to manage a bad review -- or worse yet, a string of bad reviews. And the bigger your operation, the harder it is to even find out about issues with your reputation. Social Media Analytics can help you keep an eye on "the buzz" about your brand so you can catch issues early.
Then there's the more strategic question of the root cause of bad reviews, which come from bad customer experiences. And considering how customers experience most brands both online and offline, customer experience management has broad implications -- far beyond marketing -- in the enterprise. Adaptive Customer Experience can help manage the online experience of your customers, but engaging with your contact center or customer experience department in addition to getting the messages from your marketing campaigns means more opportunities for miscues and more chances for wrong expectations that can lead to negative reviews.
That's where an integrated marketing management approach comes in. It can drive the necessary customer-centric focus is how to address the impact of bad customer reviews. It's also how to align your organization around preventing the bad customer experiences that lead to negative reviews. It's far easier said than done, but well worth the effort. And we have many examples of how well it works -- please contact us and find out how it can work for you.
I agree with what you said about not seeing the Will Smith movie because it got an %11 on rotten tomatoes. But what if your a big fan of Will Smith? Wouldn't having a star actor as the main lead still draw in their fans?
Thanks @Kelly. You know, I never thought that they may get it backwards, but perhaps that's the case for some people who write something good but have one star or have 5 stars and a pretty negative review. Occasionally though, they are really responding to two different things. They are sometimes unhappy about the product but happy about the way the seller handled the return, etc. That kind of thing only can come across in the text, which is another reason why I prefer written reviews.
We tested both the "star" ratings and the text reviews. The reviews had the most powerful relationship with quality, value and choice. Our participants felt the same way you do about the unreliability of a rating, so they prefered to hear from reviewers in their own words. And I have also seen inconsistency between the reviews and the ratings - which leads me to suspect that things like what you suggest below happen - default settings or also people not understanding that 1 is bad and 5 is good, so they get it backward!
Did the study look into different reactions to reviews that are limited to rankings and those that include the reviewer's take in words? I respond a lot more to the latter than to the former. In fact, I sometimes find that the number of stars don't match up with the description. Sometimes the person gives something 5 stars while the description shows it really doesn't merit it. I think sometimes that may be because the system's default sets up the number of stars, and the reviewer doesn't change it.
2015 Visual Analytics Interactive RoadshowSAS(r) experts are coming to a city near you in a series of live, interactive workshops focused on SAS Visual Analytics, including how to prepare your data for VA, the integration of VA with Office Analytics and a Visual Statistics demo.
January 22: King of Prussia, PA
February 24: Austin, TX
March 26: Redwood City, CA
April 22: NYC, NY (1st of 2 stops)
May 13: Seattle, WA
June 18: Minneapolis, MN
July 21: Rockville, MD
August 18: Chicago, IL
September 24: Irvine, CA
October 9: Cary, NC (during SAS Championship)
October 21: NYC, NY (2nd of 2 stops)
November 17: Orlando, FL
December 8: Atlanta, GA
LEADERS FROM THE BUSINESS AND IT COMMUNITIES DUEL OVER CRITICAL TECHNOLOGY ISSUES
The Current Discussion
Visual Analytics: Who Carries the Onus? The Issue: Data visualization is an up-and-coming technology for businesses that want to deliver analytical results in a visual way, enabling analysts the ability to spot patterns more easily and business users to absorb the insight at a glance and better understand what questions to ask of the data. But does it make more sense to train everybody to handle the visualization mandate or bring on visualization expertise? Our experts are divided on the question. The Speakers: Hyoun Park, Principal Analyst, Nucleus Research; Jonathan Schwabish, US Economist & Data Visualizer
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The days when historical shipment trends and gut feelings were enough to forecast retail demand accurately are long over. SAS chief industry consultant Charles Chase outlines the benefits of pulling real-time sales information from point-of-sale and product scanner systems, then flowing that data into dynamic forecasting tools from SAS.
With today's advanced visual analytics tools, you can stream data into memory for real-time processing, provide users the ability to explore and manipulate the data, and bring your data to life for the business.
Dynamic data visualizations let analysts and business users interact with the data, changing variables or drilling down into data points, and see results in a flash. Advance your use of data visualization with tools that support features like auto-charting, explanatory pop-ups, and mobile sharing.
No doubt your enterprise is amassing loads of data for fact-based decision-making. Hand in hand with all that data comes big computational requirements. Can traditional IT infrastructure handle the increasing number and complexity of your analytical work? Probably not, which is why you need a backend rethink. Big data calls for a high-performance analytics infrastructure, as Fern Halper, a partner at the IT consulting and research firm, Hurwitz & Associates, discusses here.
Redbox's bright-red DVD kiosks are all but ubiquitous these days, located in more than 28,000 spots across the country. Jayson Tipp, Redbox VP of Analytics and CRM, provides an insider's look at how the company has accomplished its phenomenal nine-year growth.
InterContinental Hotels Group (IHG), a seven-brand global hotelier, has woven analytics into the fabric of its operations. David Schmitt, director of performance strategy and planning, shares IHG's analytics story and his lessons learned.