Lead Hospitality

Social Media Marketing ROI (Part Two): Hotel Online Reputation Management

THE IDEA

This article explores the importance of hotel online reputation management and how to measure the success of social media marketing activity. It examines the variables to monitor, the influence of online guest reviews, and how to weight feedback according to its reach and relevance. It also recommends tracking reputation alongside guest expectations and the rate paid.

As I mentioned at the start of this series, rather than ROI, we are actually talking about metrics for measuring the success (or otherwise) of Social Media Marketing initiatives. When defining the variables we are going to monitor to assess the outcome of our Online Reputation Management, we must take into account the objectives we wish to achieve as a result of that management and of each action undertaken, so as not to become the black sheep of our own destiny. Online Reputation Management has, we might say, internal and external implications. Internal in terms of control, improvement and monitoring measures, and external in terms of the content that spreads and has a direct impact on our sales, although not all user-generated content operates in the same way. User reviews, whether from customers or not, remain online, circulate and have an impact on the internet. We must give them the importance they deserve and not focus solely on superficial aspects such as the overall rating or position in search results if we truly want to manage our reputation. We need to analyse the underlying substance of the content—that is, the review—and while the Semantic Web is not yet a reality, we ourselves will need to assess the comments, regardless of the overall rating the user has given us. To do this, we will assign each comment the score we believe the user is assigning through their words to each of the areas we wish to monitor, for example: Facilities, Service, Reception, Food and Beverage, Décor, etc. A good scoring system could range from -3 to +3, including 0 where the guest does not express an opinion on a particular area. We will also assign a publication date to each comment, so that results can be displayed weekly in a chart. One extremely important point is that not all comments influence our reputation in the same way. A review published on a very marginal platform is not the same as a review on Tripadvisor. Likewise, an article on a low-traffic personal blog is not the same as one on a highly influential blog with a large following. Therefore, each platform should be assigned an influence ratio expressed as a percentage (between 0 and 100%), by which all ratings (our own assessments) must be multiplied before being reflected in the chart. This way, we will take every review into account, but each in its proper measure. The degree of influence is left to each person's discretion, based on their own experience and instincts. In the case of blogs, the number of users subscribed via RSS may be a useful indicator, and in the case of online agencies with user reviews, the number of bookings they generate for us can be as well. That is:

Rating = [assigned internal value x criterion] x Degree of Influence / 100

The chart should take the form of a consolidated graph for each area, as well as showing the various historical milestones or improvement actions that have been implemented to influence that reputation. Guest ratings come with the caveat of perceived value versus received value: the higher expectations are, the greater the potential dissatisfaction when they are not met. Expectations are closely linked to the price paid, so it would be worthwhile to create tracking charts not by the publication dates of comments, but by the dates of stay where these can be obtained (perhaps this would be a good way to verify the authenticity of reviews). Even so, there may be some similarity with the chart based on publication dates, but it will allow us to compare it with the average rate achieved that week, or even with the rate paid for the stay by each guest who has submitted a review. By doing this, we can reach interesting conclusions:
  • How the price paid influences the satisfaction ratio.
  • How our Revenue Management policy influences our Online Reputation.
and, more importantly:
  • Predict in advance the periods in which our Online Reputation will be affected, so that we can take preventive measures.
  • Know when it will be necessary to sacrifice average rate in order to achieve better online positioning.
The lack of technological tools makes this work entirely manual, but extremely interesting. Something tells me that within a matter of months, given the pace at which technology is advancing and start-ups are emerging, we will have precise tools for our sector that will make this task easier. Of course, this is my view of what Online Reputation Management is, although one could simply monitor content and occasionally post a comment to challenge an opinion or publish fictitious comments to encourage Spam 2.0; but this is merely a reactive strategy that leaves us at the mercy of what happens in the market and what users think. Ultimately, of course, the ROI of Online Reputation Management is the traditional ROI: the ROI of our Hotel Marketing and our Revenue Management, which should improve significantly as our online reputation improves.
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