Tough Customer(Guest) Situation? Tips to make the "save".
One of the most popular features of our service (as our clients tell us) is the guest alert- which offers guests, during the feedback survey, the opportunity to request contact from hotel management. If a guest ticks that box, email alerts are sent immediately to the designated hotel personnel distribution list with details about the guest's feedback. On average, approximately 7% of our clients' guests make the request.
Over the years (this feature has been in place for 9+ years), clients have asked us for advice on how to handle those alerts. Sometimes, guests are looking to personally offer praise for a job well done or for a personal touch in booking future additional stays.
In other instances, however, guests are looking for a personal interaction in dealing with experiences that have not met their expectations. Often, these are true opportunities to save future business (both directly and through referrals), as these guests have actively opened a direct and clear line of communication. Sometimes, the fix is easy. In other instances, not so much.
This week, we came across a blog entry about dealing with tough customer support situations. While it has a technology focus, a lot of the content translates to other businesses, including hospitality. We think it's worth a read; check it out here.
A 5 point scale provides a simple and effective mechanism for quantifying ratings. In our 31 years of collecting and analyzing consumer opinions, we've seen a wide variety of rating scales and have been able to form a pretty solid data-based position on the subject.
Here are the key reasons for this position:
- An odd numbered scale provides a mid-point for a neutral rating
- 2 points on either side of that neutral point provides the opportunity to differentiate between a strong positive (or negative) and somewhat positive (or negative) rating
For example, take a look at typical attribute ratings for a guest room below; we use a satisfaction scale
By only offering 2 points on either side of the neutral point, we provide a fair measure of standardization of responses. Some folks in our business like to use a larger point scale; 11 points is common (0 - 10). The main problem we see with this is that it's difficult to accurately discern differences between all the gradations on either side of the midpoint; what I may consider an "8", you may consider a "7". Tracking these metrics becomes problematic because the meaning of, for example, an average score of 7.3 is muddled.
Consider the difficulty in tracking an 11 point rating metric when you read the following real example of guest feedback- [we actually have some clients who we've designed custom feedback solutions for to their specifications, employing a 0-10 rating scale ]. This is a guest's verbatim explanation of their rating of an attribute; "No one is perfect but my 8 and 9 are good for me."
Do you want to see perfect scores and reviews for your property on TripAdvisor, Yelp, Google, and other review sites? Maybe not.
Our research shows that perfect scores and glowing reviews are sometimes met with skepticism, especially if the sample size is alarmingly small. To be sure, nobody is perfect and consumers are looking for honesty, transparency, and responsiveness. Simply put, an online review profile of a 4.5 star rating based on 150 reviews is far more attractive than a perfect 5.0 rating and 10 reviews. And, consumers consider you in the context of your competition; that 4.5 rating/150 reviews looks especially great in a geographic competitive market where properties receive an average of 120 reviews, but not so great in a market where properties have an average of 300 reviews.
After a thorough analysis of all the data we've collected over the past 10 years, across all of our clients and properties, we found patterns and trends that led us to re-imagine the reporting of our proprietary Fan Value Score (FVS) loyalty metric. In the past, we reported each guest's FVS as a real number. The data suggested that the Fan Value Score for an individual guest is best expressed as one of five scores; +2, +1, 0, -1, -2.
+2 guests are your true-est fans (and will most likely impact your future business positively through repeat stays, recommendations, reviews), whereas -2's are are of most concern. These loyalty segments afford new targeted marketing opportunities for you; please refer to the attached document for a more thorough description of the new Fan Value Segmentation Scoring and new applications.
Our proprietary Fan Value Score metric was inspired by the Plus/Minus hockey statistic which measures the performance of a team broken down by individual player contribution. For example, a player with a +1 rating over the course of the Stanley Cup Finals will have been on the ice when his team has outscored the opposition by 1 goal. Conversely, a player with a -2 rating will have been on the ice while his team was outscored by 2 goals.
Similarly, our Fan Value Score assigns a value to each customer's experience. Scores above 0 indicate a customer who is likely to have a positive impact on future business (repeat customer, recommendation, positive feedback on the review sites). The higher the Fan Value Score, the more likely that customer will have a positive impact on your business, going forward. Marketing opportunities abound to target offers based on individual scores.
From a wider perspective, the average Fan Value Score of a business is a great metric to track over time for monitoring loyalty trends.
The Rating Percentage Index (RPI) is a metric used by the NCAA basketball committee to help select teams for the tournament. With bracket-mania now in full swing, we thought it would be interesting to see how we might use the RPI to help fill out our bracket.
Higher seeds are expected to beat lower seeds.
Upsets are expected in the tournament; lower seeds beating higher seeds.
Our Bracket Filling Rules/Methodology:
Upsets Expected Based on Previous 3 Tournaments:
Round of 64=9
Round of 32=4
Round of 16=3
Round of 8=2
So here is the bracket- we'll grade our accuracy after the tournament. Enjoy!
The blog of Database Sciences and its GuestInsight & ListenKeenly services.