Have you ever wondered how happy your travellers really are? How their level of satisfaction affects their productivity? How to put all that information into context so you can do something about it? If your answers are yes, yes and yes then read on.
If you cannot measure it, you cannot improve it
Lord Kelvin uttered these words and the good news is that we can and we know how to. By asking the right questions at the right time and integrating that information with all other travel data sources, we are able to not just measure, but to identify improvement opportunities and monitor the impact of changes. Simple, right?
Negativity bias and Von Restorff effect
From time to time stories about flights from hell make headlines and negative feedback written by unhappy travellers goes viral. If you're a keen web user, you might have heard of Rich Wisken, whose complaint letter to Jetstar has been circulating all over the internet for months, reaching hundreds of thousands of views. In contrast, rarely ever do we see comments such as "My flight was on time, it went smoothly and the food on board was surprisingly edible" gaining such popularity. Nor do we tend to see five star TripAdvisor reviews being pasted all over the web. It is also highly unlikely that Rich would have been quite so enthusiastic about describing a positive experience as he was to share his misery at being sat next to an obese passenger, after his flight got delayed, twice. Negativity bias is a psychological phenomenon by which humans have a greater recall of unpleasant memories compared with positive ones.
It is for this reason that if you were to describe one travel experience from the past year, you'd most probably be more likely to recall the one time when your flight was delayed, they ran out of dairy-free options and you were sat next to a crying toddler, who accidentally shared the contents of their stomach all over your nicest business suit. The fifteen other instances when exactly the same journey went seamlessly are somehow not as prominent in your mind as that one time when you were close to tears by the time your plane landed.
This ties in closely with the Von Restorff effect, in which an item that stands out as different is more likely to be remembered. On an American Airlines flight from Los Angeles to New York, one passenger decided to entertain her fellow travellers by singing a popular Whitney Houston hit song at the top of her voice throughout the journey. Do you think there is one single passenger from that unfortunate flight who would ever think of any other trip if they were asked to give feedback about the carrier?
Stars and thumbs
Infrequent surveys about products or services might be subject to a similar bias. Since people are more likely to share their feedback about something negative or unusual, the bigger picture may become obscured. Therefore, we end up with opinions that were only true in unfavourable or extraordinary circumstances. Amazon, for example, tries to overcome this by encouraging you to rate your purchase shortly after a product has been delivered. By doing this when your memory of the experience is still fresh, you are more likely to provide an accurate and unbiased opinion of the product.
YouTube's process is far simpler; they use the widely recognised thumbs up/down button. As a consequence, they have far greater participation and the feedback given is almost immediate. When Google bought YouTube the rating system was based on five stars. This seems simple enough but Google found that changing it to an even simpler thumbs up / thumbs down system dramatically increased participation with no loss of meaningful value.
There is more value knowing that a video has 1932 likes with only 57 dislikes versus a video that is rated 4.8 stars.
Collecting data
When it comes to capturing traveller feedback, same principles apply. Immediate traveller feedback which is timely, simple and easy will provide the most accurate outcome, be it an amazing trip to New York or a horrible train journey to London. And if the system encourages high participation and results in a large amount of data, you can dispense with an extensive survey with myriad of questions. The rich pool of data and sophisticated analytics creates insight from the simplest of responses.
Putting data into context
Traveller feedback will tell you how your travellers feel and even identify where the issue lies but it won't reveal what could be done to make them happier. It is only when you combine traveller sentiment with all other travel data sources (including standard travel data related only to your organisation, social media and public data) that you are able to answer all these questions.
The answers
Is there a correlation between a good feedback and an effective trip? Do employees make more sales and strike more successful business deals when they rated the trip as five stars, or does this have little influence? And from the opposite side of the spectrum, how about a very bad travel experience, does this have an effect on employees' effectiveness?
Let's take the example of International Sales Team A, who often go on business trips and have a high staff turnover, despite great management. With the data at our fingertips we can now look deeper into this scenario and see whether frequent travel has an effect on employee satisfaction. If Ecommerce Team B, despite a similar number of business trips, have a much lower staff churn rate, then perhaps the frequency of hardship Sales Team A experiences influences their job satisfaction. Moreover, how do Team A rate the effectiveness of their trip after a 4am "red-eye flight"? And finally do Teams A and B bring in more revenue as a result of their travels? With all the collected data, the answers will be clearly visible.
Why are your travellers very unsatisfied with a hotel that is rated as number one in Paris in TripAdvisor? Ruling out the possibility that their tastes differ dramatically from the rest of the human population, perhaps the fact that they were generally travelling at night and meeting with clients early in the morning influenced their whole perception of the trip and their experience. Or maybe, being business guests, the package the employees are receiving from that particular venue is worse than that of holidaymakers.
How can you get ahead of the game and avoid future dissatisfaction? Monitoring both internal and public reviews enables you to immediately notice changes in the sentiment and avoid unpleasant surprises. For example, if a once five-star rated venue has recently deteriorated due to management changes, we can spot this and steer our travellers elsewhere to make sure their experience is as positive as possible.
Increasingly, travel managers are transforming their function to be more strategic and recognise that more effective travel, not just cheaper travel, and better understanding and optimising the travel experience is a competitive advantage. To do so, they must take advantage of the cross-correlations that Big Data offers.
They also must understand better what the behavioural scientists call "cognitive biases", and that these biases profoundly change the perception of human experience. By doing so, Big Data promises a way for the travel manager to truly measure the effectiveness of the programmes free from these biases so that better decisions can be made with more immediacy and accuracy and demonstrate the true ROI of travel.