3 App Success Metrics Through Data – Hopper’s Flight Tonight


In July, Hopper launched its new iPhone App, Flight Tonight that provides prices for last minute, same day and next day flights. Personally, I am extremely excited about the app and use it habitually every Thursday and Friday to see if I can book an affordable last minute getaway. But with over 1.2 million apps in the app store and an average travel app’s half-life of 4 months, how is an app to get noticed and succeed long term? The way I look at it, in order for this app to prosper, it must attain these three success metrics: habit formation, conversion and viral appeal. Through data, I believe an app like Flight Tonight can succeed at attaining these metrics. For example, gathering more data on the user to refine users’ experience will promote habits and increase app utilization, overlaying additional data to better inform a user will increase the likelihood of conversions/purchases, and tracking data regarding the app’s usage can create a viral loop. Now I know the app is just over a month old, but I believe Hopper has the right skillset and vision to benefit from implementing these types of data. So here are my thoughts as to how Hopper can use data to its advantage in growing its Flight Tonight app. I have no knowledge of whether Hopper takes, or plans to take, any of these approaches.

To illustrate the potential means to achieve the success metrics mentioned above, we are going to follow a user named John, a 28 year old single male who lives in Boston. He is an avid college football fan, and is particularly fond of University of Georgia’s team (Go Dawgs!). John is sick of the early winters that hit Boston. He has downloaded the Flight Tonight app, and would check it at least once a week if it would notify him of cheap flight tickets to locations where his favorite college football teams are playing.

  • Gathering additional data points about its users’ interests, hobbies and backgrounds will enable Hopper to interact on a more personal level with its user base through notifications about events the user values. These notifications will causes users to check the app habitually, as the user interested about a notification will view the app to price flights. This increased app utilization can also reduce a major hurdle of extending any new travel app’s estimated half-life of 4 months. In sum, app-collected information, such as a user’s favorite sports teams, bands, hobbies, and other event-driven interests will allow Hopper to optimally notify the user of reasons to travel.

Assume it is Halloween night. Before heading out to a costume party, John opens the app (just like every week) and sees a cheap flight to Jacksonville, FL for the next day. He knows that UGA is playing the Florida Gators there and the expected game time temperature is 74 degrees. Now having two reasons to fly, game and weather, he purchases a ticket.

  • By following Hopper’s own decree of “data-driven” decisions, overlaying data about sporting and other major events such as concerts, art exhibits, and conferences with flight locations, can give a user a reason/purpose to convert and purchase a ticket. In the same regard, providing forecast weather for the trip’s duration allows the user to make a more informed decision on where to visit. Hopper may even want to partner with the Hotel Tonight app, which offers last-minute hotel deals, to eliminate a further roadblock to last minute travel:  where to stay.  By providing additional data points like events, weather, and even hospitality for the destination, the user is better informed about making that purchase.

Now, fast forward to the next day. It is a beautiful Saturday afternoon in Jacksonville, FL and John is enjoying the UGA football game and begins posting selfies and stadium photo to Facebook, Twitter and Instagram with the hashtag #ThanksHopper.

  • The last measure of success is about acquiring new users, while at the same time keeping your current users happy. In order to achieve this viral success, the marketing program, #ThanksHopper, is developed. The campaign serves two purposes: (a) a customer loyalty program to retain and to promote repeat purchases and (b) viral marketing through users’ social networks.  Here is how it works: after John purchases the airline ticket he is asked to join Hopper’s customer loyalty program that provides rewards points on future flights purchased through Flight Tonight.  All he has to do is provide his Twitter/Instagram handles and post pictures of his trip with the hashtag #ThanksHopper. John then earns points for every impression/click of #ThanksHopper and app download generated by his posts. As we can see, the customer loyalty program is nonintrusive for John, as he only needs to add a hashtag to the photos he is already going to post to generate the benefit.  However, the benefit is key to the viral aspect of the campaign.  Let’s assume that John has 200 Facebook friends that see pictures of him on his trip to Jacksonville and a creative hashtag that creates intrigue, like #ThanksHopper. Once they click on the hashtag, his friends see others on trips booked through Flight Tonight.  This creates brand awareness for Hopper’s app, and every app download brings another user.  By tracking the data generated by this marketing campaign, Hopper can reward its users for virally promoting its product.

Again, I know Flight Tonight is still a young app, but can you see the possibilities for Hopper to achieve the 3 success metrics by collecting and utilizing data about its users. By giving its users reasons to use the app (notifications), reasons to make a purchase (information about motivation to travel that are valuable to the user) and benefits to promote the app (customer loyalty), an app can stand out in a crowd of 1.2 million app.

We at Prosperity Analytics, would love to hear your thoughts at www.prosperityanalytics.com or data@prosperityanalytics.com!

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