It’s a case of good news/bad news for the travel app industry. The good news is that people are using apps to book travel more often than ever. The bad news is that the travel app space is highly competitive.
At the same time, there are multiple travel apps to choose from, and people have become more selective about what to download. This increases the average cost per acquired user. Now, app marketers not only have to work harder to get users to download the app in the first place, but they also have to convince them to keep using it.
Savvy marketers are using data to accomplish that. By taking a data-centric approach to mobile app marketing – one that utilizes meaningful in-app events across the user lifecycle, beyond just tracking bookings – you can help your app stand out, drive engagement and revenue.
Focus on retention, not just user acquisition
To build a sustainable business, marketers need to shift their mindset from acquiring users to retaining them.
This is true across verticals, but particularly in the travel space, which is not only crowded, but also fragmented in functionality. The top 100 free apps in the travel category include utilities, taxi, booking and planning, lodging, public transit, maps, guides, rental car, branded experience apps and more.
The other challenge is that the same major players – Yelp, Google Earth, Delta Airlines, etc – tend to dominate the rankings in the app stores. In fact, Uber has been in the top 10 list of free travel apps in the US since 2013; there is not a ton of movement in the top tier.
Before app marketers can expect to be users’ trusted source for mobile bookings, they have to build a relationship with them. Marketers can use data to improve their app user experience as well as their marketing strategies. Data enables the ability to continually offer valuable, relevant content even when users don’t have an immediate booking need.
For example, Hopper, which currently ranks in the travel app top 20 list of free apps in the US, tracks relevant, early-funnel in-app events long before a booking to drive engagement. It uses granular data on what users and airfare watchers are searching for, viewing and saving in order to personalize travel recommendations that lead to increased retention rates and drive re-engagement.
Skyscanner also took a refreshed, data-centric approach to their mobile growth in 2016 when it merged its flight, hotel and car rental apps into one app. It used mobile attribution and analytics to test and compare advertising campaigns and track and optimize performance in real time to not only drive bookings but also engagement.
Its new app has a 10x better loyalty rate and 2.5x better mobile app engagement than its legacy properties.
Don’t just follow – lead
When you track granular data points, you can improve your ability to predict user behavior and make more relevant suggestions to your users. Travel marketing used to be purely intent-driven.
For example, a booking app would invest ad dollars to ensure its ads were served when a user Googled “cheap flights to Cancun.” Now, a growing number of marketers are investing in their ability to offer smart, data-backed suggestions; they’re not waiting until a user shows intent before jumping into action.
The best examples of predictive technology rely on big data. Juggernauts such as Google and Amazon rely on machine learning and massive first-party data sets to make recommendations that can be almost eerily accurate.
Travel apps don’t have this same level of data to draw upon, as people are often searching for one-off, or at least infrequent, events, such as a destination wedding or an annual family trip. But they can still use first-party data to improve their marketing by measuring and analyzing in-app user interactions.
Marketers should not overlook the value of genuine discovery. Some of the best travel apps don’t just show users what they want, they show them what they didn’t know they wanted. For example, curating a list of new places to visit based on user preferences (rather than exact searches) can surprise, delight and drive engagement.
By properly leveraging and analyzing deep data points to understand who and how consumers are using their app, marketers can more effectively find more users like them. For example, they can create user profiles based on their most active users and then ask their advertising partners, such as Facebook, to create lookalike targeting campaigns in which they target audiences who have the same traits as high-value users.
Being a data-driven marketer is about more than A/B testing ad campaigns to see which drives the highest conversion rate. Data can, and should, be used to improve the customer experience, make better recommendations, ensure content is relevant, improve marketing communication and, ultimately, drive retention, engagement and revenues.
It is up to marketers to use the necessary tools and processes for measuring, analyzing and activating their data.
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