App Marketing and Data go together like… two things that go exceptionally well together (feel free to choose your favorite simile from this poetic list of examples of ways to say how well things go together…).
Data helps marketers spot trends and more efficiently allocate their time, efforts, and budgets. It allows marketers to get a deeper understanding of their users and their experience with their brand, and data insights are often the catalyst for big innovative new strategies and optimizations.
But data is also a sensitive subject. Now more than ever, marketers need to know how to leverage data to ensure their marketing strategies benefit from the best insight and targeting available, while also staying compliant and maintaining the integrity of their brand. Because as we all know, there are many innovative and responsible ways to improve mobile marketing that won’t anger the GDPR gods or turn into a Black Mirror episode.
We asked mobile marketers to share their most powerful data insights and how they use them to improve their app marketing. Read their answers below and find out how successful app marketers are tracking metrics and using first and third-party data to attract new app users, and improve the experience for their existing user-base.
How to use Data to increase app users
From the time when Sam worked for Yousician: “One of the best uses of data I’ve seen is to build out and optimize multi-touch marketing funnels and maximize the chances that potential users will install an app. Many in the Gaming verticals do this very well. They use multiple creatives to introduce the product to the user and sell them with a preview of the fun. They might run a simple explainer video for the user to learn how the game works. Later they re-target those who viewed the first video with a hype video that builds more excitement for the game, and keep building the funnel out as needed.
The importance of data comes into play when deciding what order to show the users the creatives, what message to push, and tracking the steps combined CPA and the time between touchpoints. Every step needs to be optimized based on data to make sure you’re spending your budget on each step effectively.
In consulting, I’ve often seen the opposite of good data usage. I’m often surprised at how little data some companies are using to allocate budget or optimize their campaigns. Non-cohorted data, no MMP, no country-level data, etc. It’s scary to think about how wrong things could go without a clear picture of what marketing dollars are doing. With so many cost-effective tools available, there’s no reason not to use as much data as possible to guide marketing decisions.” – Sam McLellan, Head of Growth at Yousician.
“Data has become the most important factor when making decisions about our games; no matter which stage we’re talking about: acquisition, optimization, re-engagement, development of new features, etc. So that means that there are many ways in which we are using data on a daily basis to improve our Mobile App marketing. If I had to pick out one data point, and the game or app already had decent KPIs, I would say that for running User Acquisition campaigns, calculating an accurate and trustful LTV is key. We must not forget that UA is probably the most controllable way to ensure a constant flow of users.” – David Cremades, CMO at From The Bench S.L.
From the time when Arturo worked for Headway:“For me, the most impactful time to use data insights is during audience targeting for UA. Mobile ad serving capabilities have improved, and it is now possible to very accurately specify who you want your ads to reach. The right combination of creative, publisher, time of day, geo, message sequence, etc., ultimately determines the success or failure of a particular ad to convert.
Keeping track of the data of all those moving parts is what allows marketers to identify which combination of factors is working best, and optimize their targeting strategies. Each time a targeted campaign is run, marketers can refine the audience based on which channels delivered the highest value users, and the characteristics of the users who converted. Essentially creating a data feedback loop that constantly optimizes targeting based on conversions.
By leveraging audience targeting data and successful conversions, marketers can deliver ads to users with the highest potential to download and use a particular app, in the optimal circumstances. In my opinion, UA targeting should always be data-driven to spot opportunities and allocate spend accordingly.”– Arturo Camargo, Head of Growth in Latam at Headway.
From the time when Michael worked for eCooltra: “The best usage of data we have implemented lately was to begin working with an RFM model (recency, frequency, monetary value model). To use the model you must segment your users into different groups according to their behavior over time. This makes it possible to automate strategic outreach and ensure users get different content depending on where they are in the funnel.” – Michael Jessen, Mobile Marketing Manager at eCooltra.
From the time when Pau worked for Innogames: “The most powerful data for performance marketing is definitely user-centered data, and Facebook is the best platform for leveraging it successfully. For MAI (Mobile App Installs) Facebook has several data insight products in place like Lookalikes, International Lookalikes or Value-Based Lookalikes, that have proven time after time to be worth their higher CPMs because of the value they deliver.
I have been following with interest the evolution of new Identity DMPs that try to replicate Facebook’s success but thus far we haven’t used any yet. We have used programmatic data insights for cross-selling or upselling but the scale is quite limited and we are looking for strategies that allow us to scale our player base. By using Facebook’s data insights we’re able to scale our campaigns and reach many more users regardless of their country.” – Pau Quevedo, Online Marketing Manager at Innogames.
From the time when Lorenzo worked for Free2Move: “I am very fascinated by the incrementality measurements that the mobile world is increasingly taking into consideration – even if I haven’t had the opportunity of experimenting with it directly.