Mobile attribution has become the focus for companies wishing to invest in and optimise growth for their mobile apps. We look at what advertisers need to consider for mobile shopping, fraud and why mobile attribution is important.
Mobile Shopping Insights
As the consumer ecosystem, and consumer demand continues to grow, brands have emphasised mobile commerce, on-the-go functionalities and being at user’s’ fingertips whenever the need to buy arises.
App Annie predicts that 75% of all eCommerce transactions will be made on mobile by 2021 (1). Retail apps are leading the mobile charge, with 5.7 billion shopping app downloads in 2018, 50% more than in 2015, according to Apptopia (2). eMarketer predicted that increased mobile usage would result in $270 billion of revenue in 2019, growing to $510 billion in 2022 (3). Roughly 70% of that revenue occurs in-app.
Given the scale of opportunity now available for retail brands, there are important aspects of mobile attribution, measurement, and marketing analytics to consider which are unique to shopping apps.
Granular In-App Event Mapping
Effective user acquisition, engagement and retargeting are all driven by audience segmentation and optimisation based on rich in-app events. These add parameters which map out ideal user behaviour into marketing goals and related KPIs.
Here are two examples to illustrate the difference between standard in-app events versus rich in-app events:
What was once simply a “purchase” is now a content type (e.g. red dress or Bluetooth speakers), a specific content identification, quantity, currency, and even a revenue amount. All these parameters can then be used to target audiences who behave similarly to current users to reach different demographics, regions, or valued purchasers.
Fraud in Shopping: What Marketers Need to Know
It is believed that campaigns modelled on cost-per-action (CPA) experience little to no fraud due to a) having no install-focused incentive and/or b) the difficulty of generating certain in-app events for fraudsters. That is simply not true. We are seeing a significant increase in post-install fraud, as fraudsters simulate in-app activity to bypass fraud protection. Therefore, savvy shopping marketers look at the following measurements:
Postcode Anomalies. It is important to identify order amount anomalies from specific cities or postcodes. When unusual spikes are detected, these often indicate bulk orders from fraudsters in a single location.
Install-to-Purchase Time. Shopping apps typically have standard time limits for installing and completing a purchase (differing across regions depending on internet connection speed and observed anomalies). Less than this standard is cause for suspicion. As each app’s needs are different, however, we recommend using attribution data to understand limits individually and create boundary conditions accordingly.
Retargeting Drives 76% of Revenue Increases for Shopping Apps
With the revenue opportunity of shopping apps so large, retargeting should not be simply considered a luxury, but critical to maximising performance.
Here are three of our top tips for shopping apps to increase customer lifetime value (CLV):
1. Personalisation - Not only for User Acquisition (UA). eCommerce app users now expect customised experiences from start to finish, particularly with the amount of apps available. View and purchase histories are useful for cross-selling or up-selling to lapsed users and deep links can be paired with other in-app event data to reduce shopping cart abandonment rates. Choose ad partners based on the behaviour or intent personalisation they offer and incorporate this process into your marketing routine.
2. Preventative Retargeting. Retargeting campaigns should also function preventatively to keep users engaged so user lapsing does not occur. According to Criteo, users are almost 30% more likely to remain engaged and convert if effectively engaged by a retargeting campaign within the first week after installation. However, preventive campaigns should be limited to engage users without overwhelming them.
3. Reattributed vs. New Users. Understand not only the campaign-level but also the user-level value of your reattribution efforts by comparing reattributed users to new users. The two main quality metrics to measure are average revenue per user (ARPU) and purchase frequency, which are analysed in windows of 30, 60, and 90 days, respectively. This comparison can also be used to determine a retargeting budget.
Given recent national and global restrictions, shopping and retail brands have an unprecedented opportunity to leverage online users across devices. An opportunity still untapped if not measured accurately.
Here are AppsFlyer’s three recommendations for mobile shopping advertisers:
1. Focus on Non-Organic
Australian advertisers should complement their campaigns with paid efforts, as brands use them regularly as part of their growth strategies. In times of digital overcrowding, paid campaigns become key to standing out from the crowd.
2. Winning mobile user retention
Mobile Shopping has significantly increased since the start of the pandemic and e-commerce advertisers are faced with the challenge of retaining those users. AppsFlyer can help through the data we collect on behalf of our advertisers.
3. DIY is costly and riskier
Mobile attribution is extremely challenging for advertisers to achieve by themselves as it involves multitudes of media sources and partners cooperating under one technical framework. Working with a market attribution solution with a proven track record is an easier, safer option.
For more information on the topics above, as well as much more, check out our brand new, comprehensive guide, Mobile Attribution, Measurement, and Marketing Analytics for Shopping App Marketers.
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