As the consumer ecosystem, and demand from shoppers, continues to grow, brands have emphasized mobile commerce, on-the-go and at user’s fingertips whenever the need to buy arises.
Proof of this growth, App Annie predicts that 75% of all eCommerce transactions will be made on mobile by 2021. The use of retail apps is leading the mobile charge, with 5.7 billion downloads of shopping apps in 2018, 50% more than in 2015, according to Apptopia.
It was also predicted that increased usage would lead to $270 billion of generated revenue in 2019, and only growing to $510 billion in 2022, according to eMarketer. Note that 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 that are unique to shopping apps.
For this purpose we have created the industry’s most comprehensive guide aimed exclusively for shopping app marketers, which you can download by clicking on the strip below:
Granular in-app event mapping
Effective user acquisition, engagement, remarketing – all are driven by audience segmentation and optimization based on rich in-app events, which add layers of both available and measured parameters that map out ideal user behavior into marketing goals and related KPIs.
Take a look at some of those the savviest mobile commerce marketers are measuring and optimizing:
Now, let’s look at two examples to illustrate the difference between standard in-app events versus rich in-app events:
What was once simply a “purchase” now becomes a content type (e.g. red dress or bluetooth speakers), a specific content ID, quantity, currency, and even a revenue amount.
All of these parameters can then be sliced and diced to target audiences who behave similarly to current users in order to reach different demographics, regions, or valued purchasers.
Fraud in shopping: What marketers need to know
It is believed that CPA-modeled campaigns 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 simply is not true.
We are seeing a significant increase in post-install fraud, as fraudsters simulate in-app activity in an attempt to bypass fraud protection.
Therefore, savvy shopping marketers look at any and all of the following measurements:
Imagine that a marketer is paying $5 for each order that is placed in their app. In CPA fraud, an ad network places an order, receives the CPA payment, but later cancels the order. Unfortunately, this behavior is legitimate, since most eCommerce platforms allow cancellations within a certain period if clients are not satisfied or if the product is damaged, etc.
Since cancellation rates are usually steady for most apps, higher rates from specific media sources or site IDs typically signal that orders are not genuine and only exist to collect CPA payouts.
To minimize damage, shopping app marketers should negotiate a penalty clause for networks in lieu of fraudulent activity directly in the contract.
Zip code anomalies
It is also important to identify order amount anomalies from specific cities or zip codes. When such spikes are detected, these often indicate bulk orders from fraudsters in a single location.
Shopping apps typically have an acceptable limit in the conversion time between install and purchase. Less than this standard is cause for suspicion. Because each app’s needs are different, however, it is suggested to use attribution data to understand that limit on an individual basis and create boundary conditions accordingly.
Remarketing drives 76% revenue increase for mobile shopping apps
With the revenue opportunity of shopping apps so large, it is not simply a luxury, but mission-critical to remarket users for maximum performance.
Why are shopping apps able to drive LTV uplift with remarketing?
Here are three of our top tips:
- Personalization – Not Just For UA. eCommerce app users now expect customized experiences from start to finish, especially with the scale of apps available. For cross-selling or upselling lapsed users, marketers can use purchase or view histories. Deep links can be paired with other in-app event data to reduce shopping cart abandonment rates. Lastly, ad partners should be chosen that offer behavior or intent personalization and make this process part of your marketing routine.
- Preventative remarketing. Remarketing campaigns should also function preventatively to keep users engaged before the possibility of lapsing occurs. According to Criteo, users are nearly 30% more likely to remain engaged and convert if effectively engaged via remarketing campaign within the first week after install. However, also make sure preventative campaigns are limited in order to engage users without overwhelming.
- 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. There are two main quality metrics to measure, ARPU and frequency of purchases, which are analyzed in windows of either 30, 60, and 90 days, respectively. This comparison can also be used to determine remarketing spend.