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Dynamic Remarketing – A Great Tool to Re-Engage with Your Customers Share via

Mobile app users are considered more valuable shoppers than mobile web users because over 71% of mobile sales are in-app today. App users browse more products and convert at a higher rate, generating more revenue, creating tough competition among mobile app marketers to remain relevant and keep users engaged with their app. In app retargeting, also known as remarketing, is what most brands rely on to stay visible to lost users and acquiring new ones.

How App Retargeting Can Help Brands

App retargeting campaigns are meant to focus on users who’ve previously shown interest or interacted with your app; these could be the uninstalled users or those who visited the landing page but didn’t download the app. Multiple studies show that a user typically deletes an app in 5-6 days after the last use; therefore, giving brands a week to develop and deploy an app retargeting strategy. Remarketing not only drives in-app activity but also increases customer retention rate and lifetime value (LTV). Brands can also use the strategy to boost cross-portfolio retention, i.e., attract current or past users to browse other apps in the collection.

Dynamic vs. Static Retargeting

Dynamic and static retargeting are two popular marketing and advertising tactics that effectively target lost users and help Brands acquire new ones. Static retargeting is mostly used by Brands to broadcast a consistent message across a wider audience, with a predefined creative; dynamic remarketing uses predictive models to create personalized offers, product recommendations, etc., where ad creatives are automatically optimized at the user level. Dynamic remarketing re-engages users who forget items in their shopping cart or have an objective to complete in a mobile game.

In-App Retargeting with Machine Learning

Businesses use Machine Learning (ML) to analyze their existing user data to identify unengaged audiences and trigger remarketing ads to prioritize certain in app conversion events. Algorithms deployed by ML helps predict user behavior, optimize creatives, and boost profits to trigger ads with in app personalized messages. Businesses can use the ads to target anything from reinstalling an app to registering for an in-app account, completing an in-app purchase, or even completing a certain level in a game. Marketers can prioritize these re-engagement campaigns based on the value a particular user will add to their business.

Re-Engage Audience with Personalization

Dynamic remarketing is a customer engagement digital solution wherein brands can optimize mobile app retargeting campaigns by using deep links, personalized content, creating quality creatives, focusing on user retention, and monitoring ad metrics. Deep links aim to increase conversion rate by driving a new user straight to a specific location within the app. It is specifically used to target users who haven’t installed the app. Personalized content is the key to re-engage the in-app audience as it helps enhance the reach and conversion rates. A brand can personalize a user’s experience by displaying exact products or other recommendations by monitoring their in-app activities. This works great with brands who wants to remind a user about their abandoned shopping cart.

Why In App Retargeting

The internet is crowded with ads, with over 10,000 ads being displayed to a consumer in a day. This gives rise to the need for a brand’s ad to stand out from the rest. Therefore, it is crucial to work on the quality of creatives for mobile app retargeting ads. Studies of other brands using these tools show that the app retention rate decreases within the first four weeks of using the app; therefore, making it critical to retarget new users regularly to remain engaged with the app.

Most gaming platforms or those selling physical products who have deployed dynamic retargeting correctly, have seen significantly improved Return on Ad Spend (ROAS). Segmenting users helps in targeting more specifically and chances of conversions are higher than random targeting. Most brands leverage these tools to follow a user’s in-app activity, including the type of purchase, location, etc., to bring back users, maximize LTV, and generate more revenue.

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