The global market has witnessed the entrance of a growing number of short video app platforms developed by Chinese developers, which, in fact, are also facing challenges from local competitors. Bigo LIKE, a short video app originally centered around music, is no stranger to Chinese users- but what’s worth attention is its “go abroad” strategy. LIKE has gained popularity in 187 countries around the world and is a Top 3 short video app platform in India.
Upon entering the India market, LIKE cooperated with 9Apps to help acquire a large number of users with a high retention rate. With huge potential, the India market has its own unique characteristics. Young mobile Internet users, who are target users for LIKE, don’t always have access to Google Play. Thus, to extend the app’s user coverage and target those who don’t use Google Play, 9Apps’s APK promotion was used as a solution.
During its early stages, the promotional campaign failed to increase the user retention rate. Since 9Apps couldn’t access its user behavior data following the download of the app, the promotions team found it difficult to form an effective optimization strategy and plan.
ⅰ. Spot optimization
AppsFlyer’s postback data reports containing install data from 9Apps helped to provide exact conversion data for further optimization strategies. In addition, AppsFlyer’s dashboard enables 9Apps to access retention data reports regarding acquired users upon the authorization of the advertiser (LIKE), analyze the data, and deliver an optimization plan.
To analyze seed users’ behavior, the optimization team ran a series of ad placement tests and A/B tests over a set period, continuously analyzing tests results, and optimizing advertising placements and other effects.
As an example, during tests and continuous data monitoring, the optimization team noticed that the conversion rates of relevant “in-video” ad placements were higher than others.They then placed ads with exposure on the homepage that matched relevant “in-video” category ads to reach more relevant users.
ⅱ. Targeting Optimization
AppsFlyer provided multi-dimensional user data, such as network status, carrier, language and device model. Through cross-matching analysis, 9Apps helped LIKE understand the correlation between certain user features and promotion performance. For example, users with a stronger network connection are more likely to show interest in content provided by LIKE.
With this knowledge, the promotions team adjusted their targeting model by optimizing ads to target users with certain features, thereby further improving the efficiency of the promotion.
ⅲ. Increased Users Through Look-alike Modeling
The 9Apps team established a multi-dimensional user profile model from user data acquired through AppsFlyer postback, including mobile device data, user attributes, user behavior data, etc. After studying user profiles and models, the promotion team gained an understanding of user characteristics and then leveraged an extended promotion period to find more look-alike users with similar characteristics. Through user feature analysis, the team noticed that LIKE users share a broad range of characteristics with users of e-commerce, traveling and entertainment apps. The promotion team decided to target those user groups and effectively increase the efficiency of the promotion.
The Day 2 retention rate increased by 3-5% following ad spot optimization
The Day 2 retention rate increased by 10% following targeting optimization
9Apps and AppsFlyer both provided significant support during Bigo LIKE’s campaign to enter the global market. The multi-dimensional data reports provided by AppsFlyer and professional support from 9Apps helped LIKE to gain a large number of target users in the local market.