How Baidu’s Task Incentive Design Boosted Mobile App Growth

Introduction

Mobile internet experienced rapid growth from 2012 to 2016, but the pace has slowed significantly. According to the 2022 China Mobile Internet Development Report, by the end of December 2021 China had 1.029 billion mobile internet users, an increase of 43.73 million year‑over‑year, indicating a deceleration in growth. In this environment, maintaining continuous product user growth is a major challenge for business teams.

Background

Against this backdrop, Baidu Speed version clarified its product positioning, focusing on low‑tier, earnings‑sensitive users and promoting growth through task incentives. Design shifted from pure user‑experience to task‑incentive design. Lacking prior experience in growth and incentive systems, the team explored and, after a year of validation, established a complete methodology for integrated task‑incentive design and visual‑language upgrade.

Goal

Implement an integrated task‑incentive design to sustain product data growth. The design is divided into two phases: Phase 1 uses timer‑based tasks for acquisition, and Phase 2 employs refined scenario‑based hand‑off to drive activation.

Phase 1: Acquisition

Through external material placement combined with internal Feed, novel, and video scenes, a universal timer task is used to increase daily active users.

01. Build a user‑growth design model to connect task play‑points and eliminate task breakpoints

Task‑pre value discovery: guide users to claim red packets to start tasks, lower login barriers, and use splash screens, red‑packet pop‑ups, timers, and half‑screen components to shorten the path to login.

Habit‑formation stage: reinforce reward perception by adding timer weight, multi‑state timers, and rich interactive effects, guiding completion through home, search results, and landing pages.

Post‑task stage: link to other tasks, attract users to continue playing, and direct them to the task center for more specialty tasks, enhancing the sense of “earning” and user stickiness.

02. Expand timer coverage through placement and hand‑off

Combine external placement with refined internal hand‑off across home, Feed, search, novel, video, and tool scenes to further increase daily active users. Home guides upward scrolling, Feed timers reinforce reward perception, search prompts multiple searches, novel timers encourage repeated reading, video timers strengthen reward perception, and tool scenes add task entry points.

Phase 2: Activation

When acquisition reaches a ceiling, the design shifts to activation to continuously improve daily active users.

01. Establish a video‑scene experience design approach

Combine interaction with user‑retention curves, applying progressive incentive models at key drop‑off points in video playback. Visual upgrades and gamified play reinforce reward perception, building a scenario‑based task experience.

02. Reconstruct the user‑growth design model

Although the growth objectives remain the same, the design methods differ between acquisition and activation phases. Pre‑task: upgrade red packets to enhance real‑feel cash‑withdrawal, further lowering login barriers. During task: progressive prompts guide upward scrolling and longer watch times, reinforcing reward perception. Post‑task: guide cash withdrawal to build trust, embed additional tasks within videos, and strengthen reward perception to encourage repeat consumption.

03. Upgrade visual language to strengthen reward perception

The new design introduces a unified visual language throughout the task flow, from pre‑task to completion, delivering a fresh user experience. Integrated timer displays real‑time coin earnings, reducing visual noise. Gamified prompts are repositioned to minimize disruption while enhancing video experience. Realistic, non‑gimmick red packets are visually upgraded across multiple scenes. Task pop‑ups adopt a card‑less design with gamified visual elements to increase immersion.

Horizontal Collaboration and Impact

The complete task‑incentive integrated design experience validated on Baidu App’s Speed version has also been deployed on Baidu App’s main client and Haokan Video, contributing to daily active user growth and demonstrating cross‑product synergy and efficiency gains.

Conclusion

This article presents Baidu App’s video growth playbook, detailing the shift from product experience design to task‑incentive design, rapid decision‑making, and multi‑platform rollout. The described methodologies help continuously improve metrics and strengthen Baidu’s ecosystem competitiveness.