How Ganji Reinvented Its Recruitment Platform to Boost User Retention

Changes and Opportunities

After years of growth, Ganji, once a multi‑service lifestyle platform, shifted its strategy to become a vertical recruitment service, aiming for more precise job offers and a richer job‑seeking ecosystem. The transition reduced overall user traffic, and the seasonal nature of recruitment created a retention challenge.

Design Strategy

Analysis with the product team identified three main reasons for user churn:

Inability to find suitable positions due to incomplete user profiles.

Job‑seeking activities moving offline after interview scheduling.

Users leaving the platform once the job‑search phase ends.

To counter these, Ganji defined three “driving forces” for retention: precise job matching, connection‑focused online job processes, and social linkage for post‑employment engagement.

Precise Job Matching

Blue‑collar users often do not create full resumes, making it hard to match them with jobs. Ganji weakened the resume concept and collected job‑intent data throughout the user journey, using scenario‑based and question‑driven forms to build richer profiles without forcing users to fill a traditional resume.

Key tactics include:

Embedding short “job‑intent” questionnaires during registration and while browsing listings.

Transforming information‑gathering into interactive Q&A sessions.

Breaking the resume into small, task‑like subtasks that gradually collect user data.

Connection‑Focused Online Job

Ganji merged the messaging module with the job‑process module, creating a unified flow that covers contact, invitation, interview, feedback, and completion. Unified card structures reduced cognitive load and kept users within the platform during interview stages.

New interview formats such as video and AI‑driven interviews were integrated, and the upgraded messaging system educated users on these features, encouraging adoption.

Social Linking for Retention

Recognizing that blue‑collar workers rely heavily on trusted acquaintances, Ganji launched a “People Circle” social ecosystem based on three relationship dimensions: peers, same‑city, and hometown connections. Content is recommended according to these relationships, fostering natural interaction.

Social features include:

Relationship‑driven content feeds that increase relevance.

Conversation bubbles that prompt likes, comments, and posts using familiar peer voices.

Network effects that extend platform usage beyond the job‑search phase.

Conclusion

After implementing these design decisions, Ganji will monitor data to quantify the impact on user retention, continuously refine activation mechanisms, and aim for dual growth in user activity and lifecycle length.