Optimizing Credit Loan Advertising Placement: Practices and Strategies from Qifu Technology

Advertising in the credit loan scenario involves a complex chain from media request, decision, bidding, exposure, user click, landing page, and credit assessment, with distinct goals for users, media platforms, and advertisers, making it a multi‑constraint optimization problem.

The platform leverages media tools such as DMP audience packages and real‑time bidding interfaces, building capabilities in audience strategy, plan strategy, and intelligent creative.

1. Audience Strategy – Basic logic and overall architecture focus on decision opportunities at request time, influencing eCPM factors and downstream conversion efficiency. The system constructs a full‑funnel data pipeline to support rapid strategy iteration.

2. Model & Data Capabilities – Real‑time decision making for billions of devices relies on third‑party data products and internal data systems, combining attribute and behavior features, large‑model content understanding, and embedding representations to feed predictive models.

3. Strategy Capabilities – Includes data foundation, differentiated bidding based on user segmentation, and extensive use of statistical and model‑based fitting for both early‑stage and sparse downstream conversion metrics.

4. Plan Strategy – Covers basic logic, mature plan control (risk, quality, potential, poor plans) with rule‑based and model‑based adjustments, and new plan creation leveraging high‑quality creative modeling and AI‑generated material selection.

5. Intelligent Creative – Utilizes large models and AIGC for rapid material generation, combining AI tagging, model‑based creative evaluation, and iterative feedback loops to improve material quality and conversion.

The overall system integrates data platforms, modeling platforms, variable platforms, decision engines, and experiment platforms to enable fast, data‑driven optimization of credit loan advertising campaigns.