从点击到转化：在 Pinterest 构建购物转化候选生成

Introduction

引言

At Pinterest, conversion ads are crucial for matching users with products they are likely to purchase, boosting value for both users and advertisers¹. While conversion actions like checkout or add-to-cart are highly valuable, they are also technically challenging to optimize for. Because they occur offsite, conversion events are significantly sparser and noisier than onsite engagement signals. Historically, Pinterest’s shopping ads retrieval relied on engagement-based models. While effective for driving interaction, this system was not designed to optimize for lower-funnel conversions. This gap motivated us to build a dedicated candidate generation model tailored for conversions, aiming to surface higher-intent products and improve advertiser performance.

在 Pinterest，转化广告对于将用户与他们可能购买的产品匹配至关重要，从而提升用户和广告主的价值¹。虽然像结账或加入购物车这样的转化行为非常有价值，但它们在技术上也很难优化。因为它们发生在站外，转化事件比站内互动信号要稀疏得多且噪声更大。历史上，Pinterest 的购物广告检索依赖于基于互动的模型。虽然该系统在驱动互动方面有效，但并非为优化低漏斗转化而设计。这一差距促使我们构建了一个专为转化定制的候选生成模型，旨在推荐更高意图的产品并提升广告主表现。

We launched our first shopping conversion model in 2023, achieving meaningful wins across both conversion and engagement, including a higher clickthrough rate (CTR). Further iterations in 2025 unlocked even stronger conversion value and improved Return on Ad Spend (RoAS) for our advertisers. This blog post documents our journey building this conversion candidate generation model, from its technical design and challenges to the key learnings of deploying it to our 600+ million monthly active users at Pinterest.

我们于 2023 年推出了第一个购物转化模型，在转化和参与度方面取得了有意义的胜利，包括更高的点击率 (...