How Promoted Works
How Promoted ranks your content and what the integration looks like
Introduction
Promoted.ai optimizes marketplace search, feed, and native ads for an extra 5-9% revenue per user. Each marketplace has unique needs, and Promoted offers a variety of options to accommodate your own platform. Promoted’s advanced model builds on top of your existing search and discovery stack — not instead of it — so results are always incremental and leverage any existing investments. Promoted's surfacing optimizations increase revenue, relevancy, and engagement with extremely low latency data logging, so buyers and sellers will have an improved experience without sensing any changes in the platform. Promoted encrypts your data, and does not own or sell any of your data or intellectual property.
Promoted listings. In search and discovery, promote the best listings at the top in real time, by leveraging Promoted's search ranking ML while protecting the user experience with ad quality controls.
Search ranking. Time-tested strategies like A/B testing reveal increases in gross sales, conversions, profits, new seller activation, and other customizable, long-term business objectives.
Deep introspection. An unparalleled ML data-centric view into how search ranking works to understand what is relevant, what is most profitable, what is promoted, and why, avoiding bugs before they happen.
How Promoted ranks your content
The steps below summarize our system, and for even more detail, see the next section for a comprehensive example using a current Promoted client.
- You will fetch and send hundreds of candidate response items to Promoted for selection and ranking. Along with the items, you will send all metadata, including any ranking, quality, relevance, or personalization scores. Promoted incorporates all of your existing signals into its own model using model stacking.
- Promoted’s heavyweight machine learning scores and chooses among these items. Our efficient C++ and Flink systems combine millions of signals extracted from your data, user engagement metrics, in-house or vendor scores, item metadata, and contextual information, like location, time, and season. For ads, this includes computing insertion bids for different ad optimizations (e.g., CPC) to be used in pricing. Our systems are open and source available.
- Using Blender, Promoted accounts for specific filtering rules, item diversity, business objectives (e.g., optimizing profitability), and ad load and quality controls (if applicable), to choose an optimal presentation of organic listings and ads.
- Promoted logs and returns the results to your in-house platform to display just as if your existing retrieval system returned them. The only change to the end-user's display or experience is that results will be better and more relevant. Promoted does not change your UI.
![Process of ranking and displaying results for a user's search query, with Promoted](https://files.readme.io/90305dd-image.png)
Process of ranking and displaying results for a user's search query, with Promoted
Integration
- Promoted’s team will help you integrate with Promoted’s performant SDKs or APIs.
- You'll log existing ranking, engagement, and content data to Promoted.
- Promoted’s system optimizes ranking using our advanced model, including Blender, our internal ML tool that combines metrics and outputs an optimized ranking order.
- Promoted's model will be deployed to users over time and undergo thorough A/B testing to prove impact. You'll gain insight into how Promoted optimizes listings through Introspection and Feature Importance Reports. Your search, recommendations, and ads are now dramatically better.
Updated 10 days ago