pla @ ebay

Product Listing Ads @ eBay

Jun Yu

eBay Marketing Science

Oct 2016

About Me

Applied research tech lead in eBay paid search and eBay Partner Network.

• Ph.D. in CS from Oregon State University and my research focuses on Probabilistic Graphical Models.

• Applied researcher @ eBayo Seller risk management & defect predictoro Paid search o eBay Partner Network (eBay affiliate program)

• Passion for data (a lot of data) and using machine learning to make sense of data.

• 15+ publications in top ML conferenceshttps://www.linkedin.com/in/junyuorst

Paid Search & eBay Partner Network

TextAds

ProductListingAds

ePN

Product Listing Ads (PLA)

Our Mission

Drive more traffic to eBay by showing our best inventories on Google search result page.

• Traffic (click and conversion)

• Revenue

• New Buyers and Reactivated Buyers

• Brand awareness

• …

Challenges

• Marketplace datao Semi-structured o Highly customized o eBay scale

• Data is extremely sparseo CTR and CVRo Dynamic inventory

• Fast-changing marketo Competitiono Trending

Antique clock

iPhone7 jet black 128GB

Challenges

All LiveListings

Listingswithimpressions

Listingswithclicks

Listingswithconversions

• Marketplace datao Semi-structured o Highly customized o eBay Scale

• Data is extremely sparseo CTR and CVRo Dynamic inventory

• Fast-changing marketo Competitiono Trending

Challenges

• Marketplace datao Semi-structured o Highly customized o eBay Scale

• Data is extremely sparseo CTR and CVRo Dynamic inventory

• Fast-changing marketo Competitiono Trending

Workflow

Google/Bing

ImpressionClickCost

eBay

Filtering Grouping Bidding

BidsFeeds

Traffic

PLA Model

Budget

RevenueConversion

PLA Model: Filtering

Filtering Grouping Bidding

PLA Model

• Seller Risk Filter

• High Price Filter

• Google/Bing restrictions

PLA Model: Grouping

Filtering Grouping Bidding

PLA Model

Group listings based on their similarities:

• Estimated Revenue per Click (RpC)

• Estimated Cost per Click (CpC)

• Product information

PLA Model: Bidding

Filtering Grouping Bidding

PLA Model

The bidding strategy:

• Estimate the relationship between cost and revenue

• Allocate budget to each group to maximize overall ROI

• Adjust the bid to hit the budget

Evaluation

10% Listings

10% Listings

80% Listings

Control

Treatment

Production

Lift ± CI ROI

A/B Testing Framework

Champion

Challenger

Other Bidding Optimizations

• Device-level bidding

• Geo bidding

• High frequency bidding

• Item image optimization

• Item title optimization

• Retargeting