leveraging big data in search marketing by hugh williams

Leveraging Big Data in Search Marketing

Hugh E. Williams

VP, Experience, Search, and Platforms

eBay Marketplaces, eBay Inc.

@hughewilliams, http://hughewilliams.com

[email protected]

WHAT IS BIG DATA?

• Big Data is a buzz phrase

• What is really means is:

– The data won’t fit in Microsoft Excel

– You need other tools (and people?) to work with the data

– You’re processing large amounts of data to find:

• Patterns

• Anomalies and outliers

• Generalizations

• Predictions

• Relative performance

• An holistic customer picture

@hughewilliams #SMX 2

PAID SEARCH AND BIG DATA

• Consider the data you have available for your site:

– Your users’ queries

– Your users’ sessions (what they click on)

– Your users’ purchases (what they buy)

– …

• You could join this data to find what queries your users pose

that lead to which items that they purchase

• You could use this to buy paid search for queries you know

you’re great at, advertising items that your customers buy,

and driving clicks to the items that sell


PAID SEARCH AND BIG DATA …

• You can measure the performance of your campaigns:

– Attribution of sales to paid search

– Incremental GMV from paid search

– Incremental traffic from paid search

– Sessions (or session length) for your users

• You can use this performance data to:

– Change what keywords you buy

– Change the prices you’re prepared to pay

– Change where and what your customers land on


GETTING STARTED WITH BIG DATA

• To be successful in using big data in search marketing, you

need to:

– Have the data in the first place

– Instrument (or “track”) everything:

• Queries, clicks, events, purchases, referers, users, …

– Never, ever throw data away

• Keep the raw data, you need it when you change your ideas

– Cleanse, organize, and maintain your data

– Be able to process the data:

• At scale, at speed, and draw conclusions


BIG DATA AT EBAY

• Vast array of applications at eBay:– Product development

– A/B testing

– System performance

– Fraud and risk detection

– Purchase prediction

– Customer support

– Buyer demand modeling

– Seller intelligence

– Financial performance

– Search Marketing


PATTERNS: QUERY REWRITES

• In 2010, our search engine was very literal: it matched exactly what you

typed

•We’re on a journey to make it more intuitive, so it does a great job of

understanding user intent and finding all of the relevant results

• Idea: Mine our big data, look for patterns, and use these to map words in

user queries to synonyms and structured data associated with items for

sale at eBay

Query RewriteSearch

User Query

eBay Results

Search Query


PATTERNS: QUERY REWRITES …


HOW DO BUYERS PURCHASE THE

PILZLAMPE?

• It turns out, they one of a few things:

–Type pilzlampe, and purchase

–Type pilzlampe, … , pilz lampe, and purchase

–Type pilzlampe, … , pilzlampen, and purchase

–Type pilz lampen, … , pilzlampe, and purchase

–…


PATTERNS: QUERY REWRITES …

• From our big data mining:

– We automatically discover that pilz lampe and pilzlampe are

the same

– We also discover that pilz and pilze are the same, and

lampe and lampen are the same

• From these patterns, we rewrite the user’s query pilzlampe as:

pilzlampe OR “pilz lampe” OR “pilz lampen” OR pilzlampen

OR “pilze lampe” OR pilzelampe OR “pilze lampen” OR

pilzelampen


ARE QUERY REWRITES EASY?

• Nothing is easy at scale

– Incorrect strong signals:

• CMU is not Central Michigan University

• Mariners is not the same as Marines

– Context matters

• Correcting Seattle Marines to Seattle Mariners is

(generally) right

• Denver Nuggets is not Denver in the Jewelry & Watches

category


Hugh E. Williams

VP, Experience, Search, and Platforms

eBay Marketplaces, eBay Inc.

@hughewilliams, http://hughewilliams.com

[email protected]

leveraging big data in search marketing by hugh williams

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