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Page 1: Becoming Data-driven - Machine Learning @ XING Marketing Solutions

Becoming Data-drivenML @ XING Marketing Solutions

Big Data World Frankfurt

November 29th, 2017

Dr. Stefan Kühn

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werben.xing.com

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This talk is about

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werben.xing.com

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Create ads @ www.xing.com/xas/

Native Advertising• Different placements

• Multiple Ad Types

• Events• Groups• Jobs• User• BusinessPages• Websites• Video• …

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AdManagerFrom Heuristics to Algorithms

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Second Bid Auction

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We focus on• Relevance

• Predict expected Clickrate = eCTR

• Revenue• Predict expected

Revenue = eRPI

• Features• Targeting• Ad-related data• User-related data• Time• Channel• …

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Heuristics – Naïve Bayes (not quite)

Why?• Easy to implement

• No theoretic background needed

• No additional toolstack

• Can be implemented by Software Engineers

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Why not?• Hard to optimize

• No theoretic guarantuees

• Toolstack limited w.r.t advanced methods

• Cannot be re-used by Data Scientist

Imprecise predictions lead to suboptimal business decisions

“Visible” costs are low “Invisible” costs are higher

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Algorithms – Collaborative Filtering

Why not?• Significant implementation effort

• Complex theory

• New and unknown toolstack requires training and learning time

• Cannot be implemented by Software Engineers alone

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Why?• Allows for ongoing optimization

• Theoretic guarantuees are a prerequisite for reasoning, proper evaluation and testing

• Modern tooling enables learning from much more data

• Additional Data Science and Engineering skills enhance the team capabilities in many ways

Short term savingsLong term benefits

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Advanced Delivery Pipeline

Separation of Concerns

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Collaborative Filtering for Recommendations

Predict approximate scores for empty spots based on similarities between users and items

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Matrix Factorization

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Short term savings versus long term benefits

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Revenue per Impression [RPI]

Before ADP Start of ADP ADP today

+11%

+30%

• Development time 4 month (small team)

• In production for 4 months now and more to come

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AdManagerMore to come

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Algorithms – The Next Level

More Data = New Features• Natural Language Processing - Matching user

interests and ad descriptions

• Social Network Analysis - Recommendations based on interactions in the user’s network

• Interaction with other content

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New Methods = Better Predictions• Multiple methods in parallel (Multi-Armed

Bandit)

• Multiple theoretical approaches (LogReg, Tree-based)

• Ensembles

New data dimensions require Big Data solution

New algorithmic dimensions require powerful distributed computing system

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Algorithms – The Next Level

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New data dimensions require Big Data solution

New algorithmic dimensions require powerful distributed computing system

We are already prepared for that!

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Thank you for your attention.

www.xing.com

Dr. Stefan KühnSenior Data Scientist – XING Markting Solutions [email protected]/profile/Stefan_Kuehn46