Predictive Analytics: Executive Primer

Ryan WithopLead Predictive Analytics & Product StrategyYouSendIt.com

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YouSendIt

Online, mobile, desktop solutions for sharing files that are too big for email

Basic level service – free for majority of usersPremium service – expanded file size / storage capability for monthly or annual recurring costEnterprise service – Multi-seat, Direct Sales

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Ryan Withop

Lead Predictive Analytics at YouSendIt

Who are our best customers? What actions lead to paid subscriptions?

Previously founded Dash Media, song recommendation engine for digital radio

What song is the best match for you right now?

@RyanWithop

(The opinions expressed here are my own, and do not necessarily reflect the opinions of my employers.)

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What is Reporting and What is Predictive Analytics?Reporting:

What happened?

Predictive Analytics: Which users might react to a given input?

Ok to raise price

Likely to cancel in 30 days – win back?

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Examples of Reporting vs Predictive Analytics

Reporting: Is that peak in registrations due to my external ad campaign last week?

How much revenue did we see this quarter?

Predictive Analytics: Who is likely to register in response to my ad campaign?

How much revenue could I expect if I target a specific group?

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What can you do with Data Mining? (Predictions)1. Decision Trees -> Business Rules, Scoring

ex. If you save 4 movies and came from this channel, you will convert at X%.

2. Clusteringex. What people/companies acting like this company we closed?

3. Time Series and Sequence Analysisex. User went to this page then this page, so serve them an ad for this.

4. Anomaly Detectionex. Who are the early adopters, heavy users, subscribers, spammers?

5. Market Basket – Association Analysisex. People who buy these products (or anything together) also buy these

6. Social Network Analysisex. Which groups are collaborative? Which are fraudulent?

Text Mining – Identifying brand sentiment, topics, clustering usersAbc

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How has Predictive Analytics been used at YouSendIt?Users from SEM entry points, in specific industry, who send a

professional file on Day 0 had 10x likelihood of paying

People who use “save” feature only once act like other non-payers

Moving users from web to apps -> 20% increase in lifetime value

Spammers / Scammers high usage indicate fraudulent payments

People who expired their files manually, also used Password Protection features

These users are at center of network - keep 10 users subscribing

Sales comments with “individual account” mentioned have higher likelihood of upsell/consolidation of seatsAbc

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VisionYou have a right to know which user has the highest likelihood of responding to what message, and what time

Predictive Analytics can automate that selection

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Technologies & Methods for Further Research

IBM SPSS Modeler – predictive algorithms with solid user interface and text ontologies

R – free, open source, command line predictive algorithms

NodeXL – Social Network graphing

ManyEyes – word visualizations

Python – open source programming language, good data libraries – easiest to write with

Neural Networks – algorithms similar to networks in brain

Ensemble models – combines the best of each algorithm into a super algorithm

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More Resources for Starting in Predictive AnalyticsCoursera

“Machine Learning”, Andrew Ng, Stanford Professor“Intro to Data Science”, Bill Howe, University of WA

Practical Text Mining by Andrew Fast, PhD

www.statsoft.com/Textbook/Data-Mining-Techniques

Job Titles: Data Scientist, Data Modeler, Data Mining, Predictive Analytics

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Questions?

@RyanWithop