Using FlockData to power your Recommendation Engine

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©2013-2015 FlockData LLC - All rights reserved TURNING DATA INTO INFORMATION BUILDING GRAPH-BASED RECOMMENDATION ENGINES

Transcript of Using FlockData to power your Recommendation Engine

©2013-2015 FlockData LLC - All rights reserved

TURNING DATA INTO INFORMATION

BUILDING GRAPH-BASED RECOMMENDATION ENGINES

©2013-2015 FlockData LLC - All rights reserved

FlockData is a unified multi-model data integration and information

management platform for information storage and retrieval

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Connections Analytics Timeline

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Graph Search Document

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Graph Search Document

Any data source(s) HTTP RESTful API integration

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Graph Search Document

Any data source(s) HTTP RESTful API integration

©2013-2015 FlockData LLC - All rights reserved

Graph Search Document

Any data source(s) HTTP RESTful API integration

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Graph Search Document

Reports Apps Structures

Any data source(s) HTTP RESTful API integration

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Recommendation Engine

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What is a recommendation engine?An algorithm that:

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What is a recommendation engine?

Incorporates any number of factors about users

Notably including products or services consumed

Leverages multiple related factors: similar products, products bought by similar users, etc

Combines these factors as connections

Returns the most relevant (connected) nodes as recommended products or services

An algorithm that:

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Why build a recommendation engine?

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Why build a recommendation engine?

Original search

Bought together = up-sell

Also bought = up-sell

Targeted ads = cross-sell

Also viewed = conversion

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Why build on graph data?Only need to specify whichtype of relationships to use

As little as 2-lines of query code

Performance: 1M rows —> ~20ms But very little scale effect

10x-1000x faster than relational Fast-enough for real-time performance

Efficient and flexible for expanded use

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Why build on graph data?Only need to specify whichtype of relationships to use

As little as 2-lines of query code

Performance: 1M rows —> ~20ms But very little scale effect

10x-1000x faster than relational Fast-enough for real-time performance

Efficient and flexible for expanded use

Lookalikes

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Graph as the basis for recommendations

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Graph: connect customers + products

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Step by step

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Start with categories

Product Features

Scandi-navian

Family

Living Room

Used in:

Style:Useful

for:

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Map in products

Catalogue

Sofa 2

Product:

Product:

Product Features

Living Room

Used in:

Style:Useful

for:Style:

StudioUsed

in:

20-some-thing

Useful for: Scandi-

navian

Family

Modern

Sofa 1

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Map in purchases

Customer A

Catalogue

Sofa 2

Product:

Product:

Product Features

Living Room

Used in:

Style:Useful

for:Style:

StudioUsed

in:

20-some-thing

Useful for:

BOUGHT

Scandi-navian

Family

Modern

Sofa 1

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Learn characteristics

Customer A

Catalogue

Sofa 2

Product:

Product:

Product Features

Family

Living Room

Used in:

Style:Useful

for:Style:

StudioUsed

in:

Useful for:

BOUGHT

DEMOGRAPHIC

LIKES

Scandi-navian

Modern

Sofa 1

20-some-thing

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Recognize new customer features

Customer A

Catalogue

Sofa 2

Product:

Product:

Product Features

Living Room

Used in:

Style:Useful

for:Style:

StudioUsed

in:

Useful for:

BOUGHT

DEMOGRAPHIC

LIKES

Scandi-navian

Sofa 1

20-some-thing

Customer A

LIKESDEMOGRAPHIC

Family

Modern

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Make recommendations

Customer A

Catalogue

Sofa 2

Product:

Product:

Product Features

Living Room

Used in:

Style:Useful

for:Style:

StudioUsed

in:

Useful for:

BOUGHT

DEMOGRAPHIC

LIKES

Scandi-navian

Sofa 1

20-some-thing

Customer A

LIKESDEMOGRAPHIC

RECOMMEND

Family

Modern