Analytics Toolbox - #SMX West 2015 - Benjamin Spiegel

SMX WEST, SAN JOSE CA

What's In My Analytics

Toolbox

Benjamin Spiegel

Managing Partner, VP InnovationCatalyst / GroupM

@nxfxcom

searchmarketingexpo.com@nxfxcom

#SMX #32a

The data we used to look at was simple and mostly structured,

1-dimensional and sources were few

• Log Files

• Web Analytics

• Link Analytics

• Banner Clicks

• Affiliate Platform

• Sales Data

THINGS USED TO BE SIMPLE


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ONE DIMENSIONAL

Date/Time Dimension Metric

January 1st 2001 Source = “Yahoo” 120 Visits

February 15th 2002 Link ID = 12 75% Conversion rate

April 10th 2003 – 15:11 PM Keyword = “Search Agency” 5% Click Through Rate

June 2nd 2005 – 11:09 AM EST Product = “Shiny Shampoo” $12

6/6/2005 Direct 5:12 avg. Visit time


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MULTI DIMENSIONAL


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MULTI SOURCE


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Evolving - 1+1=5

This is leading to new

metrics and lenses

• View-through rate

• Organic Lift

• Response Rate

• Open Rate

• Klout Score

• Social Shares

• Annotation Close rate

• …


#SMX #32a

2013 TOOLBOX


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Too many tools that

just did not fit together

• Text Analytics

• Competitive Data

• 1st/2nd and 3rd party data

• Panel

• Real-time

• Owned vs. Earned

• Media Data

• Impression Data

• Offline Data


#SMX #32a

Putting Business Questions first!

• Is my media managed effectively?

• What are my competitors doing?

• Am I playing in the right arena?

• Does my Innovation have a purpose?

• Do I need to increase investment?

• How can I get more for less?

• Is my content connecting with consumers?

• Simply put: Am I winning?

2014 RESET – OUT WITH THE TOOLS


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In this world, the focus of our toolbox is

• Enabling Innovation through discovery

• Strategic technology investments

• Broader data access for everyone

• Leveraging technologies

• Injecting IP / Unique Data

• Leveraging 3rd and 2nd party data

• Visual Storytelling

• Enabling non-IT solutions


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NEW PRIORITIES


#SMX #32asearchmarketingexpo.com@nxfxcom

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OUR APPROACH

Insights &

Action

Acquisition

Modeling

Visualization

Management


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We were looking to acquire data from • Multiple databases

• Flat files

• Web APIs

• Unstructured

• Real-time

• Behavior

• Models

• Text (Lots of if)

• Binary

AQUISITION

Insights &

Action

Acquisition

Modeling

Visualization

Management


#SMX #32a

We want to leverage

• Machine learning

• Predictive

• Linguistic

• Regression

• Clustering

• Sentiment

• Behavioral

MODELING

Insights &

Action

Acquisition

Modeling

Visualization

Management


#SMX #32a

We really wanted to enable

• Visual storytelling

• Simplification with pictures

• Easy discovery

• Insights creation

• Reporting

• Dashboards

• Scorecards

VISUALIZATION

Insights &

Action

Acquisition

Modeling

Visualization

Management


#SMX #32a

In order to do all of that we need to

• Aggregate

• Filter & verify

• Combine & merge

• Transform & enhance

• Index & optimize

• Export

• Share and distribute

• Basically ETL on steroids

MANAGEMENT

Insights &

Action

Acquisition

Modeling

Visualization

Management


#SMX #32a

HOW

Can we archive all of this with a single tool? – YES!

Open Source / Free

Multi-Platform (OSX, PC, NIX)

Full ETL Support

Expandable (Java)

Full I/O

Visualizations

Modeling

Machine learning

Flexible pipes


#SMX #32a

KNIME.ORG

• Node Based Platform

• No dev. skills required

• 1000s of Plugins

• Scalable & Flexible

• Build in Support (GA/Twitter etc.)

• SEO/SEM Adapters

• Free ;)

• 100% Innovation!!!

http://knime.org


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KNIME IN 10 SECONDS

Nodes that do things Together they do more

http://searchmarketingexpo.com/west/agenda/


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RESULT FOR AGENDA


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GETTING CREATIVE


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WHAT YOU GET


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GOING FURTHER


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WHAT YOU GET


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ONE MORE


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WHAT YOU GET


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EXTENDING - TRENDS


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EXTENDING – TRENDS - RESULT

http://marketingland.com/google-trend-goldmine-117626


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2 MINUTE SPRINT

My Top 6 Data Sources of 2015


#SMX #32a

1. IMDB EVERYTHING

http://www.imdb.com/interfaces

Raw access to all the

IMDB Data

• Actors

• Crews

• Locations

• Ratings

• Movies

• Reviews

• Tag Lines

• ….


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2. DATA.GOV

http://www.data.gov

116,298 Datasets

• Population

• Crime

• Businesses

• Consumer complaints

• Licenses

• 911 Calls

• Budgets

• ….

http://www.data.gov


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3. WIKIPEDIA

http://en.wikipedia.org/wiki/Wikipedia:Database_download

http://marketingland.com/leveraging-wikipedia-data-deeper-consumer-insights-82320

• Hourly page views

• Location specific

• Device segments

• Change history

• Article graph

• Raw articles

• ….

http://en.wikipedia.org/wiki/Wikipedia:Database_download

http://marketingland.com/leveraging-wikipedia-data-deeper-consumer-insights-82320


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4. SNAP

http://snap.stanford.edu

http://snap.stanford.edu/data/index.html

• 34MM Amazon

Reviews

• 13MM G+ Edges

• 476MM Tweets

• And so much more

http://snap.stanford.edu

http://snap.stanford.edu/data/index.html


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5. SOCIALMENTION API

http://www.socialmention.com/api/

• Blogs

• Videos

• Bookmarks

• Comments

• Events

• Images

• Audio

• Q&A

• Networks

http://www.socialmention.com/api/


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6. COMMON CRAWL CORPUS

https://aws.amazon.com/datasets/41740

• The Internet (541 TB)

• 5 Billion Pages

• Link Analysis?

• EVERYTHING!

https://aws.amazon.com/datasets/41740


#SMX #32a

Analytics Toolbox - #SMX West 2015 - Benjamin Spiegel

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