Day 2, session 10, benjamin spiegel

#ID2013

DRIVING SEARCHWITH BIG DATA

Benjamin SpiegelDirector, Search Operations

#ID2013

Who am I?

Benjamin SpiegelDirector, Search OperationsCatalyst Online

Twitter: @nxfxcomEmail: benjamin.spiegel@groupm.comURL: www.catalystsearchmarketing.com

Likes• Search• Analytics• Data• Caffeine

Dislikes• PowerPoints• Presentations• Public speaking• Plus…

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ORGANIC PAID SOCIAL

Data Silos

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Data Sources

and many more…

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So What Can You Do?

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API Process1. Determine the data sources

– Translate Business needs into KPIs and determine who has the metrics

2. Build connecters & adapters– Develop automated collection methods to collect the raw data

3. Store and aggregate the data– Choose a flexible storage and aggregation method to manipulate and prepare the data.

4. Visualize & explore with BI Tools– Connect your data to a visualization / BI Tool do filter, segment and analyze.

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So What Does That Mean For Me?

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Key Phrase Strategy

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How Can We Make That Better?

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rganic

Rank

Current CPC

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Lets Dig A Little Deeper And Let’s Size Them By

Interest

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Current CPC

Org

anic

Rank

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Okay, How About Coloring Them By Bounce Rate?

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Current CPC

Org

anic

Rank

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How About Incorporating Google Trend Forecast With

Icons

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Current CPC

Org

anic

Rank

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Current CPC

Org

anic

Rank OrganicPaid

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BrandX Wanted to create consumer connections with

50% of all searchers.

They Are Currently connecting with only 15% of

all searchers

Case Study

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abcnews.comwikihow.comyoutube.com

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So What Do They All Have In Common?

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Search Boxes

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Opportunities

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So how do we decide where to play?

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Gave Us 67,000 Unique URLsGave Us 67,000 Unique URLsGave Us 67,000 Unique URLsGave Us 67,000 Unique URLs

1. We Took ~4000 Key Phrases And Collected The Top 20 Rankings For Each

Term

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2. We Then Collected Audience Data For All Keyphrases From Compete, Comscore, And DoubleClick

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3. We Analyzed The Sentiment Of All The Discovered URLs

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4. Analyzed And Organized Inbound Links By Traffic, Quality, And Authority

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5. This Leaves Us With Over 63 Points Of Data Per Domain

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6. We Then Filtered The URLs To Remove Sites That• Did not align with the target audience• Had low engagement• Could not be influenced• Have low social or link authority

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Referral pages per Visit

Vis

ibili

ty (

Avg R

ank

| #

R

esu

lts)

7. This Left Us With Around 170 Highly Engaged & Highly Targeted Sites.

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Referral pages per Visit

Vis

ibili

ty (

Avg R

ank

| #

R

esu

lts)

BrandX Is Now Visible On

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Based On All Primary Keyphrases, ~60% Of All Results Contained Brand Mentions For Our Brand.

Result

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Thank you!Benjamin Spiegel

Director, Search Operations