Benjamin Spiegel discusses optimizing search operations using big data by identifying key data sources, automating data collection, and employing visualization tools. He illustrates a case study where audience data and site analysis led to improving brand visibility for key phrases. The approach resulted in targeting highly engaged websites, significantly increasing brand mentions in search results.

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DRIVING SEARCH
WITH BIG DATA
Benjamin Spiegel
Director, Search Operations

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Who am I?
Benjamin Spiegel
Director, Search Operations
Catalyst Online
Twitter: @nxfxcom
Email: benjamin.spiegel@groupm.com
URL: www.catalystsearchmarketing.com
Likes
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Search
Analytics
Data
Caffeine
Dislikes
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PowerPoints
Presentations
Public speaking
Plus…

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Data Silos
ORGANIC
PAID
SOCIAL

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Data Sources
and many more…

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API Process
1. 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

8. Organic Rank
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Current CPC

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

10. Organic Rank
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Current CPC

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Okay, How About Coloring
Them By Bounce Rate?

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Current CPC

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How About Incorporating Google
Trend Forecast With Icons

14. Organic Rank
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Current CPC

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Organic
Paid
Current CPC

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CASE STUDY
BrandX Wanted Visibility On 50%
Of All Results For Primary
Keyphrases
Currently Visible on 20%

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1. We Took ~4000 Key Phrases
And Collected The Top 20
Rankings For Each Term
Gave Us 67,000 Unique URLs

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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
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Did not align with the target audience
Had low engagement
Could not be influenced
Have low social or link authority

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Visibility (Avg Rank | # Results)
7. This Left Us With Around 170 Highly
Engaged & Highly Targeted Sites.
Referral pages per Visit

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

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Thank you!
Benjamin Spiegel
Director, Search Operations