#id2013 - data silos by @nxfxcom

Post on 22-Nov-2014

122 Views

Category:

Marketing

0 Downloads

Preview:

Click to see full reader

DESCRIPTION

Benjamin Spiegel's presentation at #ID2013 (Interactivity Digital) in South Beach on Data Silos in the Digital Age - http://www.youtube.com/watch?v=A0Jop4fsDpc

TRANSCRIPT

#ID2013

DRIVING SEARCH

WITH 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…

#ID2013

ORGANIC PAID SOCIAL

Data Silos

#ID2013

Data Sources

and many more…

#ID2013

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.

#ID2013

So What Does That Mean For Me?

#ID2013

Key Phrase Strategy

#ID2013O

rgan

ic R

ank

Current CPC

#ID2013

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

Interest

#ID2013

Current CPC

Org

anic

Ran

k

#ID2013

Okay, How About Coloring Them By Bounce Rate?

#ID2013

Current CPC

Org

anic

Ran

k

#ID2013

How About Incorporating Google Trend Forecast With

Icons

#ID2013

Current CPC

Org

anic

Ran

k

#ID2013

Current CPC

Org

anic

Ran

k OrganicPaid

#ID2013

CASE STUDY

BrandX Wanted Visibility On 50% Of All Results For Primary Keyphrases

Currently Visible on 20%

#ID2013

Gave Us 67,000 Unique URLs

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

Each Term

#ID2013

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

#ID2013

3. We Analyzed The Sentiment Of All The Discovered URLs

#ID2013

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

#ID2013

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

#ID2013

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

#ID2013

Referral pages per Visit

Visi

bilit

y (A

vg R

ank

| #

Resu

lts)

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

#ID2013

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

Result

#ID2013

Thank you!Benjamin Spiegel

Director, Search Operations

top related