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Big Data,
Small Data,
Data that Totally Rocks
Rob Clark
Director Insights & Measurement
Edelman Digital
@theelusivefish
“Any sufficiently
advanced
technology is
indistinguishable
from magic.”
- Arthur C. Clarke
If we take
DATA
and then add…
DATAMORE
DATA
as well as…
DATAMORE
DATA
EVEN
MORE
DATA
in addition to…
DATAMORE
DATA
EVEN
MORE
DATA
YET EVEN
MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
AND THEN SOME MORE DATA
YET EVEN
MORE DATA
and so on,
and so on,
and so on…
DATAAND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
AND THEN
SOME MORE
DATA
EVEN
MORE
DATA
Ala Peanut Butter
and Jelly
Sandwiches!!!!
1. Collect data
2. ???
3. Profit.
It’s not the size
of your data,
It’s how you
use it.
Target Case study…
An example…
Identify
pregnancy before
any official
announcement to
target marketing
before
competitors
87%
Guest ID assigned
to every customer
Tied to credit card,
name, email
address.
Purchases analyzed
and commonalities
from pregnancies
identified.
Combine for score that predicts both
pregnancy and due date…
NOTE:
The Creepy Factor
GAH!!!
A Target snuck up
and is right behind
me, isn’t it?
SHAZAM!!!!
Target Case study…
But it wasn’t
magic. Just
effective
targeting.
1. IDENTIFY A QUESTION TO BE ANSWERED,
A PROBLEM TO BE SOLVED
2. COLLECT RELEVANT INFORMATION ON THE ISSUE
3. ANALYZE THAT INFORMATION
4. FORM A CONCLUSION
Effective use of data
“But @theelusivefish,” you tweet, “that’s nice
and all, but what does that have to do with
social media data?”
“YEAH!,” tweet others in agreement and then
RT, “that’s nice and all, but what does that have
to do with social media data?”
“hashtag hashtag hello, I’ve got a great deal on
viagara cialis bit.ly/343q2a” tweets an
anonymous bot that saw activity on the topic
and dived in for the sale.
Because it’s not about ‘social media’ data. It’s
about ‘DATA’. Like people, you want to treat
data the same no matter where it came from.
But let’s talk about a familiar
social media tactic:
‘Online Influencers’
$$
$ $
Who would have ever thought that one
day, I would be an influencer on the
information super highway? Come
closer and touch my sweater… some of
the klout may rub off on you.
Does it work, or are we just
giving away free stuff to
popular people?
$$
$ $
25 boxes of swag
20 tours of factory
18 warm handshakes
from the CEO
150 tweets
6 Facebook posts
4 Blog posts
4 RTs
2 Favourites
10 Likes
Normally
we report…
But we want to know
outcomes not outputs
How do our
interactions with
an individual
impact that
individual’s
audience?
THE QUESTION:
Compare all
brand mentions
by our audience
with brand
mentions by
those not in our
audience.
THE METHOD:
Audience mapped using NodeXL
Raw data obtained using Radian6
Analysis conducted in Excel
25 Influencers
~80K Followers
Over 2M tweets
collected three
months apart
THE DATA:
About 10 x more likely to mention the brand
Will mention the brand 8 x more
Between 2-7% negative sentiment vs. 25-27%
Q2
Q1Within our
influencer’s
network, 52%
continued
mentioning the
brand vs. 12%
What’s changed?
ANYTHING CAN BE MEASURED.
ANYTHING.
LOOK FOR WHAT CHANGE YOU ARE SEEKING TO MAKE.
If it changes, then it can be
measured.
“Data! Data! Data!”,
he cried impatiently,
“I cannot make
bricks without clay!”
- The adventures of Sherlcok Holmes
Identifying
contextual
relevance from
peers and
volunteered info.
Turtles
Shelled Animals
Turtle Owners
Turtle Turtle Turtle
Reptiles – Snakes and Turtles
Tortises
Turtle Lovers
Turtle List
Subject
experts on
Turtles?
Extract lists via NodeXL
Analyze in Excel
Don’t just
leave it to the math
The social gestures don’t always
mean what we think they mean.
This guy likes turtles.
This guy …
not so much
Please don’t
pee in the pool
Encouraging false
signals spoils the
pool of data for
everyone
80% of data analysis
is cleaning the data
Keep your data TIDY!!!
OpenRefine as a useful tool for cleaning messy data
openrefine.org
Structure your data
FIRST VARIABLE SECOND VARIABLE
1st Observation Value Value
2nd Observation Value Value
3rd Observation value Value
One type of observation
• Each table contains one type of observation
• Each column is a variable
• Each row a set of observations
Keep your data TIDY!!!
1. IDENTIFY A QUESTION TO BE ANSWERED, A PROBLEM TO BE SOLVED
2. COLLECT RELEVANT INFORMATION ON THE ISSUE
3. ANALYZE THAT INFORMATION
4. FORM A CONCLUSION
Use your data effectively
Look for the change or predictable patterns
1. COMPARE OVER TIME
2. COMPARE TO SIMILAR ‘CONTROL’ GROUP
3. USE GROUP WITH KNOWN OUTCOMES TO FORM PREDICTIVE MODEL
Keep your data tidy
1. COMPARE APPLES TO APPLES
2. STANDARDIZE AND STRUCTURE OBSERVATIONS
Now watch me
disappear…
ALAKAZAM!!!
CREATIVE COMMONS – BY ATTRIBUTION
Data action figures
http://www.flickr.com/photos/jdhancock/8031897271/
LinkedIn Dataset
http://www.flickr.com/photos/luc/5418037955/
LEGO Wizard
http://www.flickr.com/photos/tamaleaver/7419788172/
Gnomes
http://www.flickr.com/photos/debabratad/4569271310/
Target shopping cart
http://www.flickr.com/photos/jreed/1352409015
Pregnant belly
http://www.flickr.com/photos/nateone/3240716239/
Purse
http://www.flickr.com/photos/lululemonathletica/4209254375
Cocoa Butter
http://www.flickr.com/photos/franciscouhlfelder/5404451647
Blue Rug
http://www.flickr.com/photos/andie712b/4619093237
Target right behind you
http://www.flickr.com/photos/gazeronly/6150401295/
Ford Online Influencers
http://www.flickr.com/photos/pandemia/6731863193/
No public access
http://www.flickr.com/photos/jmv/2734200159
Benedict Cumberbatch on set
http://www.flickr.com/photos/bellaphon/4409531705/
Pee in the pool
http://www.flickr.com/photos/lifeontheedge/230245129
Photographer
http://www.flickr.com/photos/evilerin/3098610791
Photo Credits

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Big Data, Small Data, Data that Totally Rocks - SMWTO

  • 1. Big Data, Small Data, Data that Totally Rocks
  • 2. Rob Clark Director Insights & Measurement Edelman Digital @theelusivefish
  • 8. AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA YET EVEN MORE DATA and so on, and so on, and so on… DATAAND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA AND THEN SOME MORE DATA EVEN MORE DATA
  • 9. Ala Peanut Butter and Jelly Sandwiches!!!!
  • 10. 1. Collect data 2. ??? 3. Profit.
  • 11. It’s not the size of your data, It’s how you use it.
  • 13. Identify pregnancy before any official announcement to target marketing before competitors
  • 14. 87% Guest ID assigned to every customer Tied to credit card, name, email address. Purchases analyzed and commonalities from pregnancies identified. Combine for score that predicts both pregnancy and due date…
  • 15. NOTE: The Creepy Factor GAH!!! A Target snuck up and is right behind me, isn’t it?
  • 17. Target Case study… But it wasn’t magic. Just effective targeting.
  • 18. 1. IDENTIFY A QUESTION TO BE ANSWERED, A PROBLEM TO BE SOLVED 2. COLLECT RELEVANT INFORMATION ON THE ISSUE 3. ANALYZE THAT INFORMATION 4. FORM A CONCLUSION Effective use of data
  • 19. “But @theelusivefish,” you tweet, “that’s nice and all, but what does that have to do with social media data?” “YEAH!,” tweet others in agreement and then RT, “that’s nice and all, but what does that have to do with social media data?” “hashtag hashtag hello, I’ve got a great deal on viagara cialis bit.ly/343q2a” tweets an anonymous bot that saw activity on the topic and dived in for the sale. Because it’s not about ‘social media’ data. It’s about ‘DATA’. Like people, you want to treat data the same no matter where it came from.
  • 20. But let’s talk about a familiar social media tactic: ‘Online Influencers’
  • 22. Who would have ever thought that one day, I would be an influencer on the information super highway? Come closer and touch my sweater… some of the klout may rub off on you. Does it work, or are we just giving away free stuff to popular people?
  • 23. $$ $ $ 25 boxes of swag 20 tours of factory 18 warm handshakes from the CEO 150 tweets 6 Facebook posts 4 Blog posts 4 RTs 2 Favourites 10 Likes Normally we report… But we want to know outcomes not outputs
  • 24. How do our interactions with an individual impact that individual’s audience? THE QUESTION:
  • 25. Compare all brand mentions by our audience with brand mentions by those not in our audience. THE METHOD: Audience mapped using NodeXL Raw data obtained using Radian6 Analysis conducted in Excel
  • 26. 25 Influencers ~80K Followers Over 2M tweets collected three months apart THE DATA:
  • 27. About 10 x more likely to mention the brand Will mention the brand 8 x more Between 2-7% negative sentiment vs. 25-27%
  • 29. What’s changed? ANYTHING CAN BE MEASURED. ANYTHING. LOOK FOR WHAT CHANGE YOU ARE SEEKING TO MAKE. If it changes, then it can be measured.
  • 30. “Data! Data! Data!”, he cried impatiently, “I cannot make bricks without clay!” - The adventures of Sherlcok Holmes
  • 31. Identifying contextual relevance from peers and volunteered info. Turtles Shelled Animals Turtle Owners Turtle Turtle Turtle Reptiles – Snakes and Turtles Tortises Turtle Lovers Turtle List Subject experts on Turtles? Extract lists via NodeXL Analyze in Excel
  • 32. Don’t just leave it to the math The social gestures don’t always mean what we think they mean. This guy likes turtles. This guy … not so much
  • 33. Please don’t pee in the pool Encouraging false signals spoils the pool of data for everyone
  • 34. 80% of data analysis is cleaning the data Keep your data TIDY!!! OpenRefine as a useful tool for cleaning messy data openrefine.org
  • 35. Structure your data FIRST VARIABLE SECOND VARIABLE 1st Observation Value Value 2nd Observation Value Value 3rd Observation value Value One type of observation • Each table contains one type of observation • Each column is a variable • Each row a set of observations Keep your data TIDY!!!
  • 36. 1. IDENTIFY A QUESTION TO BE ANSWERED, A PROBLEM TO BE SOLVED 2. COLLECT RELEVANT INFORMATION ON THE ISSUE 3. ANALYZE THAT INFORMATION 4. FORM A CONCLUSION Use your data effectively Look for the change or predictable patterns 1. COMPARE OVER TIME 2. COMPARE TO SIMILAR ‘CONTROL’ GROUP 3. USE GROUP WITH KNOWN OUTCOMES TO FORM PREDICTIVE MODEL Keep your data tidy 1. COMPARE APPLES TO APPLES 2. STANDARDIZE AND STRUCTURE OBSERVATIONS
  • 38. CREATIVE COMMONS – BY ATTRIBUTION Data action figures http://www.flickr.com/photos/jdhancock/8031897271/ LinkedIn Dataset http://www.flickr.com/photos/luc/5418037955/ LEGO Wizard http://www.flickr.com/photos/tamaleaver/7419788172/ Gnomes http://www.flickr.com/photos/debabratad/4569271310/ Target shopping cart http://www.flickr.com/photos/jreed/1352409015 Pregnant belly http://www.flickr.com/photos/nateone/3240716239/ Purse http://www.flickr.com/photos/lululemonathletica/4209254375 Cocoa Butter http://www.flickr.com/photos/franciscouhlfelder/5404451647 Blue Rug http://www.flickr.com/photos/andie712b/4619093237 Target right behind you http://www.flickr.com/photos/gazeronly/6150401295/ Ford Online Influencers http://www.flickr.com/photos/pandemia/6731863193/ No public access http://www.flickr.com/photos/jmv/2734200159 Benedict Cumberbatch on set http://www.flickr.com/photos/bellaphon/4409531705/ Pee in the pool http://www.flickr.com/photos/lifeontheedge/230245129 Photographer http://www.flickr.com/photos/evilerin/3098610791 Photo Credits

Hinweis der Redaktion

  1. Photo JD Hancockhttp://www.flickr.com/photos/jdhancock/8031897271/
  2. Image:luclegayhttp://www.flickr.com/photos/luc/5418037955/
  3. Photo by Tama Leaverhttp://www.flickr.com/photos/tamaleaver/7419788172/
  4. Photo by Debabratadhttp://www.flickr.com/photos/debabratad/4569271310/
  5. Photo by J. Reed http://www.flickr.com/photos/jreed/1352409015
  6. Photo by NateOnehttp://www.flickr.com/photos/nateone/3240716239/
  7. Purse – photo LululemonAthleticahttp://www.flickr.com/photos/lululemonathletica/4209254375Cocoa Butter – photo the cardinal de la villehttp://www.flickr.com/photos/franciscouhlfelder/5404451647Blue rug – Andie712b http://www.flickr.com/photos/andie712b/4619093237
  8. Phototorbakhopperhttp://www.flickr.com/photos/gazeronly/6150401295/
  9. Photo by J. Reed http://www.flickr.com/photos/jreed/1352409015
  10. Photo pandemiahttp://www.flickr.com/photos/pandemia/6731863193/
  11. Photo pandemiahttp://www.flickr.com/photos/pandemia/6731863193/
  12. Public Access photo by jmv - http://www.flickr.com/photos/jmv/2734200159Benedict Cumberbatch on set for Sherlock by bellaphonhttp://www.flickr.com/photos/bellaphon/4409531705/
  13. Turtle - “Jonathan Zander (Digon3)“http://en.wikipedia.org/wiki/File:Florida_Box_Turtle_Digon3_re-edited.jpgKrang - http://mikev.me/ Mike V
  14. Photo by Marshall Astor – Food Fetishist http://www.flickr.com/photos/lifeontheedge/230245129
  15. Photo by Tama Leaverhttp://www.flickr.com/photos/tamaleaver/7419788172/
  16. Photo by Evil Erin http://www.flickr.com/photos/evilerin/3098610791