1. Stage 1 involves going "cold turkey" and dealing with cravings and fears about weight gain and social impacts. 2. Stage 2 focuses on other behavioral methods to quit but side effects become a major issue. 3. Stage 3 involves settling on over-the-counter treatment options that minimize side effects. 4. Stage 4 turns to prescription medication but many struggle to stay on the regimen due to persistent side effects.

1. Moving from Unstructured Data
into Structured Meanings and
Data Stories
Marshall Sponder
WebMetricsGuru INC for
NYU ITP CAMP
6-22-12

2. Introduction – about me, besides being an ITP
Camper….
Marshall Sponder is the CEO/Founder of WebMetricsGuru
Inc., a social solution design, social media analytics, web
data analysis and SEO/SEM practice focusing on cutting
edge market research and social media trend analysis.
He is the author of "Social Media Analytics: Effective Tools
for Building, Interpreting, and Using Metrics", published by
McGraw-Hill, 2012.
Marshall also teaches Social Media Analytics and Art at
Rutgers University and UCI Irvine, Extension and is a
frequent speaker at Analytics conferences internationally
and in the United States.

3. Geo-located check-in data, somehow, got much harder to accurately
capture, across the board, via listening platforms after last summer (but
it was always fragmentary, at best).
Sysomos Map Query: 4sq.com/

4. Last Year did some data crunching using Radian6 and 4SQ check-ins –
found context / story much easier to get via Geo-local data
My findings are that
adding additional
“dimensions” to the
social data provides
“context” that is
often missing,
because the social
data is largely
unstructured.
Also was able to look
at “influencers” by
the venues they
habitually visited and
their Twitter
following.

6. Hitting People through multiple Channels, creates
“meaning” and DejaVu.
NY Lottery online site
2. NY Subway Train
1. Pandora
Having cookies tracked across sites is probably doing something similar – but the idea is
awareness, relevance and meaning are “created” by repetition across varied channels with in a certain

7. Finding /Creating Meaning / Creating
the Story using Social Media
Moment of
Receptivity
At the moment of receptivity – your message, argument, proposition has a chance of
being received and acted on. The story you create will be a mixture of what you wish
to create, and what your recipients will make of it (how they will process it).

8. Unstructured Data
Some types Data (not all inclusive)
Some Data
More work is
Big Data, including machine generated data (and Big Analytics) req for
unstructured
Social Media, Video, Audio and Geo Local (Mobile) Data data
Offline Data (verbal, observed) recorded or non-recorded
Search Engine and Web Analytics Data (structured and Page Based)
Large and medium business/marketing silo data (business intelligence)
Financial, manufacturing, Legal and Legislative Data
Learning/ Training Data (Education/University)
Printed / Written Data (ledgers, lists)
Structured Data

9. How much Unstructured Data is there?

10. Types of Unstructured Data (some of these types
you deal with at ITP Camp)
Examples of Structured Data (Businesses, Governments and Educational Institutions have a
lot of experience with this kind of data)
- Databases
- XML data
- Data warehouses
- Enterprise systems (CRM, ERP, etc)
Examples of Unstructured Data (no one has a corner of this type of data, yet – everyone is
struggling with it).
- Excel spreadsheets (one can argue this point – as Excel can have structure too)
- Word documents
- Email messages
- RSS feeds
- Audio files
- Video files
- Social Media Data (tweets, posts, photos, likes, shares, Near Field, Geo-fensing)
- Mobile Data (check-ins, SMS, etc)

11. Add a Plan to help Structure to Data
• Identity (who are you identifying?)
You A business, non-profit, Gov, Some one else (depends how you
an official, Industry, etc. want to define this)
• What (are you measuring?)
Check- Visits, Page views, Unique Behavioral and Attitudinal data –
ins, mentions, posts, clicks, pulse Visitors, etc (perhaps a much harder – some ITP
data, etc specific audience type) experiments seem to go here -
• Where (are you monitoring?)(have enough data?)
Social Media Channels Location (where) Venue Type Situation/mindset
• When (is it happening?)
Real Time / Seasonal Specific event Time not defined
Asynchronous
• Why (is it happening?) You know why, but you want to know how
much, be more tactical, effect specific changes
Exploratory (don’t know – trying to
find out) Business Goals? Art Goals, Effect
Changes,

12. Would be nice if Social Data could interface into something
like Isadora, don’t know if anything that does that yet, or
what the metaphors for the data would be (a good
direction, though, if someone wants to take that on).
I suspect such an interface would lend itself to “Big Data”

13. Maybe this taxonomy would work (http://behaviorgrid.org/)... But you
have code the verbatim manually – unless you can program machine
learning to do it for you (wont be that accurate, though)

14. What Platforms Provide (not a complete list by
any means)
• Geolocation (location, venue type, other friends)
• Social – Sentiment, Volume, age/gender, some attempt at
topic, usually inadequate, text analytics
• Web Analytics – Visit, Page view, Visitors (unique/new)
Cookie Location, pathing (on site only), correlation
tools, search keywords, links (referrers), ecommerce tracking
(on site only)
• Audience Measurement – via Ad Exchanges, online
panels, demographics, psychographics, and geo-
demographics.
• Census and Governmental data
• Financial Data – Wall Street,
• Market Research – Traditional – Forums, Polls, opinioned
analysis based on sampling (political polls, ie).
• Market Research – New – Big Data – try to find out hidden
patterns (ie: people who fix their roofs have less car accidents
and get cheaper car insurance, stuff like that).

15. For ITP – Suggested Taxonomy
• Author / Artist / Subject / Activity
• Place (location)
• Time (timeframe)
• Type of Action / Behavior
• Persona (this will have to be defined)
• Medium (i.e.: GSM/Mobile, Projection, etc)
• Subject / Area
• Purpose (recreational, exploratory, consciousness
raising, etc)
• Etc, etc, etc (these need to be further defined)

16. Two-Tiered Segmentation
Merging customer and visit type segmentation creates a two-tiered
segmentation framework that becomes the core of our data model
Visit Types
Visitor Product Category Early Stage Discount
Type Directed Directed Research Shopper
High-Ticket
Buyer
Prestige Giver
Visitor Record
SMB Shopper
Brand Loyalist

17. Medium is the Message - McLuhan
• How your measuring and viewing affects what you see, what you
find. Many ITP experiments are directly impacted by the
method/medium being used. In emerging media, especially, due to
“unstructured” aspect of it, tools shape the data (and insights).
• What tools or platforms are you using? What are tools are platforms
can you use (are at your disposal)?
• What is your budget for the tools platforms and people?
• Are you in control of the measurement process yourself, or are you
depending on others to execute it for you?
• Do you have a framework to put all this data in? That’s pretty
important.
IMPLICATION: Choice of tool or platform profoundly shapes the
results of your experiment or project

18. What’s the Use Case? Pick One (or add a
Type
new use case)
Behavioral

19. Use cases from a Tools/Platform
perspective
Consumer PR Monitoring &
Social Campaigns
Research Support
Automating of the
Listening for Listening and
engagement
Insights Engagement
Social Media Traditional
Coverage* Media Workflow
Coverage*
NLP (machine Influencer Operational
learning) Identification Metrics
Rich Topic
Low-Latency
Categorization Categorization
Care of Gary Angel – Semphonic.com

20. Not so much an issue for ITP, but many organizations
end up buying the same data from multiple vendors
(over and over) (something to avoid, if you can)
Examples:
Full Service
Source: Semphonic.com

21. In some cases, a high level plan (similar to a 1 minute pitch) might
help to add structure and meaning to what your going to try to do
(even here at ITP Camp or ITP, in general)
Goal(s): Audience:
among
Location: Timing :
through/ with
Vehicle (how your going to do it): Venues (where your going to do it):
ask fans and
customers to
Message (Call(S) to Action):
Regarding our
Product / Service / Program
Where Success will be judged by
Metrics/KPI’s

22. Example of a Student’s Goal – Resurrecting George Enescu’s Work
Goal: Audience:
Salvage the reputation of the Romanian 20th Among Classical music
century composer, George Enescu institutions, enthusiasts, and
musicians alike
Location: Timing:
Ideally GeorgeEnescu.com A 6 month campaign period Through/ With
Vehicle: Venues:
Online videos, online Personal blog, radio stations, YouTube, Ask fans and
networking, podcasts, musicological musicological conferences, etc. customers to
research
Message:
Enescu’s art ought to be enjoyed and celebrated as the
Regarding the
work of a deserving, 20th-century master
Program:
Program to promote the musicians and orchestras who wish to
explore Enescu’s work Success will be judged by
Metrics/KPI’s
Popularity on Google New business connections New visitors to Youtube
Trends and partnerships website statistics

23. And what is a Plan, Anyway?

24. We’re drinking from the social media fire hose
Massive data to process and make sense of it all
But … We Don’t Need to boil the ocean!
8
5

25. New Solutions Lie in …
• Adding additional dimensions to the data (i.e.:
time, place)
• Adding Custom Taxonomies, Lexicons and data
mashups helps, if done well and cleanly
• Customizing the source data feeds
• Customizing Data Extraction from Pages Crawled
• Defining what your goals are
• Defining what, when, where and how your going to
accomplish your goals
• Define your Key Performance Indicators that tell
you if you hit or missed your goal targets

26. Internet Abundant with Predictive Signals

27. Beyond Listening:
Reinventing Social Media Monitoring
If a status
update reaches
a social network
but no one sees
it, does it exist?

28. Are people using the
wrong solutions to
determine what people
are saying?

29. @listening as a use case …
Why Bother??
“the problem with social is that there is so
much data - there’s 40 or 50 data points
that you can measure and you have to
figure out whether they are important.
Some of those measurements are
fundamentally not important.

30. Pain!!
• Broad listening across the internet
Blogs Forums Press
• Focused on keyword matches
News
Social Sites Trade Sites
Networks
– Mentions of
• Brand name “Starbucks”
• Product names “Frappuccino”
• Produces valuable insights, but
is exploratory in nature, as a
result, it can not answer tactical
questions and is not scalable.
“I’m drowning in data and documents from
the internet but I need actionable insights”

31. Problems we all face with Social
No Process
Success Undefined
90 % Unstructured
Time Consuming
Hard to Scale
esp. at the beginning

32. “Lens” approach using
Boolean queries and saved
datasets don’t seem to
work very well

33. Monitoring has become too complex
http://www.youtube.com
/watch?v=4Y-SVxnVOv8
Radian6 Query on Foreclosures in Rhode Island
"housing solution"~2 AND "rhode island" AND "foreclosure", "road home program"~3 AND
"foreclosure", "home loan modification"~4 AND "foreclosure", "jobless rate"~3 AND
"foreclosure", "bankrupcy" AND "foreclosure" AND "housing" AND "obama", "rhode island
housing"~3 AND "forclosure", "foreclosure prevention funds"~5, "bank foreclosures rhode
island"~4 AND "obama", "selling house"~4 AND "foreclosure" AND "obama", "hardest hit
fund"~4, "national foreclosure mitigation"~6, "homeowner stability initiative"~5 AND
"obama", "roadhome program"~2, "hud homes rhode island"~3 AND "obama", "foreclosure
settlement"~4 AND "25 billion"~2 AND "obama", "fannie mae freddie mac"~10 AND
"foreclosure", "keeping people in their homes"~4

34. And we don’t get our
“Pie in the Sky”

36. Recorded
Future

37. Web is Loaded with Events
Silicon Valley executives head to
Vail, Colo. next week for the Drought and malnutrition hinder next year’s
annual Pacific Crest Technology development plans in Yemen...
Leadership Forum
The carrier may select partners to set up
a new carrier as early as next month
“2010 is the year when Iran will kick out “...opposition organizers
Islam. Ya Ahura we will.” plan to meet on Thursday
to protest...”
“... Dr Sarkar says the new facility will
be operational by March 2014...”
“Excited to see Mubarak “According to TechCrunch
speak this weekend...”
“Strange new Russian China’s new 4G network will
worm set to unleash be deployed by mid-2010”
botnet on 4/1/2012...”

38. Recorded Future Architecture
70,000 Real-time Sources
100,000 future events/day
3+ Billion Time-tagged Facts

43. Mobile and Tablets - Next three years
Huge market segments still emerging
• Over 75% of businesses plan on deploying tablets by 2013
• Revolutionizing health care delivery, on-site and mobile
• Disrupting software engineering and user expectations

44. Actionable Intelligence gleamed from
LBS instead of exploratory insights
Geo-Location Analytics
from SMM
VenueLabs –
They mess up here A LOT! If I wasn’t in a rush
nor a coffee addict I would go somewhere
else!
New Insights
Traditional Insights
Location Date /Time
Topic
Sentiment Staff Working Managers
Influence Local Context Unit Sales
Engagement Nearby Competitors

45. VenueLabs solves Local Data Gap Example
They mess up here A LOT! If I wasn’t in a rush
nor a coffee addict I would go somewhere else!

46. Verified the Local Data Gap
The text of the verbatim don’t help much since they we can’t tell where this
actually was taking place without looking at the additional short url and creating
a context – which the software, today, usually isn’t able to do.

47. New York Art Instance - VenueLabs

48. Most active
Museums?

49. Local Data Analytics of Museums – adding
location automatically makes info more
actionable (context)
Facebook & Twitter

50. Smoking Cessation
Smoking Cessation Phases
Patient Journey Stage 1 Patient Journey Stage 2 Patient Journey Stage 3 Patient Journey Stage 4
Behavioral: Cold Turkey Behavioral: Other Over The Counter RX
Side Effects of Craving comfort food, nicotine, Respondents are actively Respondents in stage 3 are smoking cessation is the main
Smoking fear of weight gain, quitting and seeking to quit smoking by settling on a treatment choice at stage 4 (based on our
Cessation wondering how friends and fear the physical and option presenting the least listening) but many respondents
family will view decision. psychological side effects. side effects as possible or are having problems staying on
going cold turkey. the regime due to side effects.
Choosing the right Respondents are looking for a Patients are suffering the side In Stage 3 Smoking In Stage 4 smoking cessation
medication for way to stop smoking but are effects associated with Cessation decisions side effects are the main issue
Smoking confused with options and Nicorette, nicotine patches, complicated by product bans respondents have, with men
Cessation asking for advice. smoking cessation or cold for e-cigarettes and smoking appearing to do better with the
turkey cessation in some treatment than woman.
communities and Negative press over side effects
occupations of smoking cessation are
upsetting - making many rethink
their decision to stop smoking,
Available Options In Stage 1 respondents are In Stage 2, the overwhelming In Stage 3 use of Electronic In Stage 4 Patients struggle with
for Smoking seeking guidance on all the choice of Smoking Cessation Cigarettes followed by the side effects of smoking
Cessation are available treatment options and treatment option is Hypnosis, Nicorette gum as the most cessation treatment, itself.
Confusing making a decision on which with second most popular popular treatment Some patients complete
one(s) to try. treatment being Nicorette according to our listening treatment successful but others
and then smoking cessation. reports. do not and are dissatisfied with
their progress.
Getting advice on Online respondents are going on In Stage many side effects Patients in stage 3 have tried In Stage 4 just about all the
the right blogs, twitter and forums looking associated with each treatments and are sharing information on smoking
treatment options for people who have experiences treatment are evident and their experiences struggles cessation is negative, although
for Smoking taking drugs for Smoking respondents are grappling and successes with Smoking that does not stop many patients
Cessation Cessation so they can get with which choice to make - Cessation. from taking the drug, but many
information on the right often going with hypnosis are stopping once they
approach to take. first. experience side effects.

51. Defining Key Words
Patient Journey Stage 1 Patient Journey Stage 2 Patient Journey Stage 3 Patient Journey Stage 4
Behavioral: Cold Turkey Behavioral: Other Over The Counter RX
"quit smoking" "counseling" AND "smoking" "snus" AND "smoking" "smoking cessation"
"smoking cessation" "cutting back" AND "smoking" "nicotrol“ (1 mention) "buproban" AND "-order"
"cold turkey" AND "smoking" "nicotine free-cigarettes" "e-cigarette" AND "-buy" AND
AND "quit on my own“ "-"buying“
"homeopathic remedies" AND
OR "quit smoking" AND "stop "stop smoking gum"
smoking“
“jotharmcoe” "" nasal sprayAND "smoking“(1
“smoking cessation” “hypnosis” AND “smoking” mention)
“mytimetoquit.com” AND “-weed”
“smoking cessation.com” "nicoderm"
“let’s quit together now” "embarrassed to" AND
“get quit clinic” "doctor" AND "smoking" "lozenge" AND "smoking“
“qut-quit.com”
"quit line" AND "smoking" "patch" AND "smoking"
"herbal remedies" AND "quit "inhaler AND "smoking"
smoking" AND "stop smoking"
"Nicolette“(strongest
"support group" AND keyword)
"smoking"
"nicotine replacement
therapy" AND "smoking"

52. Location of Conversation for Each Stage of the Patient Journey
Behavioral: Cold Turkey Behavioral: Other
Stage 1 Stage 2
Over The Counter RX
Stage 3 Stage 4

53. Putting targeting into action RI Primary
= Create The Story (Be The Story)?
? Over 50
80,120
RI District 1 1. Hit potential voters in District 1 with issue
targeted sponsored stories for AWARENESS
only (expect little if any Clicks)
2. Blanket Zipcodes with mailing (post office
now does this).
3. Use Venuelabs to sift checkin data and find
Members of Facebook over 49 years old voters –cross link to voting list when possible.
in RI District 1 = 102,920 (caveat: 4. Categorize (data mining – persuadable?)
there are a few zip-codes in both 5. Reach out / Community management – etc
districts) 6. Set up tracking (i.e.; Campalyst – next slide)

54. Connecting Engagement To Conversions
campalyst.com

55. Google Social Reports Cannot connect the
dots to ROI (yet) though Campalyst, Can.

56. Google Social Reports Cannot connect the
dots to ROI (yet) though Campalyst, Can.
Not enough information – Google cannot connect
the dots back to the original post that generated
the referral, but Campalyst does.

57. Campalyst ties cause and effect for Twitter and
Facebook better than any other platform I’ve yet
seen – marshall sponder – WebMetricsGuru.com

58. Campalyst can also find the brand advocates that
generate the most traction and engagement for a
brand or website.

59. Summary
• The Future of Analytics is with
Actionable Data
• Actionable Data comes from
adding contextual information
and metadata in meaningful
ways related to your business
or organizational goals.
• You need a Plan (the right one)
to execute, together with the
metrics, audience, timing, venu
e, program /vehicle and KPI’s to
succeed with Analytics of any
kind.

60. Examples of Platforms (you can play
Radian6 Basic
with these later)
Sysomos Map
Brandwatch
Campalyst
Infinigraph
6dgree
Netbase
PeekAnalytics
Traackr
mPact
Venuelabs

61. WebMetricsGuru.com
Marshall Sponder
WebMetricsGuru INC.
www.webmetricsguru.com
www.smabook.com
now.seo@gmail.com
@webmetricsguru
@smanalyticsbook
WebMetricsGuru INC.