Data Analysis Basics - Workshop (Frameworks)

Getting better and better at investigating and weaving digital data

DATA STORIES

Screen capture, Sherlock - BBC

I. ContextII. Frameworks and Rules of ThumbIII. Describing and Analyzing QualitativelyIV. Visualizing DataV. Statistics Basics - Averages & CorrelationsVI. Business Language

Why are we doing this?CONTEXT

COMPANY

GROUP

Data-driven decisions

PERSONAL

If you only want to guess how strong your ad is doing, e de sana nag-TV, radyo o billboard ka na lang.


COMPANY

GROUP


Better Insighting & Efficiency

PERSONAL?

Gather as much Wisdom (and Sales)

from data

OBJECTIVE


Doing research isn’t a silver bullet.

Rules of Thumb

LIST - CLUSTER - SORT

FIND THE STORY, FIRST.

MACRO MICRO

I. ContextII. Frameworks and Rules of ThumbIII. Describing and Analyzing QualitativelyIV. Visualizing Data

Framework

Start with the broadest view.Before you zoom in.


“Performance”

When does it peak?HISTORICAL

Did anything change?PREVIOUS

PERIOD

Where did it go?COMPETITION

- HISTORY

Anu-anong klaseng mga tao?

PROFILE

Process

Pre-work: Outline

5 minutesYou want to save money.

How would you outline your analysis of your personal

expenses?

ProcessList - Sort - Cluster - Track

1. List

get your data into a

spreadsheet

DRUDGERYLincoln said something like,

"Give me six hours to chop down a tree and I will spend the first four sharpening the axe."Sarah Slobin, Visual Journalist, New York Times and Graphics Editor of the Wall Street Journal


Gather ALL possible data important to your objective.

Marina Ekroos

2. Sort

rank everything

Arrange as many attributes as you can.

TIMEPERFORMANCEPROPORTION

Till you start perceiving patterns.

Or a lack of them.

Get acquainted.

STRENGTHWEAKNESS

NORMS

3. Cluster

classify common

elements

Check what occurs together,

and what drives

HIGH-PERFORMERSMID-RANGE

LOW PERFORMERS

Classify and list all relevant dimensions.

GENDERFORMAT

TYPESee leads into the

meaning behind the performance.

4. Track

repeat steps 1-3

after some time

WATCH DATA GROW UP.Data is about relationships.

A number doesn’t make sense by itself.- Me.

Taking your temperature again and again.

BENCHMARKINGFind: What was different that made the data shift?

COLOR > SHAPEBrain Processing Speed

Compare, not just time,but location,

types of users (demographics), etc.

FINDING MEANING


15 minutesI’ll give you a dataset.

Tell the group what story you got from it.


DESCRIBING DATA

HISTOGRAM vs BAR CHARTOnly Quantitative Categorical or Qualitative

Numerical

Num

eric

al

DimensionsN

umer

ical

If your data looks like this...

What would you say about it?

0

1

2

3

4

12-15 16-19 20-24 25-29 30-34 35-39 40-44 45-49



0

1.75

3.5

5.25

7

12-15 16-19 20-24 25-29 30-34 35-39 40-44 45-49



0

1.25

2.5

3.75

5

12-15 16-19 20-24 25-29 30-34 35-39 40-44 45-49



0

1

2

3

4

12-15 16-19 20-24 25-29 30-34 35-39 40-44 45-49

PROCESSING QUALITATIVE DATA


“Codebook”

List - Sort - Cluster - Track

F, 25-34, C2D- long for closeness-openness, yet are themselves afraid of disclosure (judgment, rejection, comparison) – relatively kimi, only one out of five gregarious (learned to defend mother from others)- married feel that they have learned to disclose and share more of themselves with their husbands; singles not yet at that stage – had to deal with judgment and “pagbabalewala” which hurts them the most – a kind of betrayal of trust- friends are for fun and forgetting problems – reminisce about happy times together, not really about trials gotten through – instead opt to go through these alone interactions must remain happy; value emotional endurance more than “opening up”- open up more through platforms (mas madali, mas hindi mahihiya, less possibility of seeing reactions/ dismissal) but also most afraid of back-biters

- music becomes escape – means to be happy and to relate to when late at night (nag-eemote)

- lifestyle/ talk shows much appreciated – of course, host authenticity is important, but also advice – want to know how to fix themselves – relationships and fashion, hobbies, tipid tips, completeness of details

- news- koreanovelas – spunky leads- game shows- musical variety- good market for unlitext – since prefer to

relate to barkada in detached manner – opt to send pahapyaw jokes and quotes (pagpaparamdam)

- also good for landlines – calling reserved for family and best friends, value telebabad time, cheap and easy

- also good for magazines – mostly Cosmopolitan and FHM – checking out other fashions, tips, kung bagay ba itsura nung mga babae; unlike 25-34 (gauging competition)

- group by paper (boring and outdated), communication (interactive – landline, mobile, internet – involving, young, uso), cable, TV – catering to everyone (middle class, middle aged)

- for social networking, counting friends (like affluent actives, and checking out where others are now, btu in less mean spirited way), 2 use multiply but more for (hi-res) pictures and shopping (value having online album), unlike affluent actives who don’t really like multiply because more complicated to upload – value ease of use

F, 25-34, C2D- wanting to uplift oneself – guilt because of feelings of having failed parents; wanting to assert one’s worth despite being alone, not having finished school, feeling that there’s something missing then throwing oneself into relationship, losing virginity - prone to religiosity- chona? – no real deep trials except pinapagsabihan ng asawa

-- gusto kong maging sikat vs. ayaw kong maging tanga vs. gusto ko kasama ako sa pinaguusapan, ginagawa ng mga kaibigan (left out)

- fear of investing oneself (betrayal of trust – through philandering and separation turning into weak social attachments) vs. fear of being worthless/ insufficient (having done the betraying themselves, or being left behind turning into controlling own aggressiveness) vs. fear of disclosure/ abandonment (not being listened to (binalewala) after trusting turning into relying on self to endure pains – no one else to rely on)

- more “practical”, proactive, goal-centric – even in platform use – group “simple life”: landline, TV, radio (basic, necessities, homebody); “luho”, pambata, busy feel, pero meron din ako para hindi mahuli – mobile, internet, movies, cable; oldies, pang-tambay, may nalalaman pero mas pampahinga lang/ pag walang magawa – newspaper, magazine, tabloid

- differences especially seen in mobile/ landline values: landline seen as more practical, whole family can use, and mahabaan, for emergency, way to reach everyone (relatively have fixed talking schedules, unlike affluent actives who prefer to be out and about instead of having a “routine”); cellular phones only for text and call when needed, don’t forward or message en masse, only 2 younger tried joining clans, one only when bored but doesn’t take phone everywhere – even do not like using phones for music or games, use separate gadgets

M, 25-34, C2D- wary of women who now cheat – say it hurts more, because cheating for women means lack of love, but all flirt with women, go out, say it’s natural – attribute women’s philandering to technology making it easy. They themselves use text for flirting, but are careful- Half only have landlines for internet, other than that, mostly for business to have stable number when working from home; others more dependent on cellular phones

F, 25-34 Tin-tin the girl really really close to her mom, lambingan with family (they gave me all that I asked for), have boyfriend in London – not really open to leaving family (wouldn’t know what she’s do without them)Tin-tin – single: wouldn’t know what she would do without her family, almost to the point of not really wanting to get married, mahilig manlambing, “lahat naman binigay nila sakin” Single: has older boyfriend who supplies everything for family (way to help family), angry at father, but not vengeful, instead remains quiet – just as mother did before she died, allows him to continue favoring younger sister even if she feels neglected Other single girl – father more ‘responsible”, stricter (come home on time, etc.), feels she has to take care of her mother, but generally privileged upbringing till recentlyMarried: all have “textmates” from time to time – just fun – all three have “tested” husbands through text; fairly committed mothers – two are working (one coming from broken family, does nto want same to happen, one got pregnant early and wants to discipline daughters to not do the same)

Similar to what a word cloud makes you understand

But, I still want you to feel the process of it.

“Codebook”

List of a good mix of responses.Cluster common answers.


15 minutesAnalyze the comments you get

on your Facebook account.


BasicsVISUALIZATION


MODELING“Craft”

Formality

Upscale/ High-class

Mass market but formal, serious

High-class and highly formal tone

Mass market and casual, colloquial, friendly

High-class and casual, colloquial, friendly

From what you know, what are the two main drivers of social media community success?

5 minutes

Map 5-10 different brands

Factor 1 Factor 2

Brand 1 High High

Brand 2 High Medium

Brand 3 Medium Medium

Brand 4 Medium Low

Brand 5 Low Low

Factor 1 Factor 2 Factor 3 Factor 4 Factor 5

Brand 1

Brand 2

Brand 3

Brand 4

Brand 5

CHARTS:)

PIEBARLINERADARSCATTER

SHARESTRENGTHGROWTH“SPREAD”POSITION

0"

20000000"

40000000"

60000000"

80000000"

10000000"

12000000"

14000000"

16000000"

18000000"

Walmart"

Family"Guy"

Eminem

"Amazon

.com

"Target"

Lil"W

ayne

"Facebo

ok"

Samsung"M

obile"USA

"Subw

ay"

Drake"

Youtub

e"Starbu

cks"

Adam"Sandler"

Nicki"M

inaj"

Rihann

a"Ba

rack"Obama"

Katy"Perry"

South"Park"

The"Simpson

s"Michael"Ja

ckson"

Wiz"Khalifa"

Usher"

Will"Smith

"Macy's"

Lady"Gaga"

Taylor"SwiT"

Bob"Marley"

SkiUles"

Hou

se"

Beyonce"

CocaXCola"

Vin"Diesel"

Dr."Pepp

er"

Buffa

lo"W

ild"W

ings"

The"Hangover"

Disne

y"Oreo"

Spon

gebo

b"SquarePants"

Cand

y"Crush"Saga"

Kevin"Hart"

Megan"Fox"

Linkin"Park"

Jersey"Sho

re"

T.I."

The"Be

atles"

Farm

Ville"

Victoria's"Secret"

MiU"Rom

ney"

Reese's"

McD

onald's"

Global""Likers""

U.S."Page""Likers""

0" 50" 100" 150" 200"

Walmart"Family"Guy"

Eminem"Amazon.com"

Target"Lil"Wayne"Facebook"

Samsung"Mobile"USA"Subway"Drake"

Youtube"Starbucks"

Adam"Sandler"Nicki"Minaj"

Rihanna"Barack"Obama"

Katy"Perry"South"Park"

The"Simpsons"Michael"Jackson"

Wiz"Khalifa"Usher"

Will"Smith"Macy's"

Lady"Gaga"Taylor"SwiR"Bob"Marley"

SkiSles"House"

Beyonce"CocaVCola"Vin"Diesel"Dr."Pepper"

Buffalo"Wild"Wings"The"Hangover"

Disney"Oreo"

Spongebob"SquarePants"Candy"Crush"Saga"

Kevin"Hart"Megan"Fox"Linkin"Park"

Jersey"Shore"T.I."

The"Beatles"FarmVille"

Victoria's"Secret"MiS"Romney"

Reese's"McDonald's"

Millions'

Global""Likers""

U.S."Page""Likers""

0" 5" 10" 15" 20" 25" 30" 35"

Walmart"Family"Guy"

Eminem"Amazon.com"

Target"Lil"Wayne"Facebook"

Samsung"Mobile"USA"Subway"Drake"

Youtube"Starbucks"

Adam"Sandler"Nicki"Minaj"

Rihanna"Barack"Obama"

Katy"Perry"South"Park"

The"Simpsons"Michael"Jackson"

Wiz"Khalifa"Usher"

Will"Smith"Macy's"

Lady"Gaga"Taylor"SwiS"Bob"Marley"

SkiTles"House"

Beyonce"CocaWCola"Vin"Diesel"Dr."Pepper"

Buffalo"Wild"Wings"The"Hangover"

Disney"Oreo"

Spongebob"SquarePants"Candy"Crush"Saga"

Kevin"Hart"Megan"Fox"Linkin"Park"

Jersey"Shore"T.I."

The"Beatles"FarmVille"

Victoria's"Secret"MiT"Romney"

Reese's"McDonald's"

Millions'

U.S.'Page'"Likers"'

U.S."Page""Likers""

What patterns do you see?

What patterns do you see?

BEGIN WITH THE END IN MIND.

What do you want them to remember?

Decide on your flow first.

PATTERN. NARRATIVE. OUTLINE. Say what you’re going to say. Say it. Then, say what you said.

Donald Lim, former CEO of Yehey, Burger King and MRM

Gain a better appreciation of what makes us special as Filipinos on social media, as opposed to the often-publicized Western statistics 1) size of following2) category – person/organization/program/device,etc.3) origin

Rules of Thumb

LIST - CLUSTER - SORT

DESCRIBE YOUR DATA HONESTLY- LET’S GROW OUR CODEBOOKS

MACRO MICRO

VISUALIZATION- FLOW FIRST, BEFORE CHARTS: WHAT’S YOUR STORY?- GROWTH - LINE OR AREA CHARTS; “DRIVERS”: MODELS - HIGH-CONTRAST COLORS: EMPHASIS

Good luck with creating your own data narratives!Let the drudgery begin.


Data & Analytics

Data Analysis Basics - Workshop (Frameworks)