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Changing Landscape of UX Research
Big Data & Big Ideas T.S.Balaji	
  
June	
  2015	
  
Agenda
Changing	
  Landscape	
  of	
  UX	
  Research	
  
02	
  
Who	
  we	
  are?	
  
Philosophy	
  
FoundaFon	
  
Programs	
  
Big	
  Data	
  
Modeling	
  
Closing	
  
We solve customer
problems by utilizing
research & analytics, in a
customer centered design
process to deliver
experiences that meet or
exceed customer
expectations.
04	
  
Hi
UX	
  @	
  Cox	
  
We	
  are	
  a	
  group	
  of	
  User	
  Experience	
  Strategists,	
  Researchers,	
  Data	
  ScienFsts,	
  Visual	
  Designers	
  &	
  Prototypers	
  that	
  come	
  
together	
  on	
  a	
  regular	
  basis	
  to	
  solve	
  customer	
  and	
  business	
  problems.	
  	
  We	
  are	
  passionate	
  about	
  understanding	
  customer	
  
behaviors	
  and	
  creaFng	
  experiences	
  that	
  are	
  delighSul	
  in	
  a	
  way	
  that	
  makes	
  recommenders	
  out	
  of	
  our	
  customers.	
  We	
  use	
  
different	
  techniques	
  to	
  understand	
  our	
  customers	
  behaviors	
  through	
  research	
  and	
  analyFcs	
  to	
  inform	
  design	
  to	
  drive	
  
innovaFve	
  soluFons.	
  These	
  soluFons	
  then	
  allow	
  us	
  to	
  drive	
  adopFon,	
  increased	
  usage,	
  lowering	
  cost	
  and/or	
  increasing	
  
sales	
  depending	
  on	
  the	
  experience	
  domain.	
  	
  
UX	
  
The	
  team:	
  
Research	
  &	
  AnalyFcs	
  +	
  
Design	
  
9
4Research
&
Analytics
Design
We	
  now	
  have	
  4	
  UX	
  
UX	
  Strategists,	
  3	
  Visual	
  
Designers,	
  1	
  Content	
  Strategist.	
  
We	
  combined	
  the	
  Research	
  &	
  
AnalyFcs	
  funcFon	
  to	
  start	
  
generaFng	
  insights.	
  	
  
	
  
Interns	
  and	
  fresh	
  graduates	
  play	
  
a	
  criFcal	
  role	
  in	
  the	
  group,	
  our	
  
promise	
  is	
  to	
  develop	
  these	
  
individuals	
  for	
  the	
  next	
  level.	
  	
  
5
Design Interns/
fresh graduates
4
R+A Interns/
fresh graduates
05	
  
Schools represented in our group
06	
  
We	
  drive	
  design	
  from	
  data	
  and	
  
this	
  could	
  be	
  qualitaFve	
  and	
  
quanFtaFve	
  in	
  nature	
  
Data	
  
The	
  Physical	
  space	
  &	
  context	
  in	
  
which	
  the	
  experience	
  unfolds	
  for	
  
the	
  customer	
  needs	
  to	
  be	
  
considered	
  
Physical	
  
Different	
  types	
  of	
  properFes	
  and	
  
devices	
  need	
  to	
  be	
  considered	
  in	
  
an	
  experience	
  
Digital	
  
Approach to Design
We	
  drive	
  design	
  through	
  the	
  eyes	
  of	
  the	
  customer	
  &	
  	
  u:lizing	
  
insights	
  gleamed	
  from	
  data	
  &	
  analysis.	
  The	
  manifestaFon	
  of	
  
the	
  design	
  can	
  be	
  in	
  the	
  digital	
  space	
  or	
  in	
  the	
  physical	
  space	
  
regardless,	
  considers	
  the	
  impact	
  of	
  physical	
  &	
  digital	
  space	
  on	
  
the	
  design	
  of	
  the	
  experience.	
  	
  
Data	
   Digital	
   Physical	
  
08	
  
Design
We	
  think	
  about	
  design	
  as	
  the	
  creaFon	
  of	
  a	
  plan	
  for	
  the	
  construcFon	
  of	
  a	
  product	
  or	
  service;	
  we	
  think	
  about	
  experience	
  design	
  in	
  terms	
  of	
  human	
  to	
  human	
  &	
  human	
  
to	
  computer	
  interacFons.	
  We	
  think	
  about	
  it	
  in	
  terms	
  of	
  customer	
  behaviors	
  and	
  uFlizing	
  design	
  to	
  facilitate	
  those	
  behaviors	
  in	
  a	
  way	
  that	
  benefits	
  the	
  customer	
  as	
  
well	
  as	
  the	
  business.	
  	
  
03	
  PROTOTYPING	
  
Rudimentary	
  working	
  model	
  of	
  a	
  product	
  or	
  
informaFon	
  system,	
  usually	
  built	
  to	
  try	
  new	
  
ideas	
  or	
  as	
  model	
  to	
  learn	
  from.	
  	
  
04	
  CONTENT	
  STRATEGY	
  
Planning,	
  development,	
  and	
  management	
  of	
  
content—wrifen	
  or	
  in	
  other	
  media.	
  	
  
01	
  UX	
  STRATEGY	
  
Taking	
  the	
  informaFon	
  about	
  the	
  user	
  and	
  
informaFon	
  about	
  the	
  business	
  and	
  turning	
  
that	
  into	
  an	
  approach	
  for	
  the	
  User	
  Experience.	
  
02	
  VISUAL	
  DESIGN	
  
Method	
  of	
  communicaFon,	
  and	
  problem-­‐
solving	
  through	
  the	
  use	
  of	
  type,	
  space	
  and	
  
image.	
  	
  
09	
  
Design Process
We	
  use	
  an	
  iteraFve	
  design	
  process	
  
to	
  create	
  delighSul	
  product	
  &	
  
service	
  experiences.	
  We	
  uFlize	
  our	
  
understanding	
  of	
  customer	
  
behaviors	
  in	
  combinaFon	
  with	
  our	
  
understanding	
  of	
  technology	
  to	
  
create	
  soluFons	
  that	
  help	
  
customers	
  and	
  our	
  business.	
  The	
  
iteraFve	
  process	
  helps	
  us	
  test	
  
soluFons	
  in	
  controlled	
  
environments	
  or	
  within	
  markets.	
  
Research	
  
Get	
  it	
  Built	
  
Launch	
  Go	
  Deep	
  
+	
  
Go	
  Broad	
  
_	
  
Get	
  It	
  
Started	
  
Research	
  
&	
  Analy:cs	
  
Monitor	
  
10	
  
Design– Blueprints
Blueprints	
  provide	
  the	
  foundaFon	
  to	
  the	
  digital	
  experience	
  
3
Deep Blue
#20274d
Topper Blue
#00192a
Navy Blue
#383d5d
Dark Blue
#045690
Common Color Uses
Text: Charcoal Black #252525
Links: #0679ca
Line separators: Light Gray 1
#dadadc
COLORS
Blue
#146ea6
Light Blue 1
#678ace
Gray Blue
#8aa6c1
Charcoal Black
#252525
Dark Gray
#6c6c6d
Gray
#979798
Light Gray 1
#dadadc
Light Gray 2
#f4f4f4
Accent Orange
#f8af00
Accent Magenta
#d12a98
Accent Green
#55b829
Primary Action
#03406a
Secondary Action
#0679ca
7
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11	
  
Approach to Research & Analytics
Health	
  This	
  is	
  a	
  view	
  into	
  the	
  health	
  of	
  the	
  product/service	
  in	
  the	
  field.	
  	
  InteracFons	
  of	
  customers	
  with	
  product/service	
  or	
  a	
  
product/service	
  interacFon	
  with	
  systems	
  result	
  in	
  the	
  end	
  experience	
  for	
  the	
  customer.	
  Both	
  of	
  these	
  interacFons	
  at	
  the	
  
highest	
  level	
  make	
  up	
  the	
  customer’s	
  percepFon	
  of	
  a	
  product/service.	
  	
  	
  
DiagnosFc	
  Diagnosis	
  begins	
  with	
  a	
  symptom	
  or	
  problem	
  experienced,	
  we	
  use	
  the	
  symptom	
  to	
  invesFgate	
  through	
  the	
  available	
  data	
  
likely	
  causes.	
  	
  	
  
Strategic	
  This	
  is	
  typically	
  an	
  12-­‐18month	
  view	
  of	
  things	
  to	
  focus	
  on	
  a	
  product/service.	
  These	
  are	
  typically	
  driven	
  by	
  quanFtaFve	
  
models	
  that	
  help	
  in	
  ascertaining	
  investments	
  in	
  the	
  product/service	
  and/or	
  in	
  a	
  porSolio	
  of	
  product/service.	
  	
  
	
  
	
  
Health	
  
	
  
	
  
Diagnos:c	
  
	
  
	
  
Strategic	
  
12	
  
Research & Analytics
DESIGN	
  RESEARCH	
  	
  
Number	
  of	
  invesFgaFve	
  techniques	
  used	
  to	
  add	
  context	
  
and	
  insight	
  to	
  the	
  design	
  process.	
  
PRE-­‐LAUNCH	
  ASSESSMENT	
  
Assessing	
  the	
  risk	
  associated	
  with	
  the	
  launch	
  of	
  a	
  product	
  
or	
  service	
  in	
  relaFonship	
  to	
  the	
  ease	
  of	
  use/usability	
  of	
  the	
  
product/service.	
  
POST	
  LAUNCH	
  ASSESSMENT	
  
Understanding	
  the	
  performance	
  of	
  a	
  product/service	
  in	
  the	
  
field.	
  Typically	
  administered	
  as	
  a	
  large	
  scale	
  survey.	
  
MODELING	
  	
  
Understanding	
  human	
  behaviors	
  and	
  represenFng	
  them	
  
using	
  mathemaFcal	
  equaFons	
  in	
  order	
  to	
  drive	
  usability	
  
and/or	
  saFsfacFon	
  associated	
  with	
  product/service.	
  
CROSS	
  CHANNEL	
  ANALYTICS	
  
Understanding	
  of	
  customer	
  behavior	
  or	
  customer	
  related	
  
acFviFes	
  across	
  channels	
  like	
  web,	
  IVRU	
  &	
  call	
  center	
  in	
  
addiFon	
  to	
  acFviFes	
  performed	
  by	
  agent	
  on	
  behalf	
  of	
  the	
  
customer.	
  
360	
  ANALYSIS	
  
Complete	
  analysis	
  of	
  a	
  product	
  or	
  service	
  across	
  design	
  
research,	
  surveys,	
  analyFcs	
  and	
  percepFon	
  informaFon	
  
provided	
  customers	
  in	
  surveys.	
  
13	
  
UX Research Methods
*Inspired	
  from	
  landscape	
  of	
  UX	
  research	
  methods	
  from	
  ChrisFan	
  Rohrer	
  
What People Do
What People Say
Why & How
To Fix
Usability Testing - lab
Benchmark Testing - lab
User Production
Focus Groups
Interviews - phone
Intercept Surveys
Observational
Interviews – lab or field
Product Surveys
Web Analytics
Business Intelligence /
Data Mining
A/B Testing
How many &
How much
USER Field Surveys
hfp://www.nngroup.com/arFcles/which-­‐ux-­‐research-­‐methods/	
  
Concept Testing
Diary/Camera Studies
Ethnographic Field Studies
We	
  use	
  specific	
  methods	
  to	
  
address	
  different	
  set	
  of	
  problems.	
  
The	
  	
  different	
  types	
  of	
  studies	
  
provide	
  insights	
  and	
  help	
  us	
  in	
  
understanding	
  issues	
  from	
  a	
  
qualitaFve	
  and	
  a	
  quanFtaFve	
  
standpoint.	
  	
  
14	
  
Research & Analytics
DESIGN	
  RESEARCH	
  	
  
Number	
  of	
  invesFgaFve	
  techniques	
  used	
  to	
  add	
  context	
  
and	
  insight	
  to	
  the	
  design	
  process.	
  
PRE-­‐LAUNCH	
  ASSESSMENT	
  
Assessing	
  the	
  risk	
  associated	
  with	
  the	
  launch	
  of	
  a	
  product	
  
or	
  service	
  in	
  relaFonship	
  to	
  the	
  ease	
  of	
  use/usability	
  of	
  the	
  
product/service.	
  
POST	
  LAUNCH	
  ASSESSMENT	
  
Understanding	
  the	
  performance	
  of	
  a	
  product/service	
  in	
  the	
  
field.	
  Typically	
  administered	
  as	
  a	
  large	
  scale	
  survey.	
  
MODELING	
  	
  
Understanding	
  human	
  behaviors	
  and	
  represenFng	
  them	
  
using	
  mathemaFcal	
  equaFons	
  in	
  order	
  to	
  drive	
  usability	
  
and/or	
  saFsfacFon	
  associated	
  with	
  product/service.	
  
CROSS	
  CHANNEL	
  ANALYTICS	
  
Understanding	
  of	
  customer	
  behavior	
  or	
  customer	
  related	
  
acFviFes	
  across	
  channels	
  like	
  web,	
  IVRU	
  &	
  call	
  center	
  in	
  
addiFon	
  to	
  acFviFes	
  performed	
  by	
  agent	
  on	
  behalf	
  of	
  the	
  
customer.	
  
360	
  ANALYSIS	
  
Complete	
  analysis	
  of	
  a	
  product	
  or	
  service	
  across	
  design	
  
research,	
  surveys,	
  analyFcs	
  and	
  percepFon	
  informaFon	
  
provided	
  customers	
  in	
  surveys.	
  
15	
  
Research + Analytics: Measurement Framework
User	
  Experience	
  Measurement	
  Framework	
  
Loyalty
Trust
Delight
Usable
Usefulness
16	
  
Research + Analytics: Primary Scales
Usability	
  &	
  SaFsfacFon	
  
The	
  SaFsfacFon	
  Scale	
  is	
  a	
  standardized	
  measure	
  of	
  how	
  well	
  a	
  service/product	
  meets	
  customer	
  needs.	
  	
  	
  
It	
  is	
  calculated	
  from	
  a	
  12-­‐item	
  amtudinal	
  survey	
  scored	
  on	
  a	
  Likert	
  scale.	
  
	
  
The	
  System	
  Usability	
  Scale	
  (SUS)	
  is	
  a	
  standardized	
  measure	
  of	
  the	
  perceived	
  usability	
  of	
  a	
  system.	
  	
  	
  
It	
  is	
  calculated	
  from	
  a	
  10-­‐item	
  amtudinal	
  survey	
  scored	
  on	
  a	
  Likert	
  scale.	
  
	
  
Exceed	
  Expecta:ons	
  
Scores	
  among	
  the	
  top	
  10%	
  of	
  products	
  
Below	
  Expecta:ons	
  
Scores	
  among	
  the	
  bofom	
  40%	
  of	
  products	
  
Meets	
  Expecta:ons	
  
Scores	
  in	
  the	
  upper	
  40%	
  of	
  products	
  
Way	
  Below	
  Expecta:ons	
  
Scores	
  among	
  the	
  bofom	
  10%	
  of	
  products	
  
10th 	
  50th 	
  90th	
  
Percen:le 	
  Percen:le 	
  Percen:le	
  
	
  -­‐4.0	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  -­‐3.5	
  	
  	
  	
  	
  	
  	
  	
  -­‐3.	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  -­‐2.5	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  -­‐2.0	
   	
  -­‐1.	
  	
  	
  	
  -­‐1.0	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  -­‐1.5	
  	
  	
  	
  	
  	
  	
  	
  -­‐0.5	
  	
  	
   	
  0.5	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  1.0 	
  1.5	
  	
  	
  	
  	
  	
  	
  	
  	
  2.0	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  2.5	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  3.0	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  3.5	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  4.0	
  
	
  	
  	
  	
  	
  	
  Meets	
  Expecta:ons	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  Way	
  Below	
  Expecta:ons	
   	
  	
  	
  	
  	
  Below	
  Expecta:ons	
   Exceed	
  Expecta:ons	
  
-­‐1.3	
  
1.3
	
  
0.0	
  
From the dawn of
civilization until 2003,
humankind generated
five exabytes of data.
Now we produce five
exabytes every two
days…and the pace is
accelerating.
Eric Schmidt,
Google 2010
18	
  
BIG DATA
Three	
  V’s	
  of	
  Big	
  Data	
  
Variety  –  Different  types  of  
data  elements,  structured  to  
unstructured
Velocity  –  Batch,  Real  ;me,  
streams  etc.    
Volume  –  Size  in  TB,  tables,  
transac;ons  &  records  
VARIETY
VELOCITY
VOLUME
BIG
DATA
19	
  
Big Data Maturity
Where	
  we	
  are	
  to	
  where	
  we	
  are	
  going	
  
Setup	
  
40%	
  
ReporFng	
  
40%	
  
Analysis	
  
10%	
  
Modeling	
  
10%	
  
Typical	
  
Setup	
  
10%	
  
ReporFng	
  
10%	
  
Analysis	
  
40%	
  
Modeling	
  
40%	
  
Target	
  State	
  
20	
  
Cross Channel Analytics Platform
Our	
  Big	
  Data	
  PlaSorm	
  
CUSTOMER
ATTRIBUTES
IVR
CALL CENTER
DIGITAL PROPERTIES
•  EASIER ACCESS TO DATA
•  ROOT CAUSE/DRILL
DOWN ANALYSIS
•  COHORT ANALYSIS
•  PREDICTIVE MODELING
•  TEXT ANALYTICS
CLOUD
SURVEY
WORK ORDERS
Big Data in 360 AnalysisUFlizing	
  data	
  from	
  qualitaFve,	
  quanFtaFve,	
  percepFon	
  &	
  behavioral	
  informaFon.	
  
AnalyFcs	
   Surveys	
  
Usability	
  TesFng	
  	
   Unstructured	
  
Data	
  
360	
  
Analysis	
  
Customer	
  behaviors	
  through	
  our	
  
digital	
  properFes,	
  machine	
  to	
  
machine	
  	
  interacFons,	
  back	
  end	
  
system	
  logs,	
  Test	
  &	
  Target	
  
Analy:cs	
  
Surveys	
  conducted	
  through	
  our	
  
digital	
  properFes	
  other	
  surveys	
  
conducted	
  through	
  tradiFonal	
  
means	
  
Surveys	
  
Lab	
  &	
  online	
  usability	
  tesFng,	
  
upfront	
  design	
  research	
  
Usability	
  Tes:ng	
  
Customer	
  comments	
  through	
  
different	
  sources,	
  notes	
  from	
  
agents,	
  arFcle	
  feedback	
  
Unstructured	
  Data	
  
We	
  uFlize	
  data	
  collected	
  through	
  different	
  sources	
  to	
  create	
  a	
  
comprehensive	
  view	
  of	
  insights	
  where	
  we	
  could	
  tell	
  a	
  story	
  around	
  the	
  
why,	
  what	
  and	
  how	
  customers	
  feel	
  as	
  they	
  experience	
  our	
  products	
  or	
  
services.	
  	
  
360	
  
21	
  
22	
  
Modeling - Basics
Capture:	
  The	
  rich	
  and	
  complex	
  
elements	
  that	
  shape	
  an	
  experience.	
  
Math:	
  Represent	
  the	
  experience	
  captured	
  
through	
  mathemaFcal	
  models	
  
Predict:	
  UFlize	
  the	
  models	
  to	
  predict	
  the	
  
changes	
  in	
  the	
  experience	
  	
  
In	
  addiFon	
  to	
  my	
  team	
  here	
  at	
  Cox,	
  I	
  would	
  not	
  be	
  in	
  this	
  posiFon	
  without	
  my	
  modeling	
  gurus	
  Clyde	
  Heppner	
  &	
  Tuan	
  Tran.	
  My	
  sincerest	
  thanks	
  to	
  them	
  for	
  being	
  
paFent	
  with	
  me	
  and	
  my	
  quesFons	
  as	
  well	
  as	
  sharing	
  the	
  wealth	
  of	
  experience.	
  	
  
Sarah	
  has	
  a	
  PhD	
  in	
  CogniFve	
  
Sciences	
  from	
  Georgia	
  State	
  
University,	
  with	
  a	
  background	
  
in	
  memory	
  and	
  decision	
  
making.	
  	
  
Sarah Cavrak
Megan’s	
  background	
  is	
  a	
  
unique	
  blend	
  of	
  industrial	
  
engineering,	
  staFsFcs,	
  and	
  
psychology,	
  with	
  qualitaFve	
  
and	
  quanFtaFve	
  analyFc	
  skills	
  
in	
  industrial	
  and	
  educaFonal	
  
semngs	
  .	
  
Megan Lutz
Sheri	
  has	
  over	
  25	
  years	
  
professional	
  experience	
  with	
  
experFse	
  in	
  UX	
  and	
  product	
  
research	
  and	
  strategy,	
  leading	
  
top	
  performing	
  cross	
  
funcFonal	
  teams	
  and	
  
delivering	
  highly	
  successful	
  
interacFve	
  product	
  soluFons	
  
that	
  effecFvely	
  align	
  business	
  
and	
  customer	
  needs	
  	
  
Sheri
Leslie	
  has	
  a	
  PhD	
  in	
  CogniFve	
  
Sciences	
  from	
  Georgia	
  State	
  
University,	
  with	
  a	
  background	
  
in	
  memory	
  and	
  decision	
  
making.	
  With	
  five	
  years	
  of	
  
professional	
  experience	
  within	
  
the	
  UX	
  field,	
  Leslie	
  has	
  
experFse	
  in	
  qualitaFve	
  and	
  
quanFtaFve	
  research	
  
methodologies	
  	
   	
  	
  
Leslie
Jagan	
  has	
  over	
  13+	
  years	
  of	
  
professional	
  experience,	
  with	
  
a	
  background	
  in	
  decision	
  
science,	
  data	
  warehousing,	
  
reporFng,	
  predicFve	
  and	
  
prescripFve	
  analyFcs.	
  	
  
Jagan
Feel free to say hi!
We are friendly and social
6305	
  B,	
  Peachtree	
  Dunwoody	
  Rd.	
  	
  
Atlanta,	
  GA	
  30338	
  
404-­‐234-­‐0444	
  
t.s.balaji@cox.com	
  

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Big Data and Big Ideas: Quantitative Modeling in UX Research - T.S. Balaji

  • 1. Changing Landscape of UX Research Big Data & Big Ideas T.S.Balaji   June  2015  
  • 2. Agenda Changing  Landscape  of  UX  Research   02   Who  we  are?   Philosophy   FoundaFon   Programs   Big  Data   Modeling   Closing  
  • 3. We solve customer problems by utilizing research & analytics, in a customer centered design process to deliver experiences that meet or exceed customer expectations.
  • 4. 04   Hi UX  @  Cox   We  are  a  group  of  User  Experience  Strategists,  Researchers,  Data  ScienFsts,  Visual  Designers  &  Prototypers  that  come   together  on  a  regular  basis  to  solve  customer  and  business  problems.    We  are  passionate  about  understanding  customer   behaviors  and  creaFng  experiences  that  are  delighSul  in  a  way  that  makes  recommenders  out  of  our  customers.  We  use   different  techniques  to  understand  our  customers  behaviors  through  research  and  analyFcs  to  inform  design  to  drive   innovaFve  soluFons.  These  soluFons  then  allow  us  to  drive  adopFon,  increased  usage,  lowering  cost  and/or  increasing   sales  depending  on  the  experience  domain.     UX  
  • 5. The  team:   Research  &  AnalyFcs  +   Design   9 4Research & Analytics Design We  now  have  4  UX   UX  Strategists,  3  Visual   Designers,  1  Content  Strategist.   We  combined  the  Research  &   AnalyFcs  funcFon  to  start   generaFng  insights.       Interns  and  fresh  graduates  play   a  criFcal  role  in  the  group,  our   promise  is  to  develop  these   individuals  for  the  next  level.     5 Design Interns/ fresh graduates 4 R+A Interns/ fresh graduates 05  
  • 6. Schools represented in our group 06  
  • 7. We  drive  design  from  data  and   this  could  be  qualitaFve  and   quanFtaFve  in  nature   Data   The  Physical  space  &  context  in   which  the  experience  unfolds  for   the  customer  needs  to  be   considered   Physical   Different  types  of  properFes  and   devices  need  to  be  considered  in   an  experience   Digital   Approach to Design We  drive  design  through  the  eyes  of  the  customer  &    u:lizing   insights  gleamed  from  data  &  analysis.  The  manifestaFon  of   the  design  can  be  in  the  digital  space  or  in  the  physical  space   regardless,  considers  the  impact  of  physical  &  digital  space  on   the  design  of  the  experience.     Data   Digital   Physical  
  • 8. 08   Design We  think  about  design  as  the  creaFon  of  a  plan  for  the  construcFon  of  a  product  or  service;  we  think  about  experience  design  in  terms  of  human  to  human  &  human   to  computer  interacFons.  We  think  about  it  in  terms  of  customer  behaviors  and  uFlizing  design  to  facilitate  those  behaviors  in  a  way  that  benefits  the  customer  as   well  as  the  business.     03  PROTOTYPING   Rudimentary  working  model  of  a  product  or   informaFon  system,  usually  built  to  try  new   ideas  or  as  model  to  learn  from.     04  CONTENT  STRATEGY   Planning,  development,  and  management  of   content—wrifen  or  in  other  media.     01  UX  STRATEGY   Taking  the  informaFon  about  the  user  and   informaFon  about  the  business  and  turning   that  into  an  approach  for  the  User  Experience.   02  VISUAL  DESIGN   Method  of  communicaFon,  and  problem-­‐ solving  through  the  use  of  type,  space  and   image.    
  • 9. 09   Design Process We  use  an  iteraFve  design  process   to  create  delighSul  product  &   service  experiences.  We  uFlize  our   understanding  of  customer   behaviors  in  combinaFon  with  our   understanding  of  technology  to   create  soluFons  that  help   customers  and  our  business.  The   iteraFve  process  helps  us  test   soluFons  in  controlled   environments  or  within  markets.   Research   Get  it  Built   Launch  Go  Deep   +   Go  Broad   _   Get  It   Started   Research   &  Analy:cs   Monitor  
  • 10. 10   Design– Blueprints Blueprints  provide  the  foundaFon  to  the  digital  experience   3 Deep Blue #20274d Topper Blue #00192a Navy Blue #383d5d Dark Blue #045690 Common Color Uses Text: Charcoal Black #252525 Links: #0679ca Line separators: Light Gray 1 #dadadc COLORS Blue #146ea6 Light Blue 1 #678ace Gray Blue #8aa6c1 Charcoal Black #252525 Dark Gray #6c6c6d Gray #979798 Light Gray 1 #dadadc Light Gray 2 #f4f4f4 Accent Orange #f8af00 Accent Magenta #d12a98 Accent Green #55b829 Primary Action #03406a Secondary Action #0679ca 7 Hero........................ Open Sans Regular, 53/57px Header 1........ Open Sans Regular, 40/44px Header 2..................... Open Sans Regular, 30/34px Header 3............................. Open Sans Regular, 24/28px Header 4................................... Open Sans Regular, 20/24px Header 5.................................... Open Sans Bold, 18/22px Header 6....................................... Open Sans Bold, 16/20px Paragraph Spacing Body Copy..................................... Open Sans Bold, 16/20px Legalese............................................ Open Sans Regular, 14/18px Price Details ...................................... Open Sans Bold, 12/16px AaOpen Sans Regular AaOpen Sans Semibold AaOpen Sans Bold TYPOGRAPHY Subhead Subhead Paragraph Text Paragraph Text Paragraph Text 20px 20px 20px 30px
  • 11. 11   Approach to Research & Analytics Health  This  is  a  view  into  the  health  of  the  product/service  in  the  field.    InteracFons  of  customers  with  product/service  or  a   product/service  interacFon  with  systems  result  in  the  end  experience  for  the  customer.  Both  of  these  interacFons  at  the   highest  level  make  up  the  customer’s  percepFon  of  a  product/service.       DiagnosFc  Diagnosis  begins  with  a  symptom  or  problem  experienced,  we  use  the  symptom  to  invesFgate  through  the  available  data   likely  causes.       Strategic  This  is  typically  an  12-­‐18month  view  of  things  to  focus  on  a  product/service.  These  are  typically  driven  by  quanFtaFve   models  that  help  in  ascertaining  investments  in  the  product/service  and/or  in  a  porSolio  of  product/service.         Health       Diagnos:c       Strategic  
  • 12. 12   Research & Analytics DESIGN  RESEARCH     Number  of  invesFgaFve  techniques  used  to  add  context   and  insight  to  the  design  process.   PRE-­‐LAUNCH  ASSESSMENT   Assessing  the  risk  associated  with  the  launch  of  a  product   or  service  in  relaFonship  to  the  ease  of  use/usability  of  the   product/service.   POST  LAUNCH  ASSESSMENT   Understanding  the  performance  of  a  product/service  in  the   field.  Typically  administered  as  a  large  scale  survey.   MODELING     Understanding  human  behaviors  and  represenFng  them   using  mathemaFcal  equaFons  in  order  to  drive  usability   and/or  saFsfacFon  associated  with  product/service.   CROSS  CHANNEL  ANALYTICS   Understanding  of  customer  behavior  or  customer  related   acFviFes  across  channels  like  web,  IVRU  &  call  center  in   addiFon  to  acFviFes  performed  by  agent  on  behalf  of  the   customer.   360  ANALYSIS   Complete  analysis  of  a  product  or  service  across  design   research,  surveys,  analyFcs  and  percepFon  informaFon   provided  customers  in  surveys.  
  • 13. 13   UX Research Methods *Inspired  from  landscape  of  UX  research  methods  from  ChrisFan  Rohrer   What People Do What People Say Why & How To Fix Usability Testing - lab Benchmark Testing - lab User Production Focus Groups Interviews - phone Intercept Surveys Observational Interviews – lab or field Product Surveys Web Analytics Business Intelligence / Data Mining A/B Testing How many & How much USER Field Surveys hfp://www.nngroup.com/arFcles/which-­‐ux-­‐research-­‐methods/   Concept Testing Diary/Camera Studies Ethnographic Field Studies We  use  specific  methods  to   address  different  set  of  problems.   The    different  types  of  studies   provide  insights  and  help  us  in   understanding  issues  from  a   qualitaFve  and  a  quanFtaFve   standpoint.    
  • 14. 14   Research & Analytics DESIGN  RESEARCH     Number  of  invesFgaFve  techniques  used  to  add  context   and  insight  to  the  design  process.   PRE-­‐LAUNCH  ASSESSMENT   Assessing  the  risk  associated  with  the  launch  of  a  product   or  service  in  relaFonship  to  the  ease  of  use/usability  of  the   product/service.   POST  LAUNCH  ASSESSMENT   Understanding  the  performance  of  a  product/service  in  the   field.  Typically  administered  as  a  large  scale  survey.   MODELING     Understanding  human  behaviors  and  represenFng  them   using  mathemaFcal  equaFons  in  order  to  drive  usability   and/or  saFsfacFon  associated  with  product/service.   CROSS  CHANNEL  ANALYTICS   Understanding  of  customer  behavior  or  customer  related   acFviFes  across  channels  like  web,  IVRU  &  call  center  in   addiFon  to  acFviFes  performed  by  agent  on  behalf  of  the   customer.   360  ANALYSIS   Complete  analysis  of  a  product  or  service  across  design   research,  surveys,  analyFcs  and  percepFon  informaFon   provided  customers  in  surveys.  
  • 15. 15   Research + Analytics: Measurement Framework User  Experience  Measurement  Framework   Loyalty Trust Delight Usable Usefulness
  • 16. 16   Research + Analytics: Primary Scales Usability  &  SaFsfacFon   The  SaFsfacFon  Scale  is  a  standardized  measure  of  how  well  a  service/product  meets  customer  needs.       It  is  calculated  from  a  12-­‐item  amtudinal  survey  scored  on  a  Likert  scale.     The  System  Usability  Scale  (SUS)  is  a  standardized  measure  of  the  perceived  usability  of  a  system.       It  is  calculated  from  a  10-­‐item  amtudinal  survey  scored  on  a  Likert  scale.     Exceed  Expecta:ons   Scores  among  the  top  10%  of  products   Below  Expecta:ons   Scores  among  the  bofom  40%  of  products   Meets  Expecta:ons   Scores  in  the  upper  40%  of  products   Way  Below  Expecta:ons   Scores  among  the  bofom  10%  of  products   10th  50th  90th   Percen:le  Percen:le  Percen:le    -­‐4.0                        -­‐3.5                -­‐3.                          -­‐2.5                      -­‐2.0    -­‐1.        -­‐1.0                      -­‐1.5                -­‐0.5        0.5                    1.0  1.5                  2.0                    2.5                            3.0                            3.5                        4.0              Meets  Expecta:ons                                                        Way  Below  Expecta:ons            Below  Expecta:ons   Exceed  Expecta:ons   -­‐1.3   1.3   0.0  
  • 17. From the dawn of civilization until 2003, humankind generated five exabytes of data. Now we produce five exabytes every two days…and the pace is accelerating. Eric Schmidt, Google 2010
  • 18. 18   BIG DATA Three  V’s  of  Big  Data   Variety  –  Different  types  of   data  elements,  structured  to   unstructured Velocity  –  Batch,  Real  ;me,   streams  etc.     Volume  –  Size  in  TB,  tables,   transac;ons  &  records   VARIETY VELOCITY VOLUME BIG DATA
  • 19. 19   Big Data Maturity Where  we  are  to  where  we  are  going   Setup   40%   ReporFng   40%   Analysis   10%   Modeling   10%   Typical   Setup   10%   ReporFng   10%   Analysis   40%   Modeling   40%   Target  State  
  • 20. 20   Cross Channel Analytics Platform Our  Big  Data  PlaSorm   CUSTOMER ATTRIBUTES IVR CALL CENTER DIGITAL PROPERTIES •  EASIER ACCESS TO DATA •  ROOT CAUSE/DRILL DOWN ANALYSIS •  COHORT ANALYSIS •  PREDICTIVE MODELING •  TEXT ANALYTICS CLOUD SURVEY WORK ORDERS
  • 21. Big Data in 360 AnalysisUFlizing  data  from  qualitaFve,  quanFtaFve,  percepFon  &  behavioral  informaFon.   AnalyFcs   Surveys   Usability  TesFng     Unstructured   Data   360   Analysis   Customer  behaviors  through  our   digital  properFes,  machine  to   machine    interacFons,  back  end   system  logs,  Test  &  Target   Analy:cs   Surveys  conducted  through  our   digital  properFes  other  surveys   conducted  through  tradiFonal   means   Surveys   Lab  &  online  usability  tesFng,   upfront  design  research   Usability  Tes:ng   Customer  comments  through   different  sources,  notes  from   agents,  arFcle  feedback   Unstructured  Data   We  uFlize  data  collected  through  different  sources  to  create  a   comprehensive  view  of  insights  where  we  could  tell  a  story  around  the   why,  what  and  how  customers  feel  as  they  experience  our  products  or   services.     360   21  
  • 22. 22   Modeling - Basics Capture:  The  rich  and  complex   elements  that  shape  an  experience.   Math:  Represent  the  experience  captured   through  mathemaFcal  models   Predict:  UFlize  the  models  to  predict  the   changes  in  the  experience    
  • 23. In  addiFon  to  my  team  here  at  Cox,  I  would  not  be  in  this  posiFon  without  my  modeling  gurus  Clyde  Heppner  &  Tuan  Tran.  My  sincerest  thanks  to  them  for  being   paFent  with  me  and  my  quesFons  as  well  as  sharing  the  wealth  of  experience.     Sarah  has  a  PhD  in  CogniFve   Sciences  from  Georgia  State   University,  with  a  background   in  memory  and  decision   making.     Sarah Cavrak Megan’s  background  is  a   unique  blend  of  industrial   engineering,  staFsFcs,  and   psychology,  with  qualitaFve   and  quanFtaFve  analyFc  skills   in  industrial  and  educaFonal   semngs  .   Megan Lutz Sheri  has  over  25  years   professional  experience  with   experFse  in  UX  and  product   research  and  strategy,  leading   top  performing  cross   funcFonal  teams  and   delivering  highly  successful   interacFve  product  soluFons   that  effecFvely  align  business   and  customer  needs     Sheri Leslie  has  a  PhD  in  CogniFve   Sciences  from  Georgia  State   University,  with  a  background   in  memory  and  decision   making.  With  five  years  of   professional  experience  within   the  UX  field,  Leslie  has   experFse  in  qualitaFve  and   quanFtaFve  research   methodologies         Leslie Jagan  has  over  13+  years  of   professional  experience,  with   a  background  in  decision   science,  data  warehousing,   reporFng,  predicFve  and   prescripFve  analyFcs.     Jagan
  • 24. Feel free to say hi! We are friendly and social 6305  B,  Peachtree  Dunwoody  Rd.     Atlanta,  GA  30338   404-­‐234-­‐0444   t.s.balaji@cox.com