PPT on Primary Market Research Methodologies

© 2014 ConceptSpring
Primary Market Research
Methodologies Overview
Primary Market Research
Methodologies Overview
Elaine Chen
© 2014 ConceptSpring
Why do research?
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You are not your customer
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A few tenets
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Not a sales pitch
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eep your eyes and ears open
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!e open minded
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Primary Market
Research:
Sausage making
instructions
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" classes o# research

Problem Research

To understand who the buyers and users are

To understand the problem statement

To understand the context in which the product will
be used

To understand use cases

Solution Research

To understand the usability and utility o the product

To help prioriti!e the eature set

To understand pricing elasticity

To understand customer satisaction
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$he anatomy o# a research program

Clearly articulate a hypothesis to be tested
"a#a research goals and ob$ecti%es&

'e(ne the mar#et segment to do research in

'e%elop sub$ect recruitment criteria according
to the de(nition o the chosen segment

Pic# a methodology

Run the research program

Crunch the data

Ta#e steps based on (ndings
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E%ample recruitment &uestionnaire
'(egment) people with sleep issues*
• )hat is your age* gender and proession+ "terminate once
age,gender -uota has been (lled or the matching segment&
• )hat is your household income+ "terminate i ./xx#&
• 0re you interested in learning more about your sleep+ "terminate i
not&
• 0re you currently encountering sleep problems+ "terminate i not&
• 0re you currently under the care o a doctor or your sleep issues+
"terminate i true&
• 1ow many nights in an a%erage wee# are you encountering sleep
issues+ "select between 223&
• Please describe the sleep issues you are currently encountering
"chec# all that apply&4 "cannot all asleep5 multiple awa#enings5
cannot go bac# to sleep ater awa#ening5 snoring spouse5 etc&
• 'o you currently share your bed+ "partner* child* pet& 6 so7 how
many nights in an a%erage wee# is your sleep a8ected by your bed
partner"s&+
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Qualitative versus
quantitative
Qualitative
• 9pen ended7 you are
ha%ing a con%ersation
• 0necdotal7 you deri%e
meaning rom each
con%ersation
• Re-uires excellent listening
and obser%ation s#ills
• :est done ace to ace "or
at least by %ideo S#ype or
by %oice call&
• :est used or exploratory
research where you are
trying to get to #now a
problem or a persona
Quantitative (>1 sam!les"
• Close ended7 you are
administering a
-uestionnaire
• Statistical7 you deri%e
meaning rom loo#ing at
aggregate results
• Re-uires systematic
analysis s#ills
• :est done %ia on2line
sur%ey "or* in the olden
days* %ia phone sur%ey&
• :est used or con(rmation
research where you are
trying to %eriy , -uantiy
what you thin# is important
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+ualitative, then &uantitative
The -ualitati%e pass helps you de%elop your -uantitati%e pass and interpret
the result with context and meaning
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#ommon metho$ologies
Qualitative (%&
sam!les"
• Contextural inter%iew
• 9bser%ation , shadowing
• 6mmersion
• ;ongitudinal diary study
• Photo essay
• etc
Quantitative (>1 sam!les"
• Sur%eys
• 9n line sur%eys
• Con$oint analysis
• Pricing studies
• ?onadic
• ?ultiple monadic
• @an )estendorp
• > etc
• Customer satisaction7
APS* P,? (t
• )eb testing
• 0,: split* ?ulti%ariate
• )eb analytics
• > etc
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Some qualitative
techniques
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#onte'tural interview: interview
su()ect where !ro$uct will (e use$
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(tructure the interview #or consistency,
ask open ended &-s, let the su./ect lead
Set up
gear
Warm
up chat
“Tell us the story of sleep
in your house”
House
tour
Discuss
sleep
problems
Probe
expect-
ations
Show prouct
iea if an only
if there!s if time
left o"er an
they as#
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O.servation) learning things people cannot
articulate
6n this pro$ect* we were trying to understand peopleBs showering habits4 )e
contracted the research to an ethnographic research company* who too#
shower ootage o %olunteer sub$ects in a nudist colony4
)e were able to measure things li#e C time people stand acing the
showerhead %ersus the other way* etc4 that no one can tell us with words4
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O.servation) learning things people will
not articulate
6n this pro$ect* we were trying to understand peopleBs inotainment needs and
multitas#ing beha%ior in the car4 6n this example* the sub$ect "a real estate
agent& was tal#ing on the phone and scheduling appointments in her boo#
while dri%ing at D0mph ")ith our cowor#ers in the bac#* who were shadowing
her or Eh that day &
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0mmersion) .ecome the user
6n this pro$ect* we were trying to understand the usability o competiti%e C0'
programs4 )e had our in house C0' experts try out F or 4 applications4 They
spent F days on each application* designing the same set o parts and
documenting their experience learning and mastering each application4
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1ongitudinal diary studies) learn things over
days2weeks, not over 34"h
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Photo essays) use imagery to capture the
conte%t
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5sa.ility .enchmark) 6ive users a task, watch
them struggle and learn why
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7ocus groups) not a #an8 9ynamics hard to
manage, e%pensive to do right
6mage credit7 msresearchinc4com
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Some quantitative
techniques
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7irst things :rst) the product concept
6n an on line sur%ey* you ha%e 2 pages to ma#e your point about your
productBs %alue proposition and its rele%ance to your sur%ey respondents4 =or
all practical purposes* you are creating an ad4 The e8ecti%eness o your
sur%ey depends on this ad4 6n%est in the creati%e content to ma#e your point4
Get a mar#eter to help do it right4
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On line surveys ; gauging interest
Construct your sur%ey careully or easy tabulation o results4
:est practice is to use 3 point scales* except or speci(c methodologies that
re-uire 10 point scales "e4g4 Aet promoter score H see slide in customer
satisaction section&
There are techni-ues to IcodeJ open ended responses H read more here4
http7,,www44uwm4edu,cuir,resources,upload,Planning2Council2-ualitati%e2
analysis2handout4pd
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Con/oint analysis

Con$oint analysis measures the %alue the mar#et
places on each eature o your product and
predicts the %alue o any combination o eatures4

1ow it wor#s7
• 0s# -uestions that orce respondents to ma#e trade2o8s
among eatures
• 'etermine the %alue they place on each eature based
on the trade2o8s they ma#e
• Simulate how the mar#et reacts to %arious eature trade2
o8s you are considering

Read more at7
http7,,www4pragmaticmar#eting4com,resources,co
n$oint2analysis2101Ksthash4d-LG%TpS4dpu
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Pricing research) Monadic ; a8k8a8 an Westendorp 'the
indle team did this and came up with ?@@ *
• Show the product concept* then as# these 4 -uestions with
a ree response7
• 0t what price would you consider the product to be so
expensi%e that you would not consider buying it+ "Too
expensi%e&
• 0t what price would you consider the product to be priced so
low that you would eel the -uality couldnBt be %ery good+ "Too
cheap&
• 0t what price would you consider the product starting to get
expensi%e* so that it is not out o the -uestion* but you would
ha%e to gi%e some thought to buying it+ "Mxpensi%e,1igh Side&
• 0t what price would you consider the product to be a bargainN
a great buy or the money+ "Cheap,Good @alue&
• Chart cumulati%e re-uencies4 6ntersection O ideal price4
• Read more here4
http7,,en4wi#ipedia4org,wi#i,@anP)estendorpQsPPricePSensiti
%ityP?eter
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Customer satis#action measure) Net
Promoter (core
• Show the product concept* then as# this -uestion on a 10
point scale "1 O not at all li#ely* 10 O %ery li#ely&7
• I1ow li#ely is it that you would recommend Ryour productS to a
riend Ror amily* or colleague etcS+J
• Categori!e responses7
• Promoters O T* 10 H your loyal enthusiasts
• Passi%es O U* E H satis(ed but unenthusiastic
• 'etractors O 02D H unhappy* can damage brand by word o mouth
• Calculate the Aet Promoter Score as ollows7 "APS&
• APS O C Promoters 2 C'etractors
• Calibrating yoursel
• 201F scores7 0pple laptop "best computer company& H UDC5
Vaiser "best health insurance company& H FDC 2 (nd your industry
or comparables
• Read more here7
http7,,www4netpromoter4com,why2net2promoter,#now,
© 2014 ConceptSpring
Customer satis#action measure) Product 2
Market 7it

Show the product concept* then as# this -uestion
on a F point scale "1 O not at all disappointed* 2
O somewhat disappointed* F O %ery
disappointed&
• I1ow would you eel i they could no longer use Rthe
productS+J

6 o%er 40C o responses O F "%ery disappointed&
you ha%e achie%ed Product ?ar#et =it

Read more here7
http7,,www4startup2mar#eting4com,using2sur%ey2io
,
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A word o# caution) know your statistics and
e%perimental design

The mean o any metric is meaningless
without the %ariance4 ;earn how to do
analysis o %ariance "0A9@0& properly to
interpret your results correctly4 Start with
the student2t test and build up rom there

The best 0A9@0 e8ort with the best
experimental design alls down with
insuWcient sample si!e4

300 is the absolute minimum

3000 is the best practice number

1000 is a good compromise
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A2! split testing
6mage credit7 http7,,www4smashingmaga!ine4com
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Multivariate testing
6mage credit7 http7,,%isualwebsiteoptimi!er4com
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We. analytics
6mage credits7 emaginewebmar#eting4com* http7,,www4openwebanalytics4com,
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$he possi.ilities are endless
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*chenelai
ne
(log+conce!ts!ring
+com
$hank you

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