Online purchase preference of youngsters

8/20/2019 Online purchase preference of youngsters

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Online Purchase preference of

youngsters: Mobile or Desktop The truth about M Commerce

Team 7 :

Akshaya M (14AC01)

AkshayaChandrasekaran(14AC02)Harish V(14AC13)Kovendan KP(14AC1)!andini "(14AC22)


2/16

The rise of the SMART PHONE

• "mar# Phones are mo$i%e &hones 'i#h an &era#in "ys#em or "* They +ome 'i#h addi#iona% ,ea#-res s-+h as +amera and media&%ayer*

• The %as# . years have seen &henomena% ro'#h o, #his ind-s#ry/ a%%

over #he 'or%d*

• n ndia/ #hey have +a-sed a maor +hane in #he %i,es#y%e o,yo-ns#ers*

200200201020122014201

No.of smart phone users

!o*o, smar#&hone -sers


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Indian Market - Today


4/16

The Internet

•

"mar# &hones oer easy a++ess #o #he in#erne# #hro-h#heir servi+e &roviders/ +on#ri$-#in #o #he ro'#h o,in#erne# -sers in #he +o-n#ry*

• .0 o, in#erne# -sers in ndia are mo$i%e on%y5 +om&ared#o 2052. in deve%o&ed +o-n#ries*

6-ne12 6-ne13 +#13 8e+13 Mar14(9s#) 6-ne14(9s#)0

20

40

0

0

100

120

140

10

10

200 Mobile Internet Users

Mo$i%e n#erne# sers

1;

21

20

;0

1


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E- Commerce


6/16

M Commerce The ease o, a++ess o, #he in#erne# in mo$i%e &hones has iven rise #


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E – Traffic

=1 2012 =2 2012 =3 2012 =4 2012 =1 2013

0*00

2*00

4*00

*00

*00

10*00

12*00

Share of e-commerce Trac From Smartphone(% share)

"mar#&hone


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Primary Data Collection

>andom da#a amon s#-den#s and &ro,essiona%s $e#'een #he ae o, 2

More #han . o, #heres&onden#s 'ere s#-den#s*


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Cross Tabulation between the no. of visits and the no.of purchases in a month

>es&onden#s 'ereasked ho' o,#en #heyvisi# an on%ine s#ore in amon#h*

They 'ere #hen asked#o ive #he n-m$er o,&-r+hases #hey made#his mon#h*

14 o, #he &eo&%e 'hovisi#ed did no# makeany &-r+hases*


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Gadget Preference

?hi%e #he &re,eren+e ,or visi#in an on%ine si#e is a%mos# e@-a%$e#'een #he desk#o& and smar# &hone/ a%mos# 7 o, #he&eo&%e &re,er a desk#o& ,or a &-r+hase*


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No. of Purchases

1 #o .

10 #o 1.

. #o 10

More #han 1.

The mos# &-r+haseshave $een made $y

&eo&%e 'ho have visi#ed%eas# o,#en*

There is a des+endin&a##ern $e#'een #he

visi#s and no* o,&-r+hases

Inferences


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• 7. o, #he &eo&%e'ho visi# #he si#e 15.#imes a mon#h &re,er a%ao& desk#o& ,or&-r+hase*

• i*e* The &eo&%e 'homake #he mos#&-r+hases &re,erdesk#o&s*

•

A%so/.. o, #he&eo&%e 'ho visi# more#han 1. #imes &re,er adesk#o& ,or &-r+hase*

Inferences


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Inferences

.7 o, #he &eo&%e &re,er a desk#o& d-e #o Com,or#ness*

Ba+#ors in-en+in #he &re,eren+e o, 8esk#o& over Mo$i%e&hones


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Finding

TH9 T>TH AC9

Tho-h #raD+ ,rom mo$i%e devi+es seems #o$e in+reasin s#eadi%y/ mos# o, i# is ,rominde+isive $ro'sers*

A+#-a% &-r+hases remain %o' and mos# &eo&%e'ho visi# 95+ommer+e si#es -sin mo$i%es/

&re,er #heir desk#o&s ,or a &-r+hase*


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Mobile Conversion Rates among variousindustries

0

0*01

0*01

0*02

0*02

0*03

"mar# Phone Conversion >a#e

-r &rimary da#a +oin+ides 'i#h #he res-%#s o$#ained d-rin o#hers-rveys* Mo$i%es have a very %o' +onversion ra#e*


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Thank yo-

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Online purchase preference of youngsters