Primary and secondary research on usage of mobile technology as medium for brand building of FMCG products. Mobile technologies included in this research paper are mobile phones, palmtops and tablet PCs.
4. Marketing and communicating to
customers via mobile technology
wherever they may be for a specific
purpose.
(i.e. visit a location, make a purchase
or capture a lead)
Mobile Marketing Association
7. Mobile marketing commands an increasing share of
marketing budgets, and organizations must ensure that their
mobile practices align with consumers’ attitudes and anticipated
behaviours.
It is estimated that annual spending on mobile advertising
alone will reach $2.55 billion in 2014, up from $734 million in
2010 a 71% increase in four years (eMarketer, 2010).
According to Forrester Research, 52% of companies say
that their top priority for mobile marketing strategy is to increase
customer engagement (Tsirulnilk, 2010).
15. 1 being least favourable and 5 being most favourable
MeanValue(5pointlikertscale)
Top three usages of the mobile device are phone calls, SMS, social networking.
20. Value in Percentage
15% of the respondents are currently using the mobile device to
find information about FMCG products.
21. Value in Percentage
Majority of the respondents are currently receiving marketing
Messages on their mobile devices.
22. Value in Percentage
37% are interested in receiving marketing messages related to FMCG products
23. ValueinPercentage
14% of the sample are probable to check out the product and 2% are very
probable to check out the product. (Online with direct marketing)
28. It is a statistical method used to describe variability among
observed variables in terms of a potentially lower number of
unobserved called factors.
In statistic, reliability is the consistency of a set of measurements
or of a measuring instrument, often used to describe a test.
It has been done to check the reliability of the components in
the factors.
29. Factor 1 ( Preference to receive marketing messages )
Factor 2 ( Response towards marketing messages )
Factor 3 ( Content of marketing messages )
Factor 4 ( Delivery Medium of marketing messages )
30. Factor 5 ( motivation to accept marketing messages )
Factor 6 ( Effect of relevant and permission based message on brand )
31. Reliability analysis of factor 1 is not possible as there is only
one variable
Reliability of factor 2 is not possible as there is only one variable
32.
33. .
In ANOVA we looked at the significance
difference between the variables.
ANOVA provides a statistical test of whether or
not the means of several groups are all equal.
Here we have taken Significance difference as
0.1.
34. • A Significance Difference in mean was observed for the
age with the Factor 1 and Factor 2
• A Significance Difference in mean was observed for the
gender with the Factor 2.
• A Significance Difference in mean was observed for
billing type with the Factor 1 and 2.
• It is also evident that women are more
interested in receiving the message in
comparison to men.
• 31-40 age group shows highest probability of
actually checking out the product.
35. • A Significance Difference in mean was observed for the age with the Factor 3
(V3, V4, V5, V7,V8).
• A Significance Difference in mean was observed for the gender with the Factor 3
(V3, V4, V5, V6,V8).
• A Significance Difference in mean was observed for billing type with the Factor
3(V3, V4, V5,V6,V7,V8).
• Favourable content of the marketing messages are Price discount
and New product information.
• Men give more preference to content preview in comparison to
women.
36. • A Significance Difference in mean was observed for the age with the Factor 4
(V10,V12,V13).
• A Significance Difference in mean was observed for the gender with the Factor 4
(V9,V10,V12,V13).
• A Significance Difference in mean was observed for the billing type with the
Factor 4(V11, V12, V13).
• Among all the age groups, 31-40 age group has highest
preference for SMS based marking message delivery.
• Prepaid owners give more preference to SMS based marking
message delivery in comparison to postpaid.
• Among all the age groups, 23-30 age group has highest
preference for mobile application based marking message
delivery.
• Men give more preference for mobile application based marking
message delivery in comparison to women.
37. • A Significance Difference in mean was observed for the age with the Factor 5
(V15,V16,V7).
• A Significance Difference in mean was observed for the gender with the Factor 5
(V14, V15,V16,V7).
• A Significance Difference in mean was observed for the billing type with the
Factor 5(V14, V15,V16,V7).
• Among all the age groups, 23-30 age group has highest
preference for feedback system in terms of marketing
messages.
• Most favoured factor to motivate consumers for accepting
mobile communication is availability of system to give feedback
of the product.
38. • A Significance Difference in mean was observed for the age with the Factor 6
(V19,V20,22).
• A Significance Difference in mean was observed for the gender with the Factor 6
(V18,V19, V20,V21,V22).
• A Significance Difference in mean was observed for the billing type with the
Factor 6 (V18,V19, V20,V21,V22).
• In 23-30 age group permission based, relevant marketing
message can improve Brand association and Brand image
&perception.
39. • Most favoured factor to motivate consumers for accepting mobile
communication is availability of system to give feedback of the
product.
• Favourable content of the marketing messages are Price discount
and New product information.
• It is evident that women are more interested in receiving the
message in comparison to men.
• Men give more preference to content preview in comparison to
women.
• Among all the age groups, 23-30 age group has highest
preference for mobile application based marketing message
delivery.
• Men give more preference for mobile application based marking
message delivery in comparison to women.
• In 23-30 age group permission based, relevant marketing
message can improve Brand association and Brand image &
perception.
40. • The study is based on small sample size
thus may not represent the universe.
• Sample was chosen randomly which could
tend to have a data bias.
• Timing of the study could have a bearing on
the results.
• TRAI guidelines