Ontela PicDeck (B): Customer
Segmentation, Targeting, and Positioning
Group B1
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DP/07/20
ABHISHEK PANDA
ADITYA SURESH WADEKAR
AMARJEET KUMAR
AMIRTHAVARSHINI L J
ANKIT VIJAYNARAYAN MISHRA
ANSHUMAN MAJHI
PRABAL GUPTA
SAMRIDHI JAKHAR
SHYAM PRASAD GHOSH
Important Variables
Most Useful variables
● Q1 - This question talks about the technology
aptitude a segment has. Also signifies which
segments have issue while uploading a photo
● Q11 - Early adopters would be preferred so
that the picdeck creates a customer base
early on who are tech enthusiast
● Q13 - This question talks about the
willingness to pay which will eventually lead
to revenues
● Q6, Q7, Q8, Q9 – These questions are
directly related to the significant features of
the offered product. They talk about the value
each segment prefers and hence can be
used in targeting different segments
Least Useful variables
● Q3, Q5 - Services offered by Picdeck are
related to the transferring of the pictures and
not pertaining to the quality of pictures.
These questions only talk about the quality
factor which is not relevant to Picdeck
● Q12 - All the 6 clusters have a similar
answer for this and this has less
differentiability.
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Profiling Clusters
*Reverse of Q1
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Customer Lifetime Value
Retention
Transactions
Profitability
C1. Professionals - Ind.
MED
MED
HIGH
C2. Professionals - Family
HIGH
HIGH
VERY HIGH
C3. Teenagers
LOW
VERY HIGH
LOW
C4. Young Adults
MED
HIGH
MED
C5. Homemakers/Part-Time
HIGH
MED
MED
C6. Middle Aged/Elderly
HIGH
LOW
MED
RESULT
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Cluster Evaluation
WTP for the service
C5
C3
C2
C1
C4
C6
Pay own bill (ATP)
The upper quadrant represents the clusters having higher willingness as well as ability to pay for the services. Based on the
population size, C1 i.e. working professionals (individuals) seems to be the most lucrative among all 6. Also, they value
services such as email and social media, which translates to higher propensity for features catering to email and facebook,
thus providing additional revenue streams.
Among C2 (Professionals with family) and C5 (home-makers), C2 provides higher opportunity for cross functional service
revenue as compared to C5, though both the segments have nearly equivalent segment sizes.
C1 i.e. individual working professionals would be the primary target cluster, followed by C2, as the
synergies among the clusters would result in lower cost to acquire and attract.
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Survey Questionnaire
Asking the right questions to the right audience is essential to obtain reliable data
which in turn will have a large impact on management decisions.
The major factors that can affect the questions asked in a survey are:
➔ The ultimate objective of what we are looking to find out or achieve
➔ How the surveyor plans to use the information collected in drawing conclusions
➔ Any preconceived notion that one might hold about the target audience
➔ Past experience of the surveyor, relevant to the current situation
➔ The surveyor’s opinion of what are the important factors for which they need
input
➔ The user personas defined by the surveyor into which they try to fit in the
respondents, which in turn can affect further questions
Demographics & Media Use Information
Being a technological product, age distribution would play a vital role in determining the adoption rate of the service. C3
having a greater distribution of age < 25, indicates that is a youth driven sample. Similarly, c6 cluster represents a older
population as per its distribution. Thus, age related variables can be used as a proxy for tech savviness and adoption of new
technology.
Magazine preferences indicates the behavioral traits of the clusters, which could be used to create personas. Variability of the
preferences across the cluster would be essential to consider it as an essential piece of information. For example, women
magazine preference is constant throughout the clusters, which makes it redundant.
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Demographics & Media Use Information
Since the service is highly dependent on internet for transfer of pictures, internet usage across the clusters is essential to
determine the propensity of users. C1, C3 and C4 are high on internet usage while C2, C5 and C6 are on the lower side,
which makes them less attractive as clusters.
Preference across plans (data and message) would be essential for the carriers to craft the services as per the target
segments. There has been a shift across from data plan to message plan as we move from C1 to C6.
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Persona development before quantitative cluster analysis
Pros
● Persona development provides in-depth
understanding of a consumer
●
As questions are unstructured in persona
development process, we can customize
the questions according to the interview
which results in better insights about the
consumers and their problems
●
Persona development helps us interpret
and understand social interactions
●
Persona development also helps us
understand why a certain phenomenon
occurs
Cons
● As persona development findings are
interpreted from small no. of sample so, it
cannot be applied to larger populations
●
In persona development, it is more difficult
to generate information that is definitively
factual
●
Quantitative cluster analysis strips all
issues down to facts and figures, all
ambiguity of language, interpretation, and
emotion is removed.
●
If persona development is followed by
quantitative analysis, it might lead to
confirmation bias as we try to fit data into
already made personas.
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