Ontela (B) Case Discussion – 

***Note on cluster analysis used in the case:

Standard statistical methods were used to group or “cluster” respondents together based on how similar their responses were.
This analysis considers similarities and response profiles across all questions (not individual questions).
This analysis does not presume that there will be a particular number of clusters. The statistical analysis guides the analyst to determine the number of clusters that best represent the survey respondents
This analysis did not consider any information beyond the data provided by the survey questions listed in Exhibit 1.

Answer ONLY the following questions for the case write up.

Which segment from among the six would you recommend as a target for PicDeck? Explain the logic and rationale behind your choice as well as any concerns you may have about the segment.

Develop a positioning statement for your target segment. (Make sure you review the lecture notes on writing a positioning statement).

Develop a positioning statement for wireless carriers. (Make sure you review the lecture notes on writing a positioning statement).KEL451
Revised March 20, 2015

©2015 by the Kellogg School of Management, Northwestern University. This case was prepared by Patrick Dupree, Christine Hsu,
Ryan Metzger, Fuminari Obuchi, Arun Sundaram, and Kari Wilson under the supervision of Professor Mohanbir Sawhney. It was
revised by Professor Kent Grayson. Cases are developed solely as the basis for class discussion. Cases are not intended to serve as
endorsements, sources of primary data, or illustrations of effective or ineffective management. To order copies or request permission
to reproduce materials, call 800-545-7685 (or 617-783-7600 outside the United States or Canada) or e-mail
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the Kellogg School of Management.


Ontela PicDeck (B):
Customer Segmentation, Targeting, and Positioning

The Quantitative Customer Segmentation Study

Although Joe Levy felt that the customer persona provided a good starting point to begin
thinking about PicDeck’s segmentation, he believed that he needed quantitative data to get a more
precise understanding of the relative attractiveness of different customer segments. This would
require data on end users regarding their preferences and behaviors related to mobile devices and
imaging. He therefore hired a market research firm to conduct a quantitative customer
segmentation study.

The firm conducted a national survey of 2,000 respondents who were selected from lists of
mobile telephone customers aged 15 and older. The questions in the survey ranged from
respondents’ current mobile phone behavior and camera experience to general technology
aptitude and price sensitivity. The survey questions are listed in Exhibit 1. The research firm
used a random sampling approach to ensure that the respondent sample accurately represented
nationwide wireless subscribers.

Analysis of Customer Survey Data

Identifying Segments—Cluster Analysis of Preference Data

The research firm performed a cluster analysis on the responses. A cluster analysis is a
statistical technique that identifies groups of customers who have similar survey response
patterns. The number of clusters is determined in part by how different the response patterns are.
If all survey respondents tend to give the same responses, then only one cluster is identified.

For this survey, six clusters of respondents were identified, each with a different response
pattern. Details of each cluster are provided in Exhibit 2, which lists the mean responses to each
question for each cluster.

For the exclusive use of C. Medina, 2022.

This document is authorized for use only by Carlos Medina in UF MKT 5806 Fall 2022 Mod 1 taught by TIM HALLORAN, Georgia Institute of Technology from Aug 2022 to Oct 2022.


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