PersonasAngela BrogsdaleCapella University.docx

Personas
Angela Brogsdale
Capella University

Part A: Persona
The persona I am creating is Dinethia Robinson. Dinethia is a
20-year-old, who is in her third year of college at Lock Haven
University. Dinethia is currently pursuing a general bachelor’s
degree at Lock Haven University. She currently lives in the off-
campus housing and shares an apartment her best friend Ashley.
Dinethia is a frequent humanitarian and spends most of her time
doing community activities for children in lower income
neighborhoods. Dinethia is considered, by many, to be an
introvert. She would rather spend her weekends in the apartment
rather than out partying. She is a very laid-back individual with
a great heart and hopes to become a Social Worker or Child
Therapist.
Dinethia is an only child and comes from a middle-class family.
Her family lives in a small town in middle Georgia. Her
fascination for community service was fostered here in her
youth. Dinethia was never one to be selfish with frivolous
items, she always had an open heart and loves helping others.
Dinethia isn’t concerned too much with the popular trends of
modern society, rather following the beat of her own drum. She
is a pretty level-headed individual, rarely losing her temper. She
frequently does her research on any products or services before
she purchases a new item.
Dinethia persona would fall under the user category. She is
using a product, the website, to determine what she will order
from the restaurant. Dinethia strongly believes that ordering
online would help reduce any unnecessary time in calling due to
the ease of the system. She also has the capability of checking
her order accuracy before submittal.
Task Analysis – Human User Ordering a Meal in a Restaurant
Task Name:Ordering a Meal in a Restaurant

Activity Performed/By Whom
Materials, Tools, or Resources Used in Task
Step 1
Dinethia, Enter restaurant, ask for take out
Step 2
Hostess directs Dinethia to bar
Menu
Step 3
Bartender greets Dinethia and provides menu
Step 4
Bartender takes Dinethia order
POS system
Step 5
Send to back of house
Step 6
Cook Read/Prepare order
Food slip/kitchen appliances etc.
Step 7
Bartender brings food to Dinethia
Step 8
bartender Bring Dinethia’s check
Check folio
Step 9
Bartender Collect check and payment
Check folio
Step 10
Bartender Return to table with change or credit card receipt
Check folio
Step 11
Dinethia drives home with food
Check folioPossible Task Flow – Human User Ordering a Meal
Using an Online System

Task Name:
Activity Performed/By Whom (Human Role or Online System?)
Materials, Tools, or Resources Used in Task
Step 1
Dinethia-access website
Computer, phone
Step 2
Dinethia- access menu
Computer, phone
Step 3
Dinethia-add order to cart
Computer, phone
Step 4
Dinethia-checkout/review order.
Computer, phone
Step 5
Make payment/submit order
Computer, phone
Step 6
Cook receives/makes order/packs order
POS system
Step 7
Dinethia-enter restaurant/provides order #
Car
Step 8
Dinethia - wait for server to bring out food
Step 9
Server-bring Dinethia food
To-go containers
Step 10
Dinethia-leave restaurant
car
The biggest factor that separates the two components is less

human interaction. This can vary by consumer technology
knowledge. Some customers may prefer a human interaction
over a computer. Also, less of an error ordering online as there
may be an error with the server inputting the order.
Different personas from varying demographics would follow the
same series of events. I know for this section we were to create
and apply a different persona, but I instead chose to interview
several of my coworkers. These individuals tend to range from
their early 20s to late 50s. This sample group followed the same
process as reflected in tables one and two when ordering food
with the only variations being the food that they order. This
consistency is caused by the individual knowing what they want
to order, when they place the order. While the name of the
restaurant may change, restaurants such as Frog Hollow have
very similar menu items. Therefore, even if an individual has
never eaten at that restaurant, they have a general idea of what
they would want to eat when the decision is made to place the
order.
Part C: Design Strategies
The human factor that I would like to take into consideration
and focus on for the design of this website is that of memory
and attention. The human brain categorizes memory in two
forms, long/short term memory or working memory. Working
memory is unstable and can only store so much info. If
something were to grab an individual’s attention while they are
performing a task, the working memory may be lost during the
midst of this interaction.
This is an important consideration because the user may forget
what they ordered or the running total of their order if they
should become distracted. Distractions occur at any time and
could occur from a simple interaction. They could be at a social
gathering where there is a lot of background noise or the phone
could ring in the other room while they are in the process of
placing an order. Such distractions could cause the user to have
to restart their order, or even duplicate their order without
knowing.

To remedy this concern, a section of the screen will contain the
current total and the items which are to be ordered. This
partition of the ordering screen will be placed on the right-hand
side of the application and will be visible on every page of the
website. This will allow individuals to know what they have
already place to order and what their total for the order is.
S w
910A22
PARLE-G
R Chandrasekhar wrote this case under the supervision of
Professor Miranda Goode solely to provide material for class
discussion.
The authors do not intend to illustrate either effective or
ineffective handling of a managerial situation. The authors may
have
disguised certain names and other identifying information to
protect confidentiality.
Richard Ivey School of Business Foundation prohibits any form
of reproduction, storage or transmission without its written
permission. Reproduction of this material is not covered under
authorization by any reproduction rights organization. To order
copies
or request permission to reproduce materials, contact Ivey
Publishing, Richard Ivey School of Business Foundation, The

University
of Western Ontario, London, Ontario, Canada, N6A 3K7; phone
(519) 661-3208; fax (519) 661-3882; e-mail [email protected]
Copyright © 2010, Richard Ivey School of Business Foundation
Version: (A) 2010-10-21
In December 2009, Pravin Kulkarnii, general manager, Parle
Products Pvt. Ltd. (Parle), a leading Indian
biscuit manufacturer, faced a difficult decision involving the
potential price increase of the company’s
flagship glucose biscuit brand, Parle-G. The input prices of two
major raw materials, sugar and wheat
flour, which comprised 55 per cent of manufacturing costs, had
risen during the past 18 months.
Consequently, the margins of Parle-G had decreased from 15
per cent of revenue to less than 10 per cent.
The pressure to reinstate margins to 15 per cent led Kulkarnii to
consider raising the price of Parle-G
biscuits.
Since Parle-G’s introduction in 1939, the biscuit brand had been
strongly associated with offering value for
money1 (VFM), a marketplace perception that had remained
unfaltering for more than 60 years. In fact, the
VFM perception was associated not only with Parle-G biscuits
but had come to define the entire glucose
biscuit category. Parle-G was sold to consumers in 46 stock
keeping units (SKUs) at 12 price points (see
Exhibit 1). The average price of Parle-G was approximately
US$1 per kilogram. For example, a packet of
15 biscuits weighing 82.5 grams (g) sold for a maximum retail
price (MRP) of INR4.00 (US$0.08).2
Worldwide, very few processed and ready-to-eat food items

were available for US$1.00 per kilogram.
Even the manufacturers of new glucose biscuit products were
forced to tow this price line to be minimally
competitive in the product category.
Parle had the distinction of having maintained the US$1.00 per
kilogram price point for Parle-G since
1990.3 In fact, VFM was the consumer perception that had led
Parle-G to become the largest selling biscuit
brand by volume in the world in 2002,4 as validated by a study
by global market research firm A C
Nielsen. That top ranking had since been retained by the brand.
1 Value for money referred to the consumer paying a minimum
price for a product while gaining maximum utility. The term
was frequently used in marketing consumer packaged goods,
always with reference to the buyer and not the seller.
2 On December 15, 2009, one U.S. dollar equaled 48.6 Indian
rupees.
3 Ranju Sarkar, “Price Warrior,” Business Standard, May 4,
2009; available at http://www.business-
standard.com/india/news/price-warrior/356973/, accessed
October 4, 2010.
4 Shweta Jain and Reeba Zachariah, “Parle G Largest Selling
Biscuit Brand in World,” Business Standard, March 14, 2002;
available at
http://www.rediff.com/money/2002/mar/14parle.htm, accessed
December 21, 2009.
This document is authorized for use only in Kyuseop Kwak's
SPR_2019_24760_Pricing and Revenue Management at
University of Technology Sydney from Jul 2019 to Sep 2020.

9B10A022
In January 2004, in its first attempt in 13 years to offset rising
costs, Parle had hiked the price of its 100-g
packet of 16 biscuits, from INR4.00 to INR 4.50. The 100-g
packet was Parle’s best-selling SKU,
contributing to 50 per cent of brand revenues every year. The
idea was to test the waters with the leading
SKU before increasing the prices of other SKUs. The company
had to roll back the increase quickly,
however, because sales of the 100-g packet dropped by more
than 40 per cent within six months. The
negative consumer reaction was spontaneous and nationwide,
forcing Parle to reinstate the previous pricing
of its Parle-G biscuits.
Four years later, management took remedial measures to deal
once again with rising costs. This time, Parle
focused specifically on reducing the weight, or grammage, of
the 100-g package. This reduction was done
in phases — first, from 100 g to 92.5 g in January 2008, then to
88 g in May 2008 and to 82.5 g in January
2009. The number of biscuits was also decreased from 16 to 15.
Consumers noticed these changes;
however, as long as the company did not tinker with the price,
consumers seemed to go along with the
grammage reduction.
Said Kulkarnii:
Biscuit is a regular consumption item in the overall food basket
which comprises 49 per
cent of the budget of an Indian family. There is a general

tendency among consumers
everywhere to look for bargains while shopping for food
categories. That explains the
price elasticity of demand in India for biscuits in general.
Price elasticity is particularly prevalent in the glucose category
of biscuits. It prevails
among all classes of both urban and rural consumers. Unlike the
“indulgent” variety of
biscuits consumed only occasionally, the “functional” variety of
glucose biscuits is a
staple diet among Indian urban consumers. Some classes of
urban consumers use it as a
supplement during both breakfast time and tea time. Some use it
as a daily source of
nutrition and calories. For all classes of rural consumers,
glucose biscuits are a major
source of energy and nourishment. Indian consumers don’t mind
the prices of premium
biscuits going up. But, with glucose category, they are price
sensitive. That is why I have
to proceed with caution.5
In addition to reducing the grammage across SKUs, the
company had undertaken cost-control measures to
safeguard margins. For example, Parle had brought
manufacturing centers closer to the wholesalers by
franchising production so as to reduce distribution costs. The
company had also consolidated buying and
entered into forward contracts with vendors of raw materials to
reduce supply chain costs. Additionally,
wax-coated paper had been replaced by bi-axially oriented
polypropylene (BOPP) paper to reduce
packaging costs.

The company could go only so far by using such measures. A
price hike seemed like a necessity to restore
margin levels, particularly because the company had ramped up
its own manufacturing capacity by 10 per
cent on an investment of INR500 million in 2008.6 A hike in
price had the potential to increase the margin
of Parle-G by 50 per cent and to perhaps restore it to the earlier
level of 15 per cent. But, if the experience
of 2004 was any indication, consumers would be extremely
sensitive to a price hike. Kulkarnii was caught
in a dilemma.
5 Based on a personal interview on June 04, 2010
6 Nishith Triveti, “Parle to Ramp Up Biscuit Manufacturing
Capacity,” Business Standard, August 13, 2008; available at
http://www.business-standard.com/india/news/ /331229/,
accessed February 22, 2010.
Page 3 9B10A022
INDIAN BISCUIT INDUSTRY
India was the third largest producer of biscuits in the world,
after the United States and China. Although 15
per cent of Indian biscuit production was exported, domestic
demand for biscuits fueled industry growth.

Biscuit manufacturing was divided into two sectors —
organized and unorganized. The former consisted of
60 per cent of the national market. The unorganized sector,
comprising mom-and-pop establishments and
catering to markets of the rural interior, did not have easy
access to bank credit, technology and
information systems. This sector was also largely outside the
national statistical data pool. Growth in the
Indian biscuit industry was largely organic because of the
limited scope for consolidation in the organized
sector.
Low-priced varieties ruled in the rural markets where players in
the unorganized sector had put up entry
barriers for branded biscuits. In comparison with most branded
counterparts, several times a day,
competitors in the rural market provided local stores with
freshly baked biscuits that carried the aroma of
newness, in an unbroken and powder-free form. These rural
competitors and local retailers had developed
long-standing relationships that branded players could not
easily change.
In the organized sector, the five main categories of biscuits
were glucose, marie, sweet, cream and milk.
Glucose was a high-volume, low-margin biscuit category that
represented 42 per cent of the biscuit market
and was accompanied by strong consumer expectations of low
price points. Sweet, cream and milk were
“indulgent” categories that carried premium prices. Marie was
an in-between category, used largely at tea
time. Parle-G was part of the glucose category.
The growth strategy of all biscuit majors was to secure the
migration from the entry-level glucose category
to the indulgent categories. The latter were available at price

points beginning at INR5.
The organized sector produced 1.7 million tons of biscuits per
annum, valued at INR110 billion in 2008.
The sector was growing at an average annual rate of 15 per
cent.7 The rate of growth of individual
categories varied. Low-priced categories traditionally grew at a
higher rate than premium categories. Of
late, however, the premium categories, which historically had
grown in the range of 8 to 10 per cent each
year, were not only catching up to the rate of growth of the low-
priced categories but were moving into a
range just above the 20 per cent range. This upward growth was
consistent with some positive factors in
Indian economy.
A study by McKinsey Global Institute, released in May 2007,
showed that the income levels of households
in India were rising, as were the consumption levels of many
goods and service categories. Focusing on
nine major consumption categories (including food products)
and 30 subcategories, the study concluded
that the percentage of spending on discretionary items would
grow dramatically, whereas the spending on
basic necessities would grow more slowly.8
The study classified Indian consumers into five categories on
the basis of individual annual incomes:
globals (those earning above INR1 million per annum, nearing
average international standards), strivers
(those earning between INR500,000 and INR1 million per
annum), seekers (those earning between
INR200,000 and INR500,000 per annum), aspirers (those
earning between INR90,000 and INR200,000

7 Indian Biscuits’ Manufacturers Association, “Biscuit Industry
in India – Status Paper”; available at
http://www.ibmabiscuits.in/industry-statistics.html, accessed
September 17, 2010.
8 www.mckinsey.com/mgi/publications/india “The Bird of
Gold: The Rise of India’s Consumer market,” published by
McKinsey Global Institute, McKinsey and Company ,May 2007
page 16 of 194 accessed September 2, 2010.
Page 4 9B10A022
per annum) and deprived (those earning less than INR90,000 per
annum). The seekers and the aspirers
together formed the middle class and were the backbone of
consumption for a variety of products and
services in India.
The study showed that the number of consumers in the deprived
category would decline, while the
aggregate income levels of the Indian middle class would
increase, together leading to a four-fold hike in
aggregate consumption (see Exhibit 2).
COMPANY BACKGROUND
In 1929, Parle had started its operations as a manufacturer of
candies in suburban Mumbai in western

India. A decade later, it diversified into making biscuits. The
company deployed state-of-the-art machinery
that provided automatic printing and packaging, and its biscuit
baking oven was the largest in Asia. Parle
had 10 manufacturing sites of its own, in addition to 60 contract
manufacturing facilities, located across
India. In terms of managerial focus, the biscuit market was
gaining ground at Parle, in part because it was a
larger market than confectionery.9
The company had 40 per cent share of the total biscuit market in
India and 15 per cent share of the total
confectionary market in India. Many of Parle’s products were
perceived as offering good value for money
and were market leaders in their respective categories. Parle
recorded a compound annual growth rate of 15
per cent. It had a research and development (R&D) wing
focused on new product development. Its role
was to use the customer insights, received from the field sales
force, in developing new brand extensions
and also new product categories, in both candies and biscuits.
Parle produced approximately 650,000 tons of biscuits per
annum, of which Parle-G, the flagship brand,
comprised 500,000 tons. The company recorded sales revenue of
INR35 billion in 2008/09, of which
Parle-G’s contribution alone was 68 per cent. Even within the
Parle-G brand, the single largest contribution
came from the INR4.00 SKU, which was contributing to 50 per
cent of the brand’s annual sales revenue.
The biscuit portfolio included not only Parle-G in the glucose
category but also Marie in the tea time
category and Hide n Seek, Monaco, Krack Jack, Cheeslings,
Jeffs, Sixer and Fun Centre in the premium
category. The margin of premium brands typically ranged

between 25 and 30 per cent. Parle-G, Monaco
and Krack Jack were considered to be the core brands because
of their individual contribution to the top
line. Although Parle clearly had a broad biscuit portfolio with
product offerings in each of the major biscuit
categories, there was room to grow Parle’s presence in the
premium category, which registered a growth
rate of approximately 20 per cent per annum.
Exports formed five per cent of Parle’s revenues. The company
had adopted a “follow the customer”
strategy of targeting the Indian diaspora,10 whereby the
potential customers were already aware of the
Parle-G brand in their home country. Parle had three contract
manufacturing facilities outside India — one
in Bangladesh and two in South Africa. All the facilities catered
to local demand; however, the bulk of
exports were manufactured in India.
9 Parle, “Smart Cookie,” press release, November 2004;
available at
http://www.parleproducts.com/media/media_press7.asp,
accessed February 22, 2010.
10 Disapora refers to persons of Indian origin working and
living outside India. An estimated 20 million Indians comprised
the
diaspora. The single largest majority of 3.5 million diaspora
lived in the countries of the Middle East.

9B10A022
Said Kulkarnii:
It is the domestic demand which drives Parle-G. The
opportunities for moving the tonnage
are greater in the home market than in any of the overseas
markets. Exports are less of a
priority for us, relatively speaking, because we believe that our
resources are better spent
on meeting local demand. Home market is also a market we
know best.11
Parle prized — and was keen on retaining — Parle G’s ranking
as the largest selling biscuit brand in the
world, by tonnage. Closely linked to this ranking were two
other rankings that were also valuable to Parle:
the company’s share of the domestic biscuits market at 40 per
cent and Parle-G’s share of the domestic
glucose category at 74 per cent. The latter rankings were based
on sales revenue.
CONSUMERS
The most widely used consumer classification system in India
was known as socio-economic classification
(SEC), which was developed by the Market Research Society of
India in the early 1980s. SEC was
uniquely suited to the Indian market. The basis of classification

was not the individual consumer but the
consumer’s household. In 2005/06, India had 207.1 million
households12 (see Exhibit 3), of which Parle-G
had penetrated 96.8 million households (see Exhibit 4). Its
penetration rate of the glucose category of the
Indian biscuits industry was 84 per cent.
The company segmented its customers for Parle-G into two
types: retail consumers and institutional
consumers. Children and mothers comprised the first segment.
Children formed 60 per cent of the target
audience for the company. The 5- to 14-year-old age group was
considered to represent both users and
influencers. This group, which formed approximately 20 per
cent of the population (see Exhibit 5), had the
potential to generate lifelong revenues for the brand. The brand
association started early because biscuits
were among the first ready-to-eat foods offered to children.
The second segment, the institutional consumers, included
hospitals, factories, railway stations, schools,
government offices and corporate offices, which usually
received a discount of 3 to 4 per cent on bulk
purchases. The institutional segment contributed to
approximately 10 per cent of Parle’s sales revenue.
Several Indian companies, even in the organized sector, focused
exclusively on the institutional segment.
Some of these companies regularly bid for official tenders to set
up kiosks at railway stations across the
country to sell a range of processed agro-products, including
biscuits.
COMPETITORS
It was not until 1996, when Britannia Industries Ltd. (BIL), a

British multinational, launched its Tiger
Glucose brand of biscuits, that Parle faced nationwide
competition in the domestic market in the glucose
category. In 2003, a new competitor, ITC Ltd. (ITC), an Indian
conglomerate with interests in hotels, agri-
businesses, paper products and retailing, launched Sunfeast
Glucose. Both new entrants were backed by
high-powered budgets. Parle-G continued, however, to rule the
mass market (see Exhibit 6).
Hindustan Unilever, a multinational consumer packaged goods
(CPG) company, had also entered the
glucose category in 2003. Its foray was an extension of its
faltering breads business. The company was
11 Based on a personal interview on June 04, 2010.
12 These data are from the last decennial national census held
in 2001.
Page 6 9B10A022
subcontracting manufacturing of its products at two locations. It
exited the biscuits business two years later
due, among other reasons, to a mismatch between costs and
margins. Parle also faced a few regional
players, whose impact was minimal at the national level.
Similar to Parle-G, both Tiger Glucose and Sunfeast Glucose

were being retailed at several SKUs, and
both had price points that averaged US$1 per kilogram. Rising
costs had affected the two new brands more
sharply because they were relatively new entrants. Their
experience with SEC penetration was similar to
Parle-G. Both had extensive retail network, built over years of
operations in Indian CPG business. Both
had built up brand equity with children in a short time, led by
strong advertising campaigns (see Exhibit 7).
Overseas majors, such as Nabisco in the United States, United
Biscuits in the United Kingdom and
Campbell Arnott’s of Australia, were eyeing the Indian biscuits
market, attracted by the potential of the
larger Indian foods market. Their focus was likely to be on the
premium category of biscuits for three
reasons: it was set to grow in future years, it was amenable to
brand building and it ensured higher
margins.
PRICING
Launched in 1939, Parle-G was targeted, from the beginning, at
the Indian mass market. Parle had
generally refrained from increasing the price of Parle-G, even
when it had no competition. In holding to the
price line, Parle had brought a disciplining factor to the Indian
market. The new entrants, BIL and ITC,
were under compulsion to keep prices low. When Parle opted
for reducing the weight of the biscuit, BIL
and ITC followed the leader.
Parle-G was priced at US$1.00 a kilogram. For decades, the
company had used a low price to build the
glucose category in India. Parle’s dominance in the category

was so strong that competitors such as BIL
(which entered the glucose category in 1996) and ITC (which
entered in 2003) did not adopt higher
pricing. They simply stayed the course of the market leader.
Decisions related to the margins for trade channels were
decentralized at the local level, whereas decisions
related to the end prices that the consumer paid were centralized
at the corporate office in Mumbai.
POSITIONING
Traditionally, Indian consumers had viewed all biscuits,
including glucose biscuits, more as a commodity
than as a brand. Prior to 1980, Parle glucose biscuits had been
called Parle Gluco. The name was changed
to Parle-G so that consumers could differentiate it from the
prevailing competition, which at the time was
restricted to the unorganized sector. A series of innovative
campaigns, in print and TV, were also
developed to drive home the health benefit of the brand.
However, the prevailing consumer perception was
that Parle-G, and the glucose biscuit category in general,
offered “value for money.” This perception was
reinforced by the price points of Parle-G’s SKUs.
Strength was a generic attribute to the glucose category.
Physical fitness carried an appeal for the young.
Boys, in particular, were drawn to evidence of muscular
strength. All glucose brands used the attribute of
strength in some form in their communications. Parle added a
new emotional layer to the core attribute to
arrive at a positioning that was unoccupied, competitive,
sustainable and contemporary. The new campaign
incorporated values such as honesty, sharing and caring to bring

home the product’s “goodness.” Riding on
Page 7 9B10A022
the equity of goodness, the brand was established as enabling
people to be true to who they were and to be
able to go on achieve their innate goals and aspirations.
The company started focusing on kids during the late 1990s,
with a campaign that identified the brand with
the mind of a “genius.” The next campaign tapped into a key
marketing insight — that mothers wanted
their sons and daughters to be an “all-rounders” rather than
brilliant in studies alone. The tag line —
“Smart kids grow up on a daily diet of Parle-G” — worked for
the brand.
In this context, Parle-G acquired the image of an affordable and
wholesome meal. Parle-G was positioned
on a combination of energy and taste — as a food item that
could be used as a “charger” when low on
energy and a “tasty” accompaniment for a cup of tea or coffee.
Although priced at the low end, the brand
was straddling all SEC classifications. Parle-G was a leveler of
social and economic strata in a vast country
such as India.
A single pack of Parle-G offered 450 calories, which was the

value proposition Parle used effectively when
promoting to the government, the benefits of using Parle-G as a
meal substitute in primary schools. The
federal government had mandated that every child attending
school would receive a mid-day meal
containing 300 calories and 8 to 12 g of protein per day for a
minimum of 200 days a year. Parle-G had
replaced cooked meals. It was positioned as “fortified
nourishment” that nurtured an overall development
of mind and body and enabled both mental and physical agility
among children (see Exhibit 8).
PACKAGING
Small packages were the norm in India for attracting what was
widely known as the bottom of pyramid
(BOP) market. Several multinationals operating in India were
customizing their unit packages to unlock
local demand. Coca-Cola, for example, began selling 200-
milliliter bottles of Coke in India in 2003. Also,
80 per cent of shampoo sales in India, from companies such as
Hindustan Lever, derived from 8-ml and
16-ml sachets, costing INR0.50 and INR1.00 respectively.
Small packages helped attract non-users, one-time users and
new users. They were convenient and
affordable for customers and translated into volumes for large
companies. Single-serve packages were
particularly useful in creating demand for low-penetration
categories such as health food. The smallest
SKU of Parle-G was a 16.5-g package containing four biscuits
and priced at INR1 (US$0.023 cents).
Small packages synergized with the Indian habit of top-up
shopping, as opposed to the North American

habit of buying large quantities in a single visit to the store.13
ADVERTISING AND PROMOTION
Every year since 2004, Parle had spent between INR600 million
and INR700 million on advertising and
sales promotion. The ad spend was approximately two per cent
of annual revenues. Of late, the company
had begun to rely on celebrity endorsements, a promotions
tactic popular with some of Parle-G’s
competitors. Parle was airing commercials in which Aamir
Khan, a popular Indian film actor, became
entangled in humorous situations, which supported the tagline
“G for genius.”
13 Atul Tandon, “Small Is Big”; available at
220.225.146.34/Open/MICA/Faculty/PAT/Small_Big/Small.ppt,
accessed
February 21, 2010.
Page 8 9B10A022
In its advertising, ITC Ltd. was using, among others, Sachin
Tendulkar, an Indian cricketer, to endorse its
Sunfeast Glucose brand. Focusing on the attributes of health
and wellness, which were becoming popular

among Indian consumers, ITC had launched a sub-brand it
called Sunfeast Sachin’s FitKit in March 2007.
Based on the cricketer’s own dietary regimen, FitKit came in
two varieties — Sunfeast Sachin’s Vitamin &
Protein Enriched (VPE) biscuits and Sunfeast Sachin’s
Multigrain (MG) biscuits.
BIL was targeting its Tiger brand of glucose biscuits almost
exclusively at children. Focusing on the
attributes of intelligence and physical fitness, which appealed to
school-aged children, the advertisements
also played on the brand name that symbolized strength.
DISTRIBUTION
India had 15 million retail outlets spread across the country.
Parle-G was sold in 2.5 million outlets. It was
available in every village with a population of 500 people, on a
par with pre-paid mobile cards. The
company had 8,000 wholesalers who had their own sales force.
The company’s sales organization structure
was based on geographies and included zonal sales managers,
divisional sales managers, area managers,
sales executives and sales officers. The logistics were handled
by depots, which also served as clearing and
forwarding agents.
ISSUES IN DECEMBER 2009
Pricing was a larger issue that had spawned two other dilemmas
for Kulkarnii.
First, Parle-G had, no doubt, remained relevant and
contemporary as a brand over the years. However,

consumer perception was rooted so strongly in Parle-G’s low
price that it was undermining other product
attributes such as quality and taste.
Said a marketing manager of a rival firm:
Companies build brand equity in order to deflect the focus of
customers from price.
Customers don’t mind paying a premium when a brand delivers
value on a dimension as
perceived by them. They also don’t mind loosening their wallets
when prices are
increased. They, in fact, expect periodic upward revisions.
Parle-G has formidable equity in the Indian biscuits industry.
But the paradox is that
company cannot increase its price. The brand is caught in a
warp of its own making. Its
equity is built on VFM positioning. VFM is the only value
dimension consumers seem to
be plugged into with Parle-G. It is also the only value
dimension they are plugged into
with the glucose category which Parle-G leads. The situation is
forcing peers, some with
strong equity of their own, to hold the price line. It is
compelling them to cope, like Parle-
G, cope with lower margins.14
Parle needed a big idea to overcome the entrenched VFM
perception, which could make a huge difference
in Parle-G’s handling the current pricing dilemma. The right big
idea could help customers loosen up and
revive Parle-G’s marketing strategy. Kulkarnii wondered:
“What would that big idea be?”

14 Based on a personal interview July 03, 2010.
Page 9 9B10A022
Second, the dependence on a single brand and a single SKU
within it a brand seemed perilous. Parle-G was
contributing 68 per cent of the company’s annual sales revenue,
and the INR4.00 SKU was contributing to
50 per cent of Parle-G’s annual sales revenue. It was a
vulnerable position. The company risked Parle-G
being unseated from its leadership position by an upstart with
deep pockets. The glucose category was
already competitive and likely to become more competitive in
future.
Furthermore, customers were migrating to high-end biscuits
belonging to the sweet, cream and milk
categories. The migration was happening both in the biscuits
industry and within Parle’s own portfolio.
The contribution of Parle-G to the company’s sales revenue was
expected to reduce to 62 per cent in 2010
and settle at approximately 50 per cent in a few years. Forecasts
for 2010, streaming in from the field staff
in a month, would likely point to an upward swing in the
demand for brands other than Parle-G.
Cannibalization of Parle-G seemed imminent without immediate

action. A decline in the sales of Parle-G
would invariably lead to a decline in market share.
Said Kulkarnii:
A flagship brand should be generating a margin of 15 to 20 per
cent of revenue. A margin
of less than 10 per cent is unacceptable for Parle-G. I have to
bite the bullet at some time
on pricing. The concerns are several. Should I make tactical
moves like launching new
SKUs and new price points? Should I continue to tinker with the
grammage? Is there a
strategic move?15
15 Based on a personal interview July 04, 2010.
Page 10 9B10A022
Exhibit 1
PARLE-G –SKU HISTORY, 2006–2009

Maximum
Retail
Price
Stock Keeping
Unit
(in grams)
Duration Maximum
Retail
Price
Stock Keeping
Unit
(in grams)
Duration
INR1
19.0 Jan 08 – Jan 09 INR6 150.0 Jan 06 – Feb 07
16.0 Dec 05 – May 06
INR10
250.0 Jan 06 – Jan 07
17.5 Jun 07 – Dec 07 220.0 Jan 07 – Jan 09
16.5 Dec 08 – Dec 09 231.0 Sep 09 – Dec 09
INR2

50.0 Jun 06 – Dec 06 192.0 Jan 08 – Dec 08
44.0 Jan 07 –Dec 08 178.5 Dec 08 – Dec 09
38.5 Jan 09 – Dec 09 209.0 Dec 08 – Dec 09
INR3
75.0 Jan 06 – Jan 07 210.5 Nov 09 – Dec 09
66.0 Jan 07 – Dec 08 212.0 Aug 09 – Sep 09
77.0 Jan 07 – Jul 07 INR12 300.0 Jan 06 – Mar 07
79.2 Jul 07– Jan 09
INR15
330.0 Jan 07 – Jun 07
66.5 Dec 08 – Dec 09 313.0 May 07 – Jun 08
60.5 Dec 08 – Dec 09
INR20
500.0 Jan 06 – Feb 07
72.6 Dec 08 – Dec 09 440.0 Nov 07 – Jan 09
INR4
100.0 Jan 06 – Feb 07 462.0 May 07 – Apr 08
88.0 Jan 07 – Dec 08 418.0 Dec 08 – Dec 09
99.0 Jan 07 – May 07
INR25
550.0 Apr 08 – Nov 08

93.5 May 07– Apr 08 577.5 Jun 07 – Apr 08
82.5 Dec 08- Dec 09
INR40
1,000.0 Jan 06 – Jan 07
INR5
110.0 Jan 08 – Feb 08 880.0 Jan 08 – Jan 09
99.0 Dec 08 – Dec 09 935.0 May 07 – Jan 08
88.0 Dec 08 – Dec 09 825.0 Dec 08 – Dec 09
Source: Company files.
Page 11 9B10A022
Exhibit 2
INDIAN CONSUMERS – CHANGING PROFILE
Consumer
Category

Annual Income
Range at the
Individual Level
Number of
Households at the
National Level
Aggregate Income
at the National
Level
Aggregate
Consumption at
the National Level
(in thousands of
INR)
(in millions) (in trillions of
INR)
(in trillions of
INR)
2005
Globals
Strivers
Seekers
Aspirers
Deprived
Total

(1,001 – plus)
501–1,000
201–500
91–200
<90
–
1.2
2.4
10.9
91.3
101.3
207.1
2.0
1.6
3.1
11.4
5.4
23.5
1.2
1.0
2.0
8.5
4.1
16.8
2015
Globals
Strivers
Seekers
Aspirers
Deprived

Total
(1,001 – plus)
501–1,000
201–500
91–200
<90
–
3.3
5.5
55.1
106.1
74.0
244.0
6.3
3.8
15.2
14.6
3.8
43.7
4.1
2.7
11.8
12.2
3.3
34.1
2025
Globals
Strivers
Seekers
Aspirers

Deprived
Total
(1,001 – plus)
501–1,000
201–500
91–200
<90
–
9.5
33.1
94.9
93.1
49.9
280.5
21.7
20.9
30.6
13.7
2.6
89.5
14.1
16.5
24.6
11.9
2.4
69.5
Source:
www.mckinsey.com/McKinsey_Global_Institute/research_topics

/Consumer_Demand_and_Demographics. Adapted
from exhibit 3 on page 13 of McKinsey and Company, “The
Bird of Gold: The Rise of India’s Consumer market,” McKinsey
Global Institute, May 2007.
Page 12 9B10A022
Exhibit 3
INDIA’S SOCIO ECONOMIC CLASSIFICATIONS AND
NUMBERS OF HOUSEHOLDS, 2005
SEC
Class
Estimated
Number of
Households
(in millions)
A1
A2
B1
B2
C

D
E1
E2
R1
R2
R3
R4
2.2
4.1
5.3
5.3
12.8
14.2
6.7
10.8
5.8
15.9
56.7
67.3
Total 207.1
Notes: SEC = socio economic classification. SEC indicates the
affluence level of a household to which an individual
belongs. SEC of an urban household is defined by the education
and occupation of the chief wage earner of a household. It
has 8 categories, A1, A2, B1, B2, C, D, E1 and E2, which are
rated in descending order of affluence. SEC of a rural
household is defined by the education and occupation of the
chief wage earner of a household. It has four categories, R1,
R2, R3 and R4, rated in descending order of affluence.
The top band of purchasing power in India, Urban A1A2,
comprised a little more than 6 million households. The next

band,
which would qualify for the “middle-class India” label,
comprising B1R1B2C, harbored approximately 30 million
households.
The ABCR1 target group, which would form the broadest
possible target group for most consumer goods, comprised
approximately 36 million households. The lower middle-class
comprised DE1R2 at approximately 37 million households.
Source: Market Research Society of India.
Page 13 9B10A022
Exhibit 4
INDIAN BISCUIT CATEGORY AND BRAND PENETRATION
Number of Indian Households That Purchased Biscuits, October
2008 to December 2009
(in millions)
SEC
Class

Biscuits (all categories) Glucose Category Parle-G Brand
178.8 % 114.9 % 96.8 %
A1 and A2
B1 and B2
C
D
E1 and E2
R1
R2
R3
R4
7.0
10.7
12.4
13.2
14.7
6.0
17.2
50.0
47.6
3.9
6.0
6.9
7.4
8.2
3.3
9.6
28.0
26.6
3.2
5.6
7.3

8.4
9.9
3.6
11.4
32.7
32.8
2.8
4.9
6.3
7.3
8.6
3.1
9.9
28.4
28.5
2.4
4.6
6.0
7.0
8.5
3.0
9.3
27.7
28.3
2.4
4.7
6.2
7.2
8.7
3.1
9.6
28.6
29.2

Page 14 9B10A022
Exhibit 5
INDIAN DEMOGRAPHY
(Population in millions)
Age group in years 2001 2011* 2021*
0–4
5–9
10–14
110.45
128.31
124.85
115.58
115.43

120.43
110.96
112.69
113.07
15–19
20–24
25–29
30–34
100.21
89.76
83.44
74.27
119.99
116.21
103.84
92.33
114.31
119.10
118.23
114.23
YOUNG POPULATION (15–34) 347.68 432.38 465.88
35–39
40–44
45–49
50–54
55–59
60–64
70.57

55.74
47.40
36.58
27.67
27.52
83.62
74.09
63.51
52.43
41.82
32.58
101.85
90.19
80.96
70.58
59.03
47.02
WORKING POPULATION (15–64) 613.16 780.43 915.51
65–69
70–74
75–79
80 plus
Age not stated
19.81
14.71
6.55
8.03
2.74
24.92
18.74
12.55

8.46
–
35.56
25.71
17.53
15.99
–
TOTAL POPULATION 1,028.61 1,196.55 1,347.02
* Projected population
Note: The government of India conducted the official census
once each decade. The most recent census was held in 2001.
Source: http://mospi.nic.in/Adapted from Youth in India –
Profiles and Programmes, Ministry of Statistics and Programme
Implementation of the Government of India, October 2006,
Table 2(a) “Distribution of population by age and sex, 2001-
2021,” p. 37; available at htpp://www.mospi.gov.in, accessed
July 14, 2010.
Page 15 9B10A022
Exhibit 6

MARKET SHARES OF THE INDIAN GLUCOSE BISCUIT
CATEGORY
Brand 2007 2008 2009
Parle-G 67 69 74
Tiger Glucose 18 16 13
Sunfeast Glucose 10 10 9
Others 5 5 4
Exhibit 7
PARLE’S COMPETITORS IN THE BISCUIT CATEGORY
Existing
Company Biscuit Category Future Plans
Year of
Entry
Brands
Britannia
Industries
Ltd.
1999 Glucose category: Tiger
Tea time category: Marie Gold
Premium categories: Good Day, Bourbon, 50-50,

Treat, Milk Bikis, Timepass, NutriChoice, Little
Hearts
• Outsource production
• Invest INR400 million in
the biscuit segment.
• Launch a variety of
products around the Tiger
brand
Hindustan
Unilever Ltd.
2003 Glucose category: Modern Withdrawn
ITC Ltd. 2002 Glucose category: Sunfeast
Tea time category: Marie Light Other categories:
Milky Magic, Golden Bakery, Dark Fantasy,
Dream Cream, Snacky, Sweet n Salt, Nice,
Benne, Vita Flaxseed, Sunfeast Special
–
Surya Food &
Agro Ltd.
1992 Glucose category: Priya Gold Tea time category:
Marie Lite Premium categories: Big Boss Milk
Classic, Bourbon, Magic Gold, Coconut Crunch
Moving beyond the
institutional markets
Anmol
Biscuits Ltd.

– Glucose category: Anmol Premium categories:
Yummy, Lemon Mazaa, Coconutty, Funfill
Going beyond eastern and
northern Indian markets
Imminent
GlaxoSmithKline Consumer Healthcare: Junior Horlicks
Biscuits
PepsiCo India: Aliva to be produced by foods division Frito Lay
India
United Biscuits (UK)
Kellogg India
Nestle India
Nabisco Foods
Campbell Arnott’s
Page 16 9B10A022
Exhibit 8
PARLE-G – POSITIONING HIGHLIGHTS
Year Goal Target Audience Core Messaging

1982 To seek differentiation through a
name change from Parle-Glucose to
Parle-G
Mass market Parle-G is healthy.
1990 To reinforce health benefits Mothers and children Parle-G
brings out the
essential goodness.
1996 To seize a market opportunity by
targeting consumers in South and
East India who were short on milk
intake
Mothers and children Parle-G makes up for lack
of milk.
1998 To communicate a new attribute Mothers and children
Parle-G provides energy
and personal power.
2003 To communicate a new attribute Mothers and children
Parle-G is more than a
biscuit, it is fortified
nourishment.
2004 To enhance communications with
celebrity endorsements and new
messaging
Mothers and children Parle-G makes kids smart,
turns them into geniuses.

Discussion Questions for Parle-G Case (Due date: 6 September
2019)
This case illustrates a classic pricing decision that many
companies face,
regardless of industry.
In writing your report, I want you to focus on the issues
discussed in the section
titled “ISSUES IN DECEMBER 2009” on pages 8 and 9 of the
case,
culminating with the questions asked by forlorn Mr. Kulkarni at
the end of the
case (on page 9):
“A flagship brand should be generating a margin of 15 to 20
percent of
revenue. A margin of 10 percent is unacceptable for Parle-G. I
have to bite the
bullet at some time on pricing. The concerns are several. Should
I make tactical
moves like launching new SKUs and new price points? Should I
continue to
tinker with the grammage? Is there a strategic move?”
Please write your report so as to give clear guidance to

Kulkarni. It might be a
good idea to first spend some time and effort in understanding
and explaining
the factors that drive Parle-G’s pricing in the report, and then
delve into your
recommendations.
Please be sure to consider and explain both the short- and long-
term impacts of
your recommendations.
Week 06
Conjoint Analysis
https://www.smh.com.au/business/companies/david‐jones‐and‐b
p‐ink‐deal‐to‐bring‐fancy‐food‐to‐petrol‐
stations‐20190827‐p52l2z.html
Customer Value
•
Customer Value is the total amount of money that the customer
is
willing to pay for the benefits received from the product.
•

For pricing, each customer benefit should be equated to dollars
and
cents that customers are willing to pay (WTP) for it.
•
Benefit 1 + Benefit 2 + ….. = WTP 1 + WTP 2 + … = Total WT
P
•
Customer value sets the ceiling or the highest possible price tha
t can
be charged for the product.
•
Understanding customer value requires an understanding of the
types and number of benefits customers receive from the produc
t
and the product/ service features that contribute.
Source: Dholakia, How to price effectively, 2017
Attributes define a product
What are attributes that define a mobile phone?
What is Conjoint Analysis?
Which car
should I get?
Conjoint Analysis: The Underlying Model

• A Product is a “bundle” of attributes
•
Consumers evaluate the alternatives in the marketplace by exam
ining how much
they offer on the various attributes and how critical each attribu
te is to them
•
Total Value of product = sum of sub‐values (partworths) of its a
ttribute levels to
the individual
•
A consumer prefers the product that delivers the greatest Total
Value to him/her
•
Decompose the product into the value of each sub‐part in order t
o determine
preference for the composed product/service
Example: A Consumer’s Value System for a car
v(brand) + v(engine type) + v(body type) + v(price)) = V(
Conjoint analysis model
Consumer’s overall judgment about
a set of complex alternatives
Rank a set of alternatives;
State their preferences
Decompose overall judgment into

separate utilities for individual attributes
Statistical analysis to recover
individual attribute weights, w
Preference = ∑ (w x µ)
= w1 µ1 + w2µ2 + w3 µ3 + …
Given attribute levels for the item (0 or 1)
•
If you choose left, you prefer Power. If you choose right, you pr
efer
Fuel Economy.
• Rather than ask directly whether you prefer Power over Fuel
Economy, we present realistic tradeoff scenarios and infer
preference from your product choices.
Simple example of Conjoint Analysis
Would you prefer…
210 Horsepower or 140 Horsepower
17 MPG 28 MPG
Another simple choice‐based conjoint
More elegant ranking‐based conjoint

Far more complicated examples
Discrete Choice Experiment
1. Identify a set of relevant
product attributes (based
on discussions with a car
company)
2. Define reasonable levels
for these attributes
(based on carsales.com)
Stages in Conjoint Analysis
A real example: Buying a car (ratings task)
Source: Havard Business School
3. Create product profiles
4. Obtain consumer preferences for profiles via survey
Concrete Conjoint Example
Source: Havard Business School
Q: With 4 attributes and 3 levels each, how many possible profil
es available?

• Complete (Full) Factorial Design (CFD)
• All possible combinations of attribute levels (L) of k
attributes.
• CFD design size = L1 x L2 x L3 x … x Lk.
•
E.g., 3 attributes with 2 levels, 4 levels and 5 levels each will re
sult in 40 profiles (= 2
x 4 x 5)
• Fractional Factorial Design (FFD)
•
Minimum design size = 1 + (L1‐1) + (L2‐1) + (L3‐1) + … + (Lk
‐1)
•
E.g., above case requires at least size of 9 (=1 + 1 + 3 + 4) prod
uct profiles.
• Desirable properties
• Balanced –
each level in an attribute appears equal number of times.
• Orthogonality –
each attribute is designed to be independent of one another. It
requires special software such as SPSS, SAS, or R.
Create Conjoint Analysis Design
• A respondent rates
every profile on a rating scale (e.g., 7‐point or 10‐
point)
• A respondent ranks
each profile in terms of preference, e.g., 1st, 2nd,
3rd, … for preference rank.

•
A respondent chooses the most preferred option out of a set of
multiple options, e.g., one out of 4 alternatives. It requires mult
iple
sets of choice tasks.
• A respondent chooses the most preferred option and the least
preferred
option out of a set of small number of options, e.g., 3 or 4
options. It requires multiple sets of choice tasks.
Data Collection
5. Analyze the Data
For ratings data, simple regression
can be used to compute the part‐worths
for the attribute levels. Choice task requires logit or probit.
‐ Dummy coding or Effect Coding is required (see workshop)
Create a “baseline” profile
• E.g., “Japanese,” “Sedan,” “Gasoline,” “$20,000”
• Partworths for these levels set to 0
• Partworths
of other levels = deviations from this baseline profile
• Total Value of baseline profile captured by the intercept
Concrete Conjoint Example
Interpreting the Output

Intercept = Total Value for the Baseline Option
v(Japanese) + v(Sedan) + v(Gasoline) + v($20000) = 4.2 “value
units”) = V(
Coefficients
Intercept 4.20
American 0.33
European ‐0.84
SUV 0.96
Sports Car ‐0.10
Hybrid 1.78
Electric 0.86
$30,000 ‐0.58
$40,000 ‐1.20
Part‐worths
Part‐Worth Plots
-1
0
1

2
3
Japanese American European
Brand Origin
-1.00
0.00
1.00
2.00
3.00
Sedan SUV Sports Car
Body Type
0.00
1.00
2.00
3.00
Gasoline Hybrid Electric
Engine Type
-2.00

-1.00
0.00
1.00
2.00
3.00
$20000 $30000 $40000
Price
What do you make of this?
What is this person’s ideal car?
How Important is Each Attribute?
• For each attribute:
• Range of an attribute = max part‐worth – min part‐worth
•
Importance of an attribute = Range / (sum of ranges across all at
tributes)
ATTRIBUTE IMPORTANCES
Attribute Range Importance
Brand Origin 1.17 0.22
Body Type 1.06 0.20
Engine Type 1.78 0.34
Price 1.20 0.23

0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Brand Origin Body Type Engine Type Price
Sum 4.6 1.0
Choice Prediction
If presented with these three options, which one would this indi
vidual choose?
A Japanese, Sedan, Hybrid, $20,000
B European, Sports Car, Gasoline, $40,000
C American, SUV, Gasoline, $30,000
V(A)= 4.21+ v(Japanese)=0 + v(Sedan)=0 + v(Hybrid)=1.78 +
v(20,000)=0
V(B)= 4.21+ v(European)=‐0.84 + v(Sports Car)=‐0.1 + v(Gas
oline)=0 + v($40,000)=‐1.2
V(C)= 4.21+ v(American)=0.37 + v(SUV)=0.96 + v(Gasoline)
=0 + v($30,000)=‐0.58
-1
0

1
2
3
Japanese American European
Brand Origin
-1.00
0.00
1.00
2.00
3.00
Sedan SUV Sports Car
Body Type
0.00
1.00
2.00
3.00
Gasoline Hybrid Electric
Engine Type
-2.00
-1.00
0.00

1.00
2.00
3.00
$20000 $30000 $40000
Price
So it looks like we can raise the price of option A…by how muc
h?
Coefficients
Intercept 4.20
American 0.33
European ‐0.84
SUV 0.96
Sports Car ‐0.10
Hybrid 1.78
Electric 0.86
$30,000 ‐0.58
$40,000 ‐1.20
•
Convert utilities of each level of attribute to price level that a p
erson is willing to

pay for the desired level of attribute
• From the output, we know that V($20,000) = 0
and V($40,000) = ‐1.20. Thus, $20,000 increase
implies 1.2 utilities decrease ($1 = 1.2/20,000 util).
• SUV has higher utility (0.96) than Sports car (‐0.10).
So, the person is willing to pay more for SUV than
for Sports car of same brand.
• Utility difference between two types = 0.96 – (‐0.10)
= 1.06 $17.667 (= 20,000 x (1.06/1.2)).
Willingness‐To‐Pay
Trade‐Off Analysis
Coefficients
Intercept 4.20
American 0.33
European ‐0.84
SUV 0.96
Sports Car ‐0.10
Hybrid 1.78
Electric 0.86
$30,000 ‐0.58
$40,000 ‐1.20

• Try to select a representative sample of the market of interest
• Below are the average
importance weights across such a sample
From Individual to Market Level Analysis
0
.1
.2
.3
Brand Origin Body Type
Engine Type Price
• Often more insightful to analyze the market by looking at all
individuals to properly account for the heterogeneity in preferen
ces
0
.2
.4
.6
P
ric
e

0 .2 .4 .6 .8
Brand
Brand v. Price
0
.2
.4
.6
P
ric
e
0 .2 .4 .6 .8
Body Type
Body Type v. Price
0
.2
.4
.6
P
ric
e
0 .2 .4 .6
Engine Type
Engine Type v. Price

•
Based on the preferences of each individual in the sample, what
would the market share be of
the following three options be?
A Japanese, Sedan, Hybrid, $20,000
B European, Sports Car, Gasoline, $40,000
C American, SUV, Gasoline, $30,000
47.7%
32.5%
19.8%
A
B
C 2. Identify most preferred option by each individual
1. Compute utilities of each option by each individual
3. Sum of all individuals who would choose each option
Decision Support System Example
Flight configuration

Wine configuration
Wine configuration
• Ideal product development based on preferred attributes
•
Product is a bundle of attributes. So, combining most preferred
attributes will
result in the most preferred product offering.
• Segmentation based on individual part‐worths
• Some emphasize brands, and others emphasize prices, etc.
• Some are price sensitive and some are not.
• Market share forecast leads to Decision Support System
• Willingness‐To‐Pay trade‐off analyses
• Compare utilities of price with utilities of any other attributes.
•
Pursuing higher level of an attribute, e.g., higher horsepower, in
creases price.
WTP for higher horsepower can be computed.
Usage of Conjoint Study
•
Service or experiential goods are hard to evaluate without actual

experience
• Defining attributes and levels are hard
• Preferences are not well formed
•
Some customer segments may find the conjoint ratings task to b
e
very difficult
• Ways of better implementation
• Prototype or Testable products
• Artificial environment mimicking real experience
•
Advanced conjoint such as Adaptive Conjoint (ACA) or Informa
tion
Acceleration (IA)
Difficulty of Conjoint Analysis
• Parle‐G case (Workshops)
• Case report is due at 3pm on Friday, 6 September.
• Submit an electronic copy via Turnitin on UTSOnline
• NO Lecture unless demanded
Next week
8/30/2019 Model User Flow and Wireframes Scoring Guide
https://courserooma.capella.edu/bbcswebdav/institution/IT/IT33

01/180100/Scoring_Guides/u03a1_scoring_guide.html 1/1
Model User Flow and Wireframes Scoring Guide
Due Date: Unit 3
Percentage of Course Grade: 15%.
CRITERIA NON-PERFORMANCE BASIC PROFICIENT
DISTINGUISHED
Revise a task flow to
make a user's
ordering process
more efficient.
20%
Does not revise a
task flow to make
a user's ordering
process more
efficient.
Revises a task flow to
make a user's ordering
process more efficient,
but the revision does
not address all key user
needs and goals during
the process.
Revises a task
flow to make a
user's ordering
process more
efficient.

Revises a task flow to make
a user's ordering process
more efficient, and
demonstrates mastery of
task flow process described
in course readings.
Design a series of
wireframes to
support user tasks.
16%
Does not design a
series of
wireframes to
support user
tasks.
Designs a series of
wireframes to support
user tasks, but these
wireframes are either
incomplete or would not
suit the task at hand.
Designs a series
of wireframes to
support user
tasks.
Designs a series of
wireframes to support user
tasks, and demonstrates
mastery of design practices
described in course
readings.

Specify user flow
between wireframes
according to a task
analysis.
16%
Does not specify
user flow between
wireframes
according to a
task analysis.
Specifies user flow
between wireframes
according to a task
analysis, but this flow
does not match the
process a user is likely
to follow in using the
interface.
Specifies user
flow between
wireframes
according to a
task analysis.
Specifies user flow between
wireframes according to a
task analysis, and
demonstrates mastery of
design practices described in
course readings.
Identify design

strategies to
address human
recognition and
recall, support user
activities, and
facilitate learning.
16%
Does not identify
design strategies
to address human
recognition and
recall, support
user activities, and
facilitate learning.
Identifies design
strategies, but they do
not adequately address
human recognition and
recall, support of user
activities, and/or
facilitating user learning.
Identifies design
strategies to
address human
recognition and
recall, support
user activities,
and facilitate
learning.
Identifies design strategies
to address human
recognition and recall,

support user activities, and
facilitate learning, and
supports these strategies
with evidence from course
readings.
Describe how an
interface should be
modified to suit
mobile devices.
16%
Does not describe
how an interface
should be
modified to suit
mobile devices.
Describes how an
interface should be
modified for mobile
devices, but the
modifications would not
suit needs for mobile
responsiveness.
Describes how
an interface
should be
modified to suit
mobile devices.
Describes how an interface
should be modified to suit
mobile devices, and
supports these modification

choices with evidence from
course readings.
Communicate
according to
assigned
requirements for
format and clarity.
16%
Does not
communicate
according to
assigned
requirements for
format and clarity.
Meets some but not all
requirements for format
and clarity.
Communicates
according to
assigned
requirements for
format and
clarity.
Communicates according to
assigned requirements for
format and clarity, and goes
beyond these requirements
to provide exceptional
structure and conciseness.

PersonasAngela BrogsdaleCapella University.docx

PersonasAngela BrogsdaleCapella University.docx

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