<?xml version="1.0" encoding="UTF-8"?><!-- generator="WordPress/2.9.2" -->
<rss version="0.92">
<channel>
	<title>Mohit Sewak</title>
	<link>http://mohit.sewak.in</link>
	<description>Gold Medalist (Marketing), Silver Medalist (Finance), Silver Medalist (PGPM)</description>
	<lastBuildDate>Sun, 14 Mar 2010 15:29:55 +0000</lastBuildDate>
	<docs>http://backend.userland.com/rss092</docs>
	<language>en</language>
	
	<item>
		<title>Results (Conjoint Analysis- Indian Insurance Industry)</title>
		<description><![CDATA[.
.
.
Results &#8211; (Conjoint Analysis of the Indian Life Insurance)

.
.
Utility Values of Different Levels in every Factor:
.






. 




 
Factor

 
Level

Utility Estimate


Std. Error




Type


Term


.356


.191




ULIP


-.402


.191




Endowment


.046


.229




Coverage


Only Life


.019


.210




Life + heath


-.266


.260




life + pension


.704


.260




joint (spouse/ kids)


-.456


.260




Distribution


Online Purchase


.110


.191




Through Agent


.378


.191




Through Corpoate Tie-Ups


-.488


.229




Communication


Social Media


.090


.275




TV Ads


.500


.275




Newspaper &#38; Print Ads


-.255


.275




Hoarding &#38; Banners


.385


.275




Online Ads i.e. Google Adwords


-.720


.275




Positioning


Simple and honest plan


.412


.210




Maximizing Returns


-.217


.260




Maximizing coverage options


-.272


.260




Assured/ easier claims


.077


.260






(Constant)


12.825


.163




.
.

Importance of Different Attributes of [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/business-analytics/conjoint-analysis/results-conjoint-insurance/</link>
			</item>
	<item>
		<title>Phase 2 &#8211; Quantitaive Research (Conjoint &#8211; Indian Insurance Industry)</title>
		<description><![CDATA[.
.
.
Phase 2 &#8211; Quantitative Research &#8211; (Conjoint Analysis of the Indian Life Insurance)

.
.
Research 3:
Method:  Conjoint Analysis. 
Type: Fractional Factorial Design/ Full  Profile Conjoint Design.
.

(Green, P. and Srinivasan, V. (1978) Conjoint analysis in consumer research: Issues and outlook, Journal of Consumer Research, vol 5, September 1978, pp 103-123)
.
Research Design:

A total      of [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/business-analytics/conjoint-analysis/phase2-conjoint-insurance/</link>
			</item>
	<item>
		<title>Design of Experiment  (Conjoint Analysis &#8211; Indian Life Insurance Industry)</title>
		<description><![CDATA[.
.
.
Design of Experiment &#8211; (Conjoint Analysis of the Indian Life Insurance)

.
.
Phase 1 &#8211; Qualitative Research
 .
Research 1:
Method:  Secondary Research
Description:
.


We went through various literature on the different policies and plans being offered by various companies, their features, and their market shares.
We also visited their websites, newspaper, and TV ads to identify their integrated communication strategy.

.
.
Snapshot  [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/business-analytics/conjoint-analysis/doe-conjoint-insurance/</link>
			</item>
	<item>
		<title>A Conjoint Analysis of the Indian Life Insurance Industry</title>
		<description><![CDATA[.
.
.
A Conjoint Analysis of the Indian Life Insurance Industry
.
.
.
Why Conjoint Analysis?

.
Conjoint Analysis (Srinivasan, V. &#8211; 1978) is considered far superior to any other research methodology of knowing consumer perception, and scope of new product launch. The main reason behind this is that this is one of those rare techniques that makes the customer makes real [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/business-analytics/conjoint-analysis/conjoint-analysis-insurance/</link>
			</item>
	<item>
		<title>Business Challenges for KPO/ BKO/ BPO in India</title>
		<description><![CDATA[.
.
Business Challenges for KPO/ BKO/ BPO in India
.
.
.
 
High Marketing Costs:
BPO industry consists of large as well as small firms (with less than 300 employees). The major weakness of these smaller BPOs is the high marketing costs. These costs are mostly incurred while searching for new market opportunities.  Further, a need to have onsite offices [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/indian-kpo-business-challenges/</link>
			</item>
	<item>
		<title>Threats for the Indian BKO/ KPO/ BPO Industry</title>
		<description><![CDATA[.
.
Threats for the Indian BKO/ KPO/ BPO Industry
.
.
.
After being market leaders for a long time, Indian outsourcing industry are now facing increased competition from new entrants along with rising demands for services globally. Outsourcing companies in Indian market that dominated the industry for a long time are being threatened by new players from Latin America, [...]]]></description>
		<link>http://mohit.sewak.in/marketing/threats-for-the-indian-bko-kpo-bpo-industry/</link>
			</item>
	<item>
		<title>Future market opportunities for the Indian BKO/ KPO/ BPO Industry</title>
		<description><![CDATA[.
.
Future market opportunities for 
.
The Indian BKO/ KPO/ BPO Industry
 .
.
.
The achievements to date of Indian BPO industry are impressive. However, there is significant headroom to tap the addressable market opportunity from exports and from serving the domestic market. A bottom-up analysis shows a total export BPO market opportunity of US$ 220-280 billion by 2012. [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/indian-kpo-bko-opportunities/</link>
			</item>
	<item>
		<title>Different Types Of Services Being Offered by Indian BPOs / KPOs</title>
		<description><![CDATA[.
.
Different Types Of Services Being Offered by 
.
Indian BPOs / KPOs Currently
 .
.
.
There are many types of Business/ Knowledge Process Outsourcing services being outsourced to India. A complete list of such services under their respective categories is given below:
.
.
1. Technical Support Services 
Technical support offerings include round-the-clock technical support and problem resolution for OEM customers [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/indian-bpo-services-offered/</link>
			</item>
	<item>
		<title>BKO Industry: Industry Analysis and The Indian AdvantageOutsour</title>
		<description><![CDATA[.
.
Industry Analysis of the KPO/ BKO/ BPO Industry,
.
and The Indian Advantage
.
.
.
Growing at more than 35 percent over the past three years, BPO is the fastest growing segment of the overall offshore market, and is currently estimated at US$ 26-29 billion. While labor arbitrage has been a key driver for this growth, other factors such as [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/bko-industry-analysis/</link>
			</item>
	<item>
		<title>Knowledge Process Outsourcing &#8211; Choosing The Right Strategy:</title>
		<description><![CDATA[.
.
Knowledge Process Outsourcing
.
Choosing The Right Strategy:

.
.

.
There are several options for how a company can outsource or offshore research and other business processes. The most common approach is to band off the process to another entity, which performs the work on the requesting company&#8217;s behalf. The location of choice for outsourcing has been India, which has [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/kpo-right-strategy/</link>
			</item>
	<item>
		<title>Key Success Factors in the KPO Industry</title>
		<description><![CDATA[.
.
Key Success Factors In The Outsourcing Industry
 .
.
Before trying to understand what drives BPO (Business Process Outsourcing)/ KPO (Knowledge Process Outsourcing)/ BKO (Business Knowledge Outsourcing) jobs to India, and what are the opportunities and threats in the offering for India, we have to first understand the key factors that lead a business to be outsourced [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/outsourcing/kpo/kpo-industry-success-factors/</link>
			</item>
	<item>
		<title>Biological Neural Networks</title>
		<description><![CDATA[.
.
Neural Networks
.
Our brain consists of approximately 1011 neurons, in a densely connected and functionally related in a peripheral nervous system. These neurons are biological cells which get energized by the reaction of chemical ions, which generates an electrical signal which then propagates the neural network. These neural networks are nothing but a network of all [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/bi/neural-network/biological-neural-networks/</link>
			</item>
	<item>
		<title>Profiting From Data Mining</title>
		<description><![CDATA[
.
.
.

Profiting From Data Mining



.
.
.

Richard Mouser was spending $85 per sale on ad costs for his website. After using Bullock’s Taguchi method of data mining where he tested headers, subheaders, site copy and sent test pages to customers, he was able to reduce his advertising cost to $8 per sale and sales numbers have gone up [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/bi/data-mining/profiting-data-mining/</link>
			</item>
	<item>
		<title>Diamonds in Data Mines: Data Mining Digs In</title>
		<description><![CDATA[
.
.
.

Diamonds in Data Mines
.
Data Mining Digs In


.
.
.
Recently Farmer&#8217;s Insurance group with the help of IBM pulled 2 million policies from its database to run a pilot test using IBM’s Decision Edge software.
They found that apart from young 20 something single guys, married boomers with kids also bought sports cars. They paid same insurance surcharges but [...]]]></description>
		<link>http://mohit.sewak.in/marketing/database-marketing/diamonds-in-data-mines/</link>
			</item>
	<item>
		<title>Perception Mapping of Indian Car Industry</title>
		<description><![CDATA[.
.
The Changing Consumer Perception
.
India is poised to become a major Auto hub in the near future. Indian car industry is changing rapidly, so is the mindset of Indian Consumers. We, at the Great Lakes Institute of Management, took an initiative to find out that whether the changing ground realities have also changed the India Auto Consumer&#8217;s mindset vis-a-vis [...]]]></description>
		<link>http://mohit.sewak.in/marketing/branding/perception-mapping-of-indian-car-industry/</link>
			</item>
	<item>
		<title>The Most Sought After Attribute in a Car</title>
		<description><![CDATA[.
.
Relative Importance of Attribute of a Car
.
.
Various attributes goes behind selecting a car for purchase. Even more of these attributes goes in a consumers mind before evaluating the supremacy of a car over another.
After good literature review, and discussion with experts, we came to the conclusion that the most sought after attributes for a car [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/business-analytics/important-car-attributes/</link>
			</item>
	<item>
		<title>Factors affecting Impulse Buying in a Retail Store</title>
		<description><![CDATA[
.
.
.

Factors affecting Impulse Buying in a Retail Store
 



.
.
.

The article “The Interplay Among Category Characteristics, Customer Characteristics, and Customer Activities on In-Store Decision Making” by J. Jeffrey Inman, Russell S. Winer, &#38; Rosellina Ferraro, gives some intuitive insights about the effect of various factors on the unplanned behavior of the consumer.
.
.

.
.
It proves that where factors [...]]]></description>
		<link>http://mohit.sewak.in/marketing/consumer-behavior/factors-affecting-impulse-buying-in-a-retail-store/</link>
			</item>
	<item>
		<title>TERIM Model of Securitization: How is Securitization Done ?</title>
		<description><![CDATA[.
.
.

TERIM Model of Securitization

.
How is Securitization Done ?
. 
.
In the earlier posts we had discussed what is Securitization, why it is required, and some of the terms related to Securitization like CDO/ ABS/ CLO/ CDS, SPV/ SPE/ SPT etc. Now its time to understand all the steps involved in carrying out any securitization.
.
All the steps [...]]]></description>
		<link>http://mohit.sewak.in/finance/securitization-finance/terim/</link>
			</item>
	<item>
		<title>Identifying Revolutionary MegaTrends</title>
		<description><![CDATA[.
.
.

Identifying Revolutionary MegaTrends
. 
.
Clayton Christensen (of Harvard University), did years of research in various industries to find out that ONE thing, or indication that later turns into a revolution in any industry.
Clayton studied the Disk Drive/ Storage industry (as he believed this industry to be the Fire-Fly industry to study innovation), and closely monitored all [...]]]></description>
		<link>http://mohit.sewak.in/analytics-and-consulting/megatrends-future-technologies/identifying-megatrends/</link>
			</item>
	<item>
		<title>What is a Bankruptcy Remote Entity (BRE) ?</title>
		<description><![CDATA[.
.
.

What is a Bankruptcy Remote Entity (BRE) ?
. 
.
A Bankuptcy Remote Entity (BRE), also called a Special Purpose Vehicle (SPV), is a financial/ legal entity created to isolate the risk of the parent firm from a risky activity/ project that it wants to undertake.

Although the above definition seems very crude, but technically speaking it captures [...]]]></description>
		<link>http://mohit.sewak.in/finance/securitization-finance/what-is-bre/</link>
			</item>
</channel>
</rss>
