Admin at 07:51, 2 October 2008

2008-10-02T07:51:24Z

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==Approach for Segmentation==

[[Image:Segmentation.jpg|500px|center|thumb|Segmentation]]

* Creating the hypotheses by doing the web search, by studying the various websites consisting of relevant information to Coffee. This selection of websites is based on the most popular websites s per ALEXA.com . We had also done random search on Google.

* Identification of the sizable market for the selected hypotheses.

* Size determined will help us to decide the segment or the community that can be targeted.

===Alexa.com Rankings===

* [[Media:Coffee_Drinks.xls|Top Coffee places under Drink category]]
* [[Media:Coffee_beverages.xls|Top Coffee places under Beverages category]]
* [[Media:Coffee_Central America11.xls|Top Coffee places of Central America]]
* [[Media:Coffee_Restaurants.xls|Top Coffee places under Hospitability_ Restaurant category ]]

==Post Approach==
* Once the segment to be targeted is identified, we can also search for the various ways to reach the targeted community using various promotional tools.
* This is can be done by developing the Value Adding (Unique Selling) proposition to the targeted segment.

=='''Hypothesis testing'''==
* We will test some of the above Hypothesis for the following aspects:
# Size of community
# Places where these communities get together for specific events
# Size of potential congregation during such specific events

=='''Identification of communities that follow Operas'''==

# We have defined operas as acts that involve dialogs and music.
# Symphonies, and other solo performances like comedy acts by Robin Williams are considered targeting a different community.

* '''Methodology''':

#Under this category we first found out opera companies. Once identified the companies we had ranked them on the basis of the capacity of audience it can accommodate.
#After ranking them, we had further broken the data on the basis of the events scheduled incoming months.
#The production from these opera companies were further classified based on composers whose acts are being rendered by them.

Better insight can be obtained by viewing the following spreadsheet.

This spread sheet are prepared from the data obtained from the http://www.operabase.com/view.cgi?cc=us from where we were able to extract the information pertaining to various company in opera business. This information was then broke down, and the following excel sheets were prepared.

== Estimating Potential Audience Data ==

Methodolgy:
In estimating potential audience data we had followed the following steps:

'''Step 1''': We had identified the capacity of theater in which the performance is to be done.

'''Step 2''': Next we had identified the number of performance of particular show in a particular theater.

'''Step 3''': We now had multiplied the result obtained from step 2 and step 3.

*Assumption: we have assumed that all the shows are houseful.

The below example will suffice to the understanding of above steps:

[[Image:Calculation of potential Audience.jpg|800px|left|thumb|Calculations]]

== Church Goers Community==

'''Methodology'''

*Mainly focussed on mega churches.

*Under this category we had first of all tried to find out top churches. Once identified them we had ranked them on the basis of attendance.

*After ranking them, we had further broken the data on the basis of the denominations.

*We had also tried to identify whether the church have coffee place within the church premises or not.

The data source used is the 2007 outreach magazine report of 100 largest churches.

Methodology - Revision history

Admin at 07:51, 2 October 2008