Secondary data research involves analyzing existing data collected by others rather than primary data collected by the researcher. Secondary data has increased with large electronic databases and the internet. It is used for background research, identifying trends, and fact-finding. The advantages are easy availability, low cost, and breadth of data. Disadvantages include lack of specificity, outdatedness, and variation in definitions. Researchers must evaluate if the secondary data applies to their research questions, population, and time period. Objectives of secondary research include fact-finding, database marketing, and model building like forecasting sales. Sources include internal organizational data, government data, trade associations, commercial databases, and panel data tracking consumer behavior over time.

1. Secondary Data Research In A
Digital Age
Presented by :
Khushbu Aggarwal
Anima Arora
Anish Bengeri
Anirban chakraborty
Ankur Chauhan

2. Introduction
Gathered and
Recorded by
someone else
prior to the
current project
Usually
historical and
already
assembled
Require no
access to
respondents or
subjects
Secondary Data
has exploded with
the advent of
large-scale
electronic
information
sources and the
Web

3. Secondary data is used to find general trends and to
write research papers by students as much of the
background work needed has already been carried
out by using the following sources:
Literature Reviews
Case Studies,
Published texts and statistics
Media promotion
Personal contacts

4. Advantages
Easy
Availability
Fast
Less
Expensive
Expertise
required
for primary
Breadth of
data
available
allows
researcher
s to look
at trends
and
changes
of
phenomen
a over
time.
Eliminates
activities
associated
with
primary
data
collection
Use of
Electronic
Retrieval
to access
Data
Stored
Digitally
Essential
where
primary
research
is not
possible

5. Disadvantages
1. Lack Of
Specificity
2. Not designed
specifically for the
required research
3. No control over
inaccuracy,
biases that
support the
publisher’s
interest
4. Data
conversion may
be required
5. Can be
Inadequate For
the Research’s
Need:
1. outdated
information
2. variation in
definition of terms
3. different units of
measurement
4. lack of
information to verify
the data’s accuracy
6. Population in
research may not
be comparable to
population of
interest
7. Units of
measurement
may not conform
to the research

6. How to evaluate Secondary Data
1. Is the subject matter consistent with our problem
definition?
2. Do the data apply to the population of interest?
3. Do the data apply to the time period of interest?
4. Do the secondary data appear in the correct units
of measurement?
5. Do the data cover the subject of interest in
adequate detail?

8. Objectives of Secondary Research
DATABASE
MARKETI
NG
FACT
FINDING MODEL
BUILDING

9. Continued..
• Identifying consumer patterns
• Analyzing trends
• Environment scanning
FACT-
FINDING
• Using CRM databases to develop
one-to-one relationships
• Sources : Transaction records,
data provided directly by
customers, secondary data
purchased from third parties
DATABASE
MARKETING

10. Model Building
 Secondary data specifying relationships between 2
or more variables
 Leads to equations:
 Descriptive
 Predictive
 Ex: Market share = Company Sales/Industry
Sales
 3 objectives to satisfy:
 Estimating Market Potential
 Forecasting Sales
 Selecting Potential Facility/Expansion Facility

11. Estimating Market Potential
 Exact figures :
 Trade associations
 Secondary data for a country or large geographic location
available
 For unique/specific geographic data:
 Projections for the geographic area
 Example: Brewing company estimating potential
 Market Potential = Population * Consumption
Country Population
projection(000’s)
Per capita Beer
consumption(litr
es)
Market Potential
Estimate
Germany 80,000 116 80000*116
Japan 1,50,000 80 150000*80
Spain 45,000 130 45000*130

12. Forecasting Sales
• For Products in Stable markets secondary Research data important
• Identifies trends and extrapolates past performance to future
• Model: Sales= past sales volume * Expected growth rate
• Example
• Trend projection using Moving Average projection
• Model : Avg Ticket price +(Avg Ticket Price*3-year moving Avg)
• Best suited for Static competitive environment
• Statistical trend analysis
Year Avg Ticket
Price
% Growth
Rate
3-year
moving avg
2006 22.21 4.9 5
2007 22.70 2.2 4.6
2008 25.43 12 6.4
2009 27.05 - -

13. Analysis of Trade Areas and Sites
 Site analysis : Using Secondary-data to make best
location decision for retail operations
 Index of Retail Saturation: Investigate retail site and
describe relationship between demand and supply
 Index= local market potential/Local Market retailing space
 Data Mining
 Used for mining large amount of data to discover patterns
about customers and products
 When data mining is useful?
 When relevant data is independent and in unrelated
files
 No of distinct pieces of information is large

14.  Market Basket Analysis:
 Analyzes random POS transaction database
 Identifies coinciding purchases
 Relationships between products purchased and other retail
information
 Example: Men who walk in to buy Diapers between 6pm – 8pm walk
out with 6-pack beer
 Behavioral pattern helps in store layout
 Customer Discovery:
 Mining data to look for patterns of valuable customers
 Mine data on :
 Sales
 Response to marketing
 Customer service
 Database marketing using CRM
 Using CRM databases to develop 1-to-1 relationship and precisely
targeting customers

15. Sources of Secondary Research

16. Internal data
Secondary data that originate inside the
organization
 Data properly coded into a modular database can be
used for detailed analysis
 Sales Information broken down by
product/geography can be used to forecast sales
 Intranet tools like ‘Enterprise Search’ and Autonomy
helps people search the corporate intranet
 Customer Complaints

17. Traditional Distribution
 Indirect channel using intermediary
Information Producer
(Federal Government)
Library
(Storage of
government
documents
and books)
Company User

18. Traditional Distribution
 Direct Channel
Information Producer
(Federal Government)
Company User

19. Modern Distribution of secondary data
Information producer A
(Federal government-
census data)
Information producer B
(Grocery store-retail
scanner data)
Information producer C
(Audience research company-
television viewing data)
Vendor/external
distributor
(Computerized database
integrating all three data
sources for any
geographic area)
Company User

20. External Data
Created, recorded, or generated by an entity other than
the researcher’s organization
 Governments-RBI,DGFT
 Trade Associations-Collect data of interest to firms,
especially data on market sizes and trends
 Newzpapers and Journals
 Library
 Internet
 Vendors-intermediaries like Dun and Bradstreet,Hoovers
which allow managers to access thousands of external
databases via computers and telecommunications

21. Commercial Sources
Firms that specialize in selling and/or publishing
information
 Market share data companies like A.C. Nielsen
provide information about sales volume and brand
share over time using a service called ScanTrack
 INFOSCAN is a syndicated store tracking service
that collects scanner data weekly from
supermarkets, drug outlets etc.

22. Single Source Data Integrated
Information
• Diverse type of data by single company
• Integrated based on geographic area
• Sometimes on the basis of geodemographic
~CACI Marketing Systems, PRIZM by Claritas Corporation,
MRI Cable Report

23. Panel Data
 Multi dimension information
 For Multiple time
 Sampling unit can be individual, company
Panel Data
Balance
Unbalanced

24. Scanner Panel Date
 To gather individual consumer buying pattern
 Information like brand, quantity, occasion
 Used in product development, advertising, promotion,
assortment, pack size
 Used by Retail outlets like Reliance, Wal Mart,
Foodworld, Big Bazaar

25. Conclusion
Secondary data is economical and
time efficient. However secondary
data should be closely examined to
be sure that the information is
reliable, timely, and meets specific
needs.
“Always look for secondary data
first”