Internal secondary data and analytics - VLE 3 Flashcards
What do we mean by primary and secondary data?
Primary data are originated by a researcher for the specific purpose of addressing the problem at hand.
Secondary data are data which have already been collected for purposes other than the problem at hand. These data can be located quickly and inexpensively.
What is a business’s operational data?
Operational data are data which represent the daily activities and transactions of a business.
A wealth of secondary data that can be obtained from inside a company, so-called internal secondary data.
What is CRM and what is needed for it?
Internal secondary data facilitate customer relationship management (CRM).
- Direct marketing.
- Rise of e-business and e-communication.
It is important to have a customer database containing:
- contact details
- geodemographic data
- buying behaviour data.
Why is it good to start research with locating and analysing internal secondary data?
- no additional data collection costs
- no access problems (if managers do not make it difficult for reasons such as politics or personal stuff)
- easier to establish quality data
What information on consumer behaviour can be gathered through operational data?
which products customers buy
which customers buy the most products
which customers repeat purchases
which customers appear only when there are special offers
where these customers are located
how these customers pay – by cash or credit
which customers are the most profitable
seasonal patterns of purchasing behaviour by product types and customer types.
How did scanning devices (e.g. barcode scanners) changed the extent of operational data?
The invention of the barcode scanning device has revolutionised checkout queues. Customers are happy – quicker processing times; companies are happy – a quick form of electronic observation.
Unfortunately, sales data are anonymous – the shopping basket was bought by which type of consumer? For effective decision-making, it is necessary to classify customers (market segmentation).
Why are loyalty cards useful? How do they perform in context of gathering operational data?
Customer loyalty cards link customer characteristics to actual product purchases. Characteristics include demographic and household details obtained during the application stage. Combined with product scanning systems, benefits include the following.
- Profiles of customers can be built up.
- Products used and not used →
cross-selling. - Communications which have worked and not worked (for example, discount coupons).
- Distribution methods can be tailored, such as in-store, online etc.
Additional benefits to market researchers include:
- one big laboratory (can establish causal inferences)
- refining the marketing process (employ statistical modelling)
- developing a clear understanding of ‘gaps’ in a firm’s knowledge of its consumers (attitudinal data)
- linkages between behavioural and attitudinal data.
How does it aid marketing decision makers to gain data which identify characteristics of consumers and their shopping behaviour in a store?
Profiles of customers can be built up
Products used and not used
Communications which have worked and not worked
Distribution methods can be tailored (e.g. shop size can matter for consumer, etc)
How does gaining information on consumer characteristics aid the market researcher?
One big laboratory. Experiments can be conducted. The monitoring of customers, markets and interrelated marketing mix activities allows many causal inferences to be established
Refining the marketing process. With time series of responses to planned marketing activities, statistical models of consumer responses can be built with associated probabilities of a particular outcome. Or consumer lifetime profiles can be built and statistical models too.
Developing a clear understanding of ‘gaps’ in a firm’s knowledge of its consumers. The barcode scanner and loyalty card electronically observe behaviour but do not encapsulate attitudinal data. The nature and levels of satisfaction, what is perceived as good quality service, and what brand image is associated with a particular brand of vodka, are examples of attitudinal data. The use of the database helps to identify target populations to measure and the attitudinal data which needs to be collected. In all, there can be much greater clarity in the nature of primary market research which tackles attitudinal issues.
Linkages between behavioural and attitudinal data.
Behavioral Data refers to what people do—observable actions such as purchase history, website clicks, app usage, or product interactions. It’s data collected from actual behaviors, often objectively measurable.
Attitudinal Data refers to what people think or feel—their opinions, preferences, beliefs, or intentions, typically gathered through surveys, interviews, or focus groups.
What is a geodemographic information system?
A geodemographic information system matches geographic information with demographic information.
As well as being able to discriminate and describe distinctive groups of consumers, the analyses have to produce ‘pictures’ of consumers which are meaningful to marketing decision-makers.
How can market researchers support marketing decision makers by creating consumer profiles?
describe the nature and scope of customer groups
understand the nature of forces which shape the needs of customer groups and the marketer’s ability to satisfy those groups
test individual and interactive controllable marketing variables
monitor and reflect upon past successes and failures in marketing decisions.
What are the stages of building consumer profiles?
Stage 1:
Existing customer database
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Stage 2:
Geodemographic profiles
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Stage 3:
Combine customer data with geodemographic profiles
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Stage 4:
Add survey data
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Stage 5:
Create ‘own’ consumer profiles
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Stage 6:
Use of the datawarehouse
What is a datawarehouse?
A datawarehouse empowers users by providing them with access to a whole array of information in an organisation, making it available for use in other applications.
What are the three components of datawarehouses?
acquisition – existing databases
storage – data from various sources
access – perform individual analyses.
What is data mining?
Data mining is the process of discovering meaningful correlations, patterns and trends by sifting through large amounts of data stored in repositories using pattern recognition, as well as statistical and mathematical techniques.
