SEM 2.04 - A – MARKETING INFORMATION MANAGEMENT PE – Understand data-collection methods to evaluate their appropriateness for the research problem/issue PI – Explain sources of secondary SEM information

Types of Data Primary Data Original data collected by the researcher first hand specifically for the purpose of the study Interviews, sampling, accounting records and newspaper articles are good examples Spectators and participants are major sources of primary data for SEM Concert attendees, gym members, game attendees can answer polls, surveys and attend focus groups

Types of Data Secondary Data Data collected by someone other than the user Information & conclusions gathered after reviewing primary data 2 types of Secondary Data Internal – collected from within the organization External – collected from outside of the organization

Internal Secondary Data Advantages – easily accessed and saves money Disadvantages – doesn’t acknowledge market & might not be up to date Common sources: Budgets Schedules Call reports Order/shipping/billing records Sales reports Customer complaints/requests

External Secondary Data Data that originates outside the organization for which the research is being done Advantages – inexpensive & plentiful Disadvantages – more difficult to obtain accurate information because the data has much greater variety & you have more sources. Outside data may be biased Common Sources: Government agencies: federal for demographic information on a specific geographic location and your target market – census, state, local Chamber of Commerce Trade/industry associations for trends E-marketers for clickstream data about what advertisements are viewed by target market

Info Available from External Secondary Sources Political & economics Consumer trends and habits Social & ethical issues Technological Environmental (Physical) Legal – tax policies and proposed laws Demographic information Consumer protections Competitors – type, strengths & weaknesses

E-Marketers Use external information to help guide their efforts Use digital customer information such as clickstream data Gives webmasters a view of what users are viewing Raises serious security concerns Data sold as a way to increase revenue

Quantitative Data Deals with numbers. Data which can be measured. Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages, etc. Quantitative → Quantity 

Qualitative Data Deals with descriptions. Data can be observed but not measured. Colors, textures, smells, tastes, appearance, beauty, etc. Qualitative → Quality