SEM1 – MARKETING INFORMATION MANAGEMENT 2.04 Identify data collection methods and explain sources of Sports Marketing Information Understand data-collection methods to evaluate their appropriateness for the research problem/issue

Types of Data Primary Data Original data collected by the researcher first hand specifically for the purpose of the study Examples: Interviews, sampling, accounting records and newspaper articles Spectators and participants are major sources of primary data for SEM Concert attendees, gym members, game attendees polls, surveys and 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 –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 Advantages – inexpensive & plentiful Disadvantages –difficult to obtain accurate information because the data has much greater variety because there are more sources Outside data may be biased

External Secondary Data Common Sources: Government agencies: Census Bureau demographic information on a specific geographic location Trade/industry associations for industry trends Clickstream data Data collected from consumer views of wesites or online advertisements Used by E-Marketers

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 Quantitative → Quantity 

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