AEM 2400 Final Review PDF

Title AEM 2400 Final Review
Author Chloe Williams
Course Marketing
Institution Cornell University
Pages 4
File Size 43.6 KB
File Type PDF
Total Downloads 14
Total Views 178

Summary

For Prof. Nathan Yang. Goes over all that was required for fall 2020 marketing final....


Description

In preparation for the final exam, be sure to be able to explain and answer questions surrounding: 1.

Overview N/A 2. Marketing Strategy a. Definition of a market b. The marketing environment, strategy, mix (4 P’s) c. Marketing framework d. A mission statement 3. Marketing Environment a. Segmentation and targeting b. Positioning and differentiation c. Marketing environment i. Demographics, culture, lifestyle, values, etc. d. Millennials vs. baby boomers 4. Marketing Math 1 a. Revenues and Costs b. Break-even analysis c. Customer lifetime value (CLV) d. CLV and marketing decisions i. Customer based corporate valuation ii. Customer relationship management (CRM) 5. Marketing Math 2 a. Understand all of these practice questions and the equations listed 6. Consumer Behaviour 1 a. Buying decision process / consumer decision process b. Need recognition, information search i. High and low involvement c. Post purchase behaviour d. Factors that influence the purchase behaviour i. Culture, social, personal, etc. e. Dichotomy of buying decision behaviour 7. Consumer Behaviour 2 a. Types of buying decision behaviour b. Factors influencing purchase behaviour (as above) c. Consumer psychology in practice i. Perspectives on human economic behaviour d. Heuristics and biases e. Context effects f. Business buying behaviour

i. participants 8. STP (segmentation, targeting, positioning) a. Customer value-driven strategy b. Segments and steps to segmentation c. Positioning i. The value proposition ii. Positioning statement iii. tools 9. Marketing Research 1 a. Marketing research process b. BASES c. Types of research projects d. Data and data collection e. Focus groups i. Pros and cons f. Sampling decisions g. Surveys 10. Marketing Research 2 a. Collecting data via experiments b. Causation c. Experimental design and variables i. Correlation ii. descriptive statistics d. Machine learning i. Big data 11. Product 1 a. Product decisions b. Product types, categories, mixes c. Levels of products d. Basic terminology of products and branding i. Product mix ii. Line extensions and brand extensions 12. Product 2 a. Packaging and labeling b. Product lifecycle i. Consumer segments c. New product development 13. Branding 1 a. What is a brand

i. Identification ii. Differentiation b. Role of brands c. Brand building d. Brand equity 14. Branding 2 a. Brand Valuation b. Brand Loyalty c. Brand positioning d. Brand associations i. Function brand benefits ii. Emotional brand benefits e. Brand protection 15. Pricing 1 a. Pricing b. Pricing strategy c. Communicating price d. Pricing in different types of markets 16. Pricing 2 a. Cost-based pricing b. Profit-based pricing c. Value-based pricing d. Demand-based pricing e. New product pricing f. Product mix pricing g. Captive-product pricing h. Prestige pricing i. Price discrimination 17. Place 1 a. Distribution channels b. Chanel intermediaries c. Push vs pull strategies d. DTC retail e. Distribution intensity f. Vertical integration g. Channel conflicts 18. Place 2 a. Retailing b. E-commerce c. AR/VR/AI d. Customer Experience e. Impact of COVID 19. Promotion a. Promotional Mix

b. Integrated Marketing Communications c. Developing Market Communications 20. E-commerce Recommendation System a. E-commerce different than brick and mortar b. Evaluating e-commerce websites c. Purchase funnel d. Recommendation systems 21. Online Reviews a. The Influence Mix b. Competitive Position c. Communication d. Market research e. Product segmentation f. Measuring the impact of online reviews 22. Search engine optimization a. Inbound and outbound marketing b. Leveraging social media c. Converting website visits into sales d. Website evaluation 23. Visual listening a. Implications of visual information b. How marketers leverage computer vision c. Contextual targeting d. Generating customer segment e. Racial recognition f. Retail analytics g. Companies that leverage CS vision h. Picture features i. Conjoint Analysis j. Clustering Images k. Spotting your brand 24. Mobile marketing a. Changes in consumer behavior b. Forces behind the mobile economy i. Context ii. Location iii. Time iv. Saliency v. Crowdedness vi. Trajectory vii. Social dynamics viii. Weather c. Technological forces...


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