Chapter7 2014 Essay

Chapter7 2014 Essay Chapter7 2014 Essay ïÆ'Ëœ Critical area for marketing ïÆ'Ëœ Important for any industry ïÆ'Ëœ Always active! But what is new 1  Repositioning Innovations Line Extensions â€Å"Me Too† Products New to World New to Company 2 Markets Existing Existing New Market Penetration Market Development New Product Development (Diversification) Products New 3 Opportunity Identification Design Testing Introduction Life Cycle Management 4 ïÆ'Ëœ Product Design ïÆ'Ëœ Forecasting 5 ïÆ'Ëœ Product design using conjoint analysis ïÆ'Ëœ Forecasting the pattern of new product adoptions (Bass Diffusion Model) 6 Purpose: To incorporate customer preferences into the new product design process. Process: By evaluating how customers make tradeoffs between various product attributes. Output of CA: - A numerical assessment of the relative importance each customers attaches to attributes of a product set. - The value (utility) provided to each customer by each attribute option. 7 Input is overall preferences. Thus, CA links customers’ stated overall preferences to utility values. For example, Memory $1,000 Price $1,500 8 Mb 16 Mb 24 Mb 4 7 9 2 5 8 $2,000 1 3 6 9 = Most preferred 1 = Least preferred 8 Memory $1,000 Price $1,500 8 Mb 16 Mb 24 Mb 4 7 9 2 5 8 1 3 6 20/3 15/3 10/3 = = = 6.7 5.0 3.3 Part-Worth: $2,000 PartWorth 7/3 = 15/3 = 23/3 = 2.3 5.0 7.7 9 Example: Utility of 24 Mb vs 16 Mb = 7.7 – 5.0 = 2.7 units, while Utility of $1,000 vs $1,500 = 6.7 – 5.0 = 1.7 units Thus, 8 Mb is worth more than $500 to this customer. How does this help a manager? If I have a 64 Mb product selling for $1600/-, how should I price a product if I add 8 Mb to it? 10 Another example: Input for Salsa Thickness Spiciness Color Actual Ranking* Regular Regular Regular Regular Regular Regular Thick Thick Thick Thick Thick Thick Extra-Thick Extra-Thick Extra-Thick Extra-Thick Extra-Thick Extra-Thick Mild Mild Medium-Hot Medium-Hot Extra-Hot Extra-Hot Mild Mild Medium-Hot Medium-Hot Extra-Hot Extra-Hot Mild Mild Medium-Hot Medium-Hot Extra-Hot Extra-Hot Red Green Red Green Red Green Red Green Red Green Red Green Red Green Red Green Red Green 4 3 10 6 15 16 2 1 8 5 13 11 7 9 14 12 17 18 Ranking as Estimated by Model 4 3 10 8 16 15 2 1 6 5 13 11 7 9 14 12 18 17 * 1 = most preferred, 18 = least preferred. 11 Conjoint Analysis: Graphical Output Thickness Spiciness Color 2 1 0 -1 -2 Regular 0.161 Thick 0.913 Ex-Thick Mild -1.074 1.667 Medium-Hot 0.105 Ex-Hot Red -1.774 -0.161 Green 0.161 Range of utility = {(.913, -1.074), (1.667, -1.774), (-.161, .161)} = {1.987, 3.441, .322} Total = 5.75 Ideal Product Second Best 12 0 20 40 60 Spiciness 100 % 59.8% Thickness Color 80 34.6% 5.6% 13 ïÆ'Ëœ Maximum utility rule ïÆ'Ëœ Share of preference rule ïÆ'Ëœ Logit choice rule 14 Designing new products that enhance consumer utility. Forecasting sales/market share of alternative product concepts. Identifying market segments for which a given concept has high value. Identifying the â€Å"best† concept for a target segment. Pricing products/product bundles. Product line management. Positioning new products to different segments. 15 Stage 1- Designing the conjoint study: Step 1.1: Step 1.2: Step 1.3: Select attributes relevant to the product or service category, Select levels for each attribute, and Develop the product bundles to be evaluated. Stage 2- Obtaining data from a sample of respondents: Step 2.1: Step 2.2: Design a data-collection procedure, and Select a computation method for obtaining part-worth functions. Stage 3- Evaluating product design options: Step 3.1: Step 3.2: Step 3.3: Segment customers based on their part-worth functions, Design market simulations, and Select choice rule. 16 Running Conjoint Analysis: Example: Bicycle design Set Up 17 Model designed to answer the question: When will customers adopt a new product or technology? 18 Total Sales at time ‘t’ = From ‘innovators’+ From