1. New Products–1 New Product Models G Pre-Test Market Models G Product Design using Conjoint Analysis G Forecasting with Diffusion Models

2. New Products–2 New Product Decision Models G Product design using conjoint analysis G Forecasting the pattern of new product adoptions (Bass Model) G Forecasting market share for new products in established categories (Assessor model)

3. New Products–3 The New Product Development Process Design Identifying customer needs Sales forecasting Product positioningEngineering Marketing mix assessmentSegmentation Opportunity Identification Market definition Idea generation Testing Advertising & product testing Pretest & prelaunch forecasting Test marketing Introduction Launch planning Tracking the launch Life-Cycle Management Market response analysis & fine tuning the marketing mix; Competitor monitoring & defense Innovation at maturity GoNo GoNo GoNo GoNo Reposition Harvest

4. New Products–4 Value of Concept Testing: TV Series 2,000Ideas 100Scripts 20Pilots 5Scheduled for prime time 1Success (?)

5. New Products–5 New Product Testing from a Customer’s Perspective 1)Concept testing 2)Alpha/Beta/In-house testing 3)Laboratory test market 4)Full-scale test market

6. New Products–6 Questions Answered in Concept Testing G Is the concept worth pursuing further? G Which attributes are more important (provide more value) to the consumers? G Which segments are worth pursuing with this concept? G What amount of cannibalization of current products might occur?

7. New Products–7 Questions Answered in Alpha/Beta Testing G Are the product features/benefits important in use? G What problems are encountered in the use of the product? G What are the costs in use for our consumers? G Does the product perform better than the competing brands?

8. New Products–8 Questions Answered in Laboratory Test Markets G What is the potential number of triers of the product? G What is the potential repeat? G What is the potential frequency of purchase? G What is the projected sales/share for new product in the first two years of introduction? G What should we do to improve the product’s chances of market success?

9. New Products–9 Questions Answered in Test Markets G What is the level of awareness generated by the marketing program? G What trial, repeat, and usage rates are generated by the program? G What changes in attitude are accomplished by the program? G What levels of marketing expenditures are optimal? G What specific levels of advertising, packaging, distribution, etc. will work? G What should we do to improve the product’s chances of market success?

10. New Products–10 Pretest Market Models G Objective Forecast sales/share for new product before a real test market or product launch G Conceptual model Awareness è Availability è Trial è Repeat G Commercial pre-test market services u Yankelovich, Skelly, and White u Bases u Assessor

11. New Products–11 A SSESSOR Model Objectives G Predict new product’s long-term market share, and sales volume over time G Estimate the sources of the new product’s share, which includes “cannibalization” of the firm’s existing products, and the “draw” from competitor brands G Generate diagnostics to improve the product and its marketing program G Evaluate impact of alternative marketing mix elements such as price, package, etc.

12. New Products–12 Overview of A SSESSOR Modeling Procedure Management Input (Positioning Strategy) (Marketing Plan) Reconcile Outputs Draw & Cannibalization Estimates Diagnostics Unit Sales Volume Preference Model Trial & Repeat Model Brand Share Prediction Consumer Research Input (Laboratory Measures) (Post-Usage Measures)

13. New Products–13 Overview of A SSESSOR Measurements DesignProcedureMeasurement O 1 Respondent screening and Criteria for target-group identification recruitment (personal interview) (eg, product-class usage) O 2 Pre-measurement for established Composition of ‘relevant set’ of brands (self-administrated established brands, attribute weights questionnaire) and ratings, and preferences X 1 Exposure to advertising for established brands and new brands [O 3 ]Measurement of reactions to theOptional, e.g. likability and advertising materials (self- believability ratings of advertising administered questionnaire) materials X 2 Simulated shopping trip and exposure to display of new and established brands O 4 Purchase opportunity (choice recordedBrand(s) purchased by research personnel) X 3 Home use/consumption of new brand O 5 Post-usage measurement (telephoneNew-brand usage rate, satisfaction ratings, and repeat-purchase propensity; attribute ratings and preferences for ‘relevant set’ of established brands plus the new brand O = Measurement; X = Advertsing or product exposure

14. New Products–14 Trial/Repeat Model Market share for new product M n = T  R  W where: T=long-run cumulative trial rate (estimated from measurement at O 4 ) R=long-run repeat rate (estimated from measurements at O 5 ) W=relative usage rate, with w = 1 being the average market usage rate.

15. New Products–15 Trial Model T = FKD + CU – (FKD)  (CU) where: F=long-run probability of trial given 100% awareness and 100% distribution (from O 4 ) K=long-run probability of awareness (from managerial judgment) D=long-run probability of product availability where target segment shops (managerial judgment and experience) C=probability of consumer receiving sample (Managerial judgment) U=probability that consumer who receives a product will use it (from managerial judgment and past experience)

16. New Products–16 Repeat Model Obtained as long-run equilibrium of the switching matrix estimated from (O 2 and O 5 ): Time (t+1) New Pr.Other New Pr. p(nn)p(no) Time t Other p(on)p(oo) p(.) are probabilities of switching where p(nn) + p(no) = 1.0; p(on) + p(oo) = 1.0 Long-run repeat given by: p(on) r =–––––––––––––– 1 + p(on) – p(nn)

17. New Products–17 Preference Model: Purchase Probabilities Before New Product Use where: V ij =Preference rating from product j by participant i L ij =Probability that participant i will purchase product j R i =Products that participant i will consider for purchase (Relevant set) b=An index which determines how strongly preference for a product will translate to choice of that product (typical range: 1.5–3.0) (V ij ) b L ij = –––––––– R i  (V ik ) b k=1

18. New Products–18 Preference Model: Purchase Probabilities After New Product Use where: L´ it =Choice probability of product j after participant i has had an opportunity to try the new product b=index obtained earlier Then, market share for new product: L´ in M´ n =E n  ––– I N n=index for new product E n =proportion of participants who include new product in their relevant sets N=number of respondents (V ij ) b L´ ij = ––––––––––––––––– R i (V in ) b +  (V ik ) b k=1

19. New Products–19 Estimating Cannibalization and Draw Partition the group of participants into two: those who include new product in their consideration sets, and those who don’t. The weighted pre- and post- market shares are then given by: L in M j =  ––– I N L´ in L´ in M´ j =E n  –––+ (1 – E n )  ––– I N Then the market share drawn by the new product from each of the existing products is given by: D j =M j –M´ j

20. New Products–20 Example: Preference Ratings V ij (Pre-use)V´ ij (Post-use) Customer B1B2B3B4B1B2B3B4New Product 10.10.04.93.70.10.02.61.70.2 21.50.73.00.01.60.60.60.03.1 32.52.90.00.02.31.40.00.02.3 43.13.40.00.03.33.40.00.00.7 50.01.30.00.00.01.20.00.00.0 64.10.00.00.04.30.00.00.02.1 70.42.10.02.90.42.10.01.60.1 80.60.20.00.00.60.20.00.05.0 94.82.40.00.05.02.20.00.00.3 100.70.04.90.00.70.03.40.00.9

21. New Products–21 Choice Probabilities L ij (Pre-use)L´ ij (Post-use) Customer B1B2B3B4B1B2B3B4New Product 10.000.000.630.370.000.000.690.310.00 20.200.050.750.000.210.030.030.000.73 30.430.570.000.000.420.160.000.000.42 40.460.540.000.000.470.500.000.000.03 50.001.000.000.000.001.000.000.000.00 61.000.000.000.000.800.000.000.000.20 70.010.350.000.640.030.610.000.360.00 80.890.110.000.000.020.000.000.000.98 90.790.210.000.000.820.180.000.000.00 100.020.000.980.000.040.000.890.000.07 Unweighted market share (%) 38.028.323.610.128.124.816.1 6.724.3 New product’s draw from each brand (Unweighted %) 9.9 3.5 7.5 3.4 New product’s draw from each brand (Weighted by E n in %) 2.0 0.7 1.5 0.7

22. New Products–22 Assessor Trial & Repeat Model Market Share Due to Advertising Max trial with unlimited Ad Ad$ for 50% max. trial Actual Ad $ Max awareness with unlimited Ad Ad $ for 50% max. awareness Actual Ad $ % buying brand in simulated shopping Awareness estimate Distribution estimate (Agree) Switchback rate of non-purchasers Repurchase rate of simulation purchasers % making first purchase GIVEN awareness & availability 0.23 Prob. of awareness 0.70 Prob. of availability 0.85 Prob. of switching TO brand 0.16 Prob. of repurchase of brand 0.60 % making first purchase due to advertising 0.137 Retention rate GIVEN trial for ad purchasers 0.286 Response ModeManual Mode Long-term market share from advertising 0.39 Source: Thomas Burnham, University of Texas at Austin

23. New Products–23 Assessor Trial & Repeat Model Market Share Due to Sampling Sampling coverage (%) 0.503 % Delivered 0.90 % of those delivered hitting target 0.80 Simulation sample use Switchback rate of non-purchasers Repurchase rate of simulation non-purchasers Prob. of switching to brand 0.16 Prob. of repurchase of brand 0.427 Long-term market share from sampling 0.02 % hitting target that get used 0.60 Retention rate GIVEN trial for sample receivers 0.218 Correction for sampling/ad overlap (take out those who tried sampling, but would have tried due to ad) 0.035 Market share trying samples 0.251 Source: Thomas Burnham, University of Texas at Austin

24. New Products–24 Assessor Preference Model Summary Source: Thomas Burnham, University of Texas at Austin Pre-use constant sum evaluations Post-use constant sum evaluations Cumulative trial from ad (T&R model) 0.137 Beta (B) for choice model Pre-entry market shares Post-entry market shares (assuming consideration 0.274 Weighted post entry market shares 0.038 Pre-use preference ratings Pre-use choices Post-use preference ratings Proportion of consumers who consider product 0.137 Draw & cannibalization calculations

25. New Products–25 Assessor Market Share to Financial Results Diagrams Market share 0.059 Market size 60M Sales per person $5 JWC factory sales 16.7 Average unit margin 0.541 Ad/sampling expense 4.5/3.5 Net contribution JWC factory sales 16.7 Industry average sales $ for market share 17.7 JWC factory sales Frequency of use differences 0.9 Unit-dollar adjustment 0.94 Price differences 1.04 Return on sales Source: Thomas Burnham, University of Texas at Austin

26. New Products–26 Predicted and Observed Market Shares for A SSESSOR Deviation Deviation Product Description Initial Adjusted Actual (Initial – (Adjusted – Actual) Actual) Deodorant13.311.010.4 2.9 0.6 Antacid 9.610.010.5–0.9–0.5 Shampoo 3.0 3.0 3.2–0.2–0.2 Shampoo 1.8 1.8 1.9–0.1–0.1 Cleaner12.012.012.5–0.5–0.5 Pet Food17.021.022.0–5.0–1.0 Analgesic 3.0 3.0 2.0 1.0 1.0 Cereal 8.0 4.3 4.2 3.8 0.1 Shampoo15.615.615.6 0.0 0.0 Juice Drink 4.9 4.9 5.0–0.1–0.1 Frozen Food 2.0 2.0 2.2–0.2–0.2 Cereal 9.0 7.9 7.2 1.8 0.7 Etc................ Average 7.9 7.5 7.3 0.6 0.2 Average Absolute Deviation —— — 1.5 0.6 Standard Deviation of Differences —— — 2.0 1.0

27. New Products–27 Yankelovich, Skelly and White Model Forecast market share = S  N  C  R  U  K where: S=Lab store sales (indicator of trial), N=Novelty factor of being in lab market. Discount sales by 20–40% based on previous experience that relate trial in lab markets to trial in actual markets, C=Clout factor which retains between 25% and 75% of SN determined, based on proposed marketing effort versus ad and distribution weights of existing brands in relation to their market share, R=Repurchase rate based on percentage of those trying who repurchase, U=Usage rate based on usage frequency of new product as compared to the new product category as a whole, and K=Judgmental factor based on comparison of S  N  C  R  U  K with Yankelovich norms. The comparison is with respect to factors such as size and growth of category, new product’s share derived from category expansion versus conversion from existing brand.

28. New Products–28 Some Issues in Validating Pre-Test Models G Validation does not include products that were withdrawn as a result of model predictions G Pre-test and actual launch are separated in time, often by a year or more G Marketing program as implemented could be different from planned program