Measuring the Impact of the Corporate Brand on Product Brand Evaluation Using CBC-HB

1. Measuring the Impact of the Corporate Brand on Product Brand Evaluation Using CBC-HB Andreas Strebinger Vienna University of Economics and Business Administration (WU Wien), Austria Presentation at the Workshop on Conjoint Applications: Hierarchical Bayes and Finite Mixture Models (Prof. Joel Huber, Prof. Thorsten Teichert) University of Bern, April 30, 2004

2. Contents • Practical relevance • Research objectives & sample • Experimental design of the study • Design of the conjoint task • Data Analysis: Preliminary thoughts • Discussion

3. Two frequently used types of brand consolidation starting point: many isolated product brands consolidation through „Dual Branding“ „Power Branding“ … or … corporate brand

4. Dual Branding: Research questions and sample • What is the influence of the corporate brand on consumer product brand preferences and product brand image in four product categories? • What is the influence of the individual product brands on the corporate brand image, once the affiliation is disclosed? • Is this influence moderated by brand status (premium vs. medium-priced brand), by brand usage, or by buying motives (functional, experiential, relational, symbolic)? Sample: face-to-face interviews with n=1,000 consumers representative of Austrian FMCG buyers between 18 and 65 years (quota sample)

5. Project Partners Cooperating Company(CC) multi-national FMCG producer Thomas Otter Department of Advertising and Marketing Research (Prof. Dr. Günter Schweiger)

6. Product categories and brands in conjoint analysis

7. Experimental design of the study • 4 product categories x • 3 branding strategies (product brands only vs. dual branding vs. dual branding after exposure to a representative sample of all of the company´s brands) x • 2: brand status (premium brand vs. medium-priced brand) x • 2 (order of product categories)

8. product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand product brand Group C: brand portfolio+dual branding Branding Strategy: Experimental Manipulation Group A product brands only Group B dual branding conjoint product category 1 corporate brand conjoint product category 2

9. Conjoint task • 4 brands at 3 price levels • Choice-based conjoint (CBC) • considered to be the most realistic response format • no clear-cut results of previous research, CBC in many cases equal to or better than ratings- or rankings-based conjoint in terms of internal and/or external validity (cf. e.g., Moore/Gray-Lee/Louviere 1998; Vriens/Oppewal/Wedel 1998; Otter 2001; Gensler 2003; Hartmann/Sattler 2004), as long as there are sufficient choice tasks per respondent (cf. Teichert 2000a) • most popular response format in commercial conjoint studies in Europe, especially for brand-price trade-off (Hartmann/Sattler 2002) • pictorial stimuli: pack shot with or without the corporate brand • 15 choice sets for each respondent in each of the two product categories assigned to the respondent according to her/his buying pattern • fixed design (no variation of choice sets between consumers within a product category)

10. Constructing the CBC design • 12 choice tasks designed with SAS choiceff macro (Zwerina/ Huber/Kuhfeld 1996; cf. Chrzan/Orme 2000) • optimization of design efficiency for main effects (brand, price) only • prior parameter estimates computed from data on relative market share and mean purchasing price of the brands analyzed, then flattened (market share confounds brand preference and non-preference factors, e.g. distribution intensity, habit formation) • price as a qualitative attribute (cf. Zwerina/Huber/Kuhfeld 1996, p. 102) • plus 3 choice sets for consumers with extreme price sensitivity or brand preferences out of the following choice sets: • high, high, high, low (buyers with strong aversion against the store brand) • high, low, low, low // low, high, low, low // low, low, high, low (buyers with a strong preference for one of the brands) • equal prices for all four brands (buyers with high price sensitivity)

11. Choice Design(example: household article) prices in Euro

12. Constructing the CBC design (contd.) • „Jittering“ of prices by randomly adding + 30/50/100 Cents, 0 Cents, or -30/-50/-100 Cents (balanced within each brand/price combination) + makes task more realistic (Otter 2001) + supports identification of HB analysis • no „none“ option (cf. Johnson/Orme 1996; Sattler/Hartmann/ Kröger 2003) • Criteria in fixing the order of the 15 choice tasks: • no/low correlations of order and brand prices • 3 choice sets with a „natural“=low price of the partly unknown store brand at the beginning and at the end of the conjoint task (cf. Otter 2001) • rotation of the order (bottom-up vs. top-down)

13. Choice Design(after „jittering“) prices in Euro

14. Choice Design(ordered) prices in Euro

15. Data analysis: Preliminary thoughts • Hierarchical Bayes MNL Model • Why HB? • compares favorably to FM (e.g., Allenby/Ginter 1995; Lenk et al. 1996; Allenby/Aurora/Ginter 1998; Moore/Gray-Lee/Louviere 1998; no general superiority:Teichert 2001; Gensler 2003) • quite robust to violations of underlying assumptions (e.g., Andrews/Ansari/Currim 2002) • „safer“ choice when the true structure and amount of heterogeneity is unknown (e.g., Teichert 2000b, p. 230; Gensler 2003) • continuous heterogeneity distributions in the sense that βi≠ βj for all i ≠ j more likely a priori (Otter/Frühwirth/Tüchler 2004) • simultaneous and direct incorporation of covariates (Allenby and Ginter 1995) Software: R