Designing optimal promotional offers according to consumers’ preferences: a conjoint analysis study Pauline de PECHPEYROU University of Lille II (I.M.D.) IAREP/SABE 2008 at LUISS in Rome

2 Research objective In France, the total number of promotional operations rose by 39% in 2003 and 26% in 2004 (BIPP). Price techniques are among the most often used promotional techniques (73% in 2004 versus 56% in 2000, BIPP), especially on- packaging price coupons. But repeated discounting negatively affects the consumer’s internal reference price and consequently the demand for the brand when it is sold at the normal price. Brand managers could be tempted to prefer “value-added” promotions, such as free-product or premiums. How can managers design “optimal” promotional offers according to the customer target profile ?

3 I. Theoretical Framework Promotions and Reference Price Repeated discounting decreases the reference price of the product (Diamond & Campbell, 1989; Kalwani & Yim, 1992; Slonim & Garbarino, 1999; Desmet, 2003) Previous low prices (compared to the current price) are predicted to cause a low adaptation level, which is itself predicted to cause the current price to be perceived as relatively expensive, thus decreasing transaction utility and demand. Both the price promotion frequency and the size of price discounts have a significant adverse impact on a brand's expected price (Kalwani & Yim, 1992).

4 I. Theoretical Framework A Congruency Framework Some types of promotions affect reference price more than others (Diamond & Campbell, 1989): Same units as the reference price (e.g. price-off promotions)  framed as a reduced loss  integrated with the reference price. Other units than money (e.g. premiums or extra amounts)  framed as gains  more difficult to integrate with the reference price Therefore, brand managers tend to favour extra product offers over immediate discounts. These “value added” promotions should not reduce brand equity. However, French consumers seem to ask for price reductions (TNS Sofres, November 2006)

5 I. Theoretical Framework Semantic Effects Consumers discriminate between economically similar deals (Das, 1992; Smith & Sinha, 2000) E.g. subjects who discriminate prefer the volume promotion (Buy one get one free) to the mixed promotion (Buy two get 50 percent off) by a ratio of five to one, even though the two deals are equivalent both in terms of total cost and unit cost. Discounts should be advertised differently according to the amount of savings (Darke & Freedman, 1993) E.g. sales involving a high percentage of savings but offering little in terms of the absolute amount of money saved might be best advertised in terms of the percentage of savings offered.

6 II. Methodological Approach Conjoint Analysis Step 1 – Attributes and Attribute Levels Step 2 – Preference Model Step 3 – Data Collection Method Step 4 – Stimulus Presentation Step 5 – Measurement Scale for the Dependent Variable

7 II. Methodological Approach Step 1 – Attributes and Attribute Levels Attributes from literature review (Das, 1992; Schindler, 1992; Bernadet, 1993; Darke & Freedman, 1993) Levels in attributes: Reduction amount - three options: 15%, 25% and 50% Type of promotion - two options: bonus pack and discount Semantic formulation - two options: quantity and percentage

8 II. Methodological Approach Step 2 – Preference Model Flexibility of the shape of the preference model (Green & Srinivasan, 1978, p. 106) Vector < ideal point < part-worth function models However, the reliability of the estimated parameters is likely to improve in the reverse order Therefore, we chose the part-worth function model for the preference model.

9 II. Methodological Approach Step 3 – Data Collection Method Four major types of data collection procedures are currently used for conjoint analysis (Green et al., 2001) Full profile techniques, self-explicated preference data collection, hybrid techniques and adaptive conjoint analysis. We chose the full-profile method using rating scales Most common (Wittink & Cattin, 1989) Particularly appropriate when the environmental correlation between factors is large and the number of factors on the stimulus card is small (Green & Srinivasan, 1978)

10 II. Methodological Approach Step 4 – Stimulus Presentation

11 II. Methodological Approach Step 5 – Measurement Scale for the Dependent Variable Dependent variable = overall preference (0-100 scale) Individual- and Category-Related Variables Two product categories (laundry detergent and chocolate cake) Different levels of price and stock-piling. Two individual variables: Consumption level (Ong et al., 1997; Diamond & Sanyal, 1990) Deal proneness (3 items from Froloff, 1992)

12 III. Results Part-Worths Estimation ProductPrice15%25%50%QuantityPercentage Mean St. Dev Min Max Great heterogeneity in the individual part-worths

13 III. Results Cluster-Analysis on Part-Worths Segmentation variable / Cluster Overall (n=127) Cluster 1 (n=88) Cluster 2 (n=39) Extra product Price reduction % % % Quantity Percentage « savings-oriented » segment « semantic-oriented » segment

14 III. Results Discriminant Analysis Discriminant variable / Cluster Overall (n=127) Cluster 1 (n=88) Cluster 2 (n=39) Household size Standardized consumption rate Deal-proneness (item1) Deal-proneness (item2) Deal-proneness (item3) Gender (1=male; 2=female) The “savings-oriented” segment: larger households, higher consumption level, high level of deal-proneness, more female. The “semantic-oriented” segment (promotion as a “signal”): less deal-prone, more male, lower level of consumption.

15 IV. Implications, Limitations and Future Research Directions 1.Free bonus packs as an efficient promotional technique No great difference in their average part-worth. Stronger visual impact at the time of purchase No negative effect on the consumer internal reference price for the brand (Diamond & Campbell, 1989) 2.Amount remains a key variable in the appreciation of the promotional offer: Consumers seem to be used to be offered 25% or even 50% discounts and they are asking for it. 3.Great heterogeneity in consumers’ preferences A “savings-oriented” segment: deal-proneness A “semantic-oriented” segment: promotion as a “signal”

16 IV. Implications, Limitations and Future Research Directions Our research was mostly exploratory We used a convenience sample, homogeneous in terms of age. Need for a replication on a more representative and larger sample. Respondents react to “fictitious” stimuli (CA approach). Situational influences such as time pressure could have an impact on consumer’s choice. Future research direction: include other dependent variables, such as the credibility of the promotional offer (Ong et al., 1997).

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