Are your discount levels hurting your sales?

Article from Professional Pricing Journal

Authors: Marlene Jensen & Ronald Drozdenko

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The best way to determine optimal discount levels is to systematically test alternatives in the marketplace, as do direct marketers. Other marketers, under time constraints, often use less systematic methods to determine discounts – such as industry convention, competitive response or historical precedence.

Using unsystematic methods of setting discounts may result in three potentially negative outcomes:

• Even if the discount achieves a managerial objective (e.g., to sell X units, increase sales by X%, etc.) – you can’t know if a smaller discount would achieve a similar sales response but with a higher profitability.
• The deeper discounts used may be associated with a lower perception of quality, which may discourage some consumers from buying, thus lowering your unit sales potential.
• A lowered perception of quality may affect brand loyalty.

Research results are contradictory

A number of studies have looked at consumer responses to discounts, with, unfortunately, contradictory results. For example Mobley, Bearden & Teel (1988) found a positive, increasing response to 25% and 50% discounts. Marshall & Leng (2002) concurred for product sales, but disagreed for services, finding that for services pricing 40-70% discounts were no more positive than 20% discounts, while 30% garnered the most intent to buy.

Other researchers studied consumer perceptions of higher discounts, including Kahneman & Tversky (1979), Sherif & Hovland (1964) and Ong & Jensen (1996). Each found that the higher the discount the more likely it would be “discounted” in determining an internal reference price.

Yet, Urbany, Bearden & Weilbaker (1988) found that even exaggerated, implausible external reference prices were still perceived positively by consumers.

To evaluate why there is such discrepancy, we looked at the individual studies and found a number of reasons:

• Many studies used different products at different overall price points.
• Many looked at only one discount level.
• Some used fictitious brands and others used name brands. This is significant, because Moore & Olshavsky (1989) found discounts positive at all levels for name brands, but negative at the highest levels (75%) for unknown brands.

The new study

We then conducted a new study designed to overcome the above problems by looking at:

• 5 different products (toothpaste, vodka, yogurt, tires, and HDTVs) at a wide range of price points
• Both recognized, high-quality brands and fictitious brands
• 4 different discount levels (none, 15%, 30% and 45%).

The objective of the study was to determine how discounts affect both quality perception and purchase intention. Further, it was to determine whether these results are different for different types of products and for recognized vs. unknown brand names.

For each product at each discount level, we asked consumers to rate on a scale of 1-10, both:

• How high they believed the quality of the product was, and
• How likely they were to buy the product

We studied 634 consumers (52% male) in mid-Connecticut, with ages ranging from the 20s to the 70s.

Mocked-up ads were shown for each product, including a picture, a logo, a description, and a clearly stated price. For the 3 discount levels, that price was crossed out and the new, discounted price was written in. For example:

Crest toothpaste (large 6.2 oz size): $4.70. Now 30% off – just $3.29.

The actual prices for all products within a category (e.g. toothpaste) were the same. Thus the other 3 discount versions of the toothpaste ads included:

$3.29

$3.87. Now 15% off – just $3.29

$5.98. Now 45% off – just $3.29

Each consumer saw only one ad per brand, but 2 ads per category (e.g., for toothpaste, there was both Crest and Advanguard – the fictitious brand).

Danger found for a 45% discount level

For all products together, consumers distrusted the quality of brands with a 45% discount level – and it decreased their reported intent-to-buy. Further, there was a direct correlation between a consumer’s rating of the perceived quality of a product and their rating of their intent to buy – as can be seen by comparing the two lines on the graph below.

Results for new or unknown brands

The known brand in each of the 5 product categories had a much higher quality and intent-to-buy rating than the unknown brand.

Further, consumer’s negative reactions to the unknown brands were even stronger at the two highest discount levels studied. As you can see from the below graph, the quality ratings (and intent-to-purchase) went up for a 15% discount (over no discount), but then dropped for a discount level of 30% and dropped even more for a 45% discount.

Known, quality brands, however, continued to rise in quality perceptions and in intent-to-buy through the 30% level, then dropped for a 45% discount.

 

Results differ for different types of products

Quality perception

All products showed a decrease in quality perception from the 30% to the 45% discount levels – except two.

Absolute (vodka) and Chromateen (HDTV) both had the highest quality rating at the no discount level. Yet the discount levels did not affect intent-to-buy for Absolut, and intent-to-buy was highest at the 45% discount level for Chromateen.

For the unknown tire brand, Zurgin, the lowest discount (15%) was the most effective in increasing purchase intention. This level was statistically more effective than no discount, 30% or 45% discounts. Possibly using deeper discounts for products that have safety implications, such as tires, may signal quality concerns for consumers when the brand is unknown. The quality ratings for Zurgin corresponded to the purchase ratings.

Intent to purchase

Vodka: If you’re selling a recognized vodka brand, you have an interesting scenario. For Absolut vodka, there was no significant effect on purchase probability for any of the discount levels. Consumers appear to look at the out-of-pocket price and decide only on that. Elksat vodka (the fictitious brand) showed a decrease in intent-to-purchase from a 30% to a 45% discount level.

HDTVs : This was a very mixed bag! The highest purchase probability for the Sony HDTV was with no discount. The highest for the fictitious brand (Chromateen) HDTV was at the 45% discount level – the only product where the 45% discount level was the most favorable. Possibly for a relatively expensive ($3000) unknown brand, a large discount is necessary to elicit a greater probability of purchase.

Toothpaste, yogurt & tires: These all showed the same overall purchase probability as the summary results for all products. Thus for recognized brands, the intent-to-buy was highest at the 30% level, then dropping for the 45% level. For the unknown brands, the purchase probability was highest at the 15% discount level, then dropped for the 30% and dropped even more for the 45% levels.

How you can profit from this research

Based upon this study, and previous research, consumer opinions of quality appear to drop even for recognized, high-quality brands, and drop quicker (and at a lower discount levels) for unknown brands. However, these results do differ in some product categories.

You can best profit from this research by:

• Test your discount levels to make sure they are the best for your products
• If you have high discount levels and good quality, use some (or most) of your marketing copy to emphasize the quality of what you offer. For example, your headline might be the discount, but the body copy might be primarily devoted to convincing details on the quality.

Resources:

Ronald Drozdenko is the author of Optimal Database Marketing: Strategy, Development and Data Mining.

Marlene Jensen is the author of 46 Ways to Raise Prices -- Without Losing Sales.

Professional Pricing Journal is a publication of the Professional Pricing Society