Psychology Laboratory Report: Quantitative Decision-Making Process
Abstract
Consumer behavioral patterns are a point of interest for marketers who strive to capitalize on them and increase their revenues. This laboratory report investigates what influences consumer quantitative decision process with regards to units of products purchased by each consumer. The experiment investigates consumer choices of units they would purchase for different products on sale and rationalizes the difference in product units. From the survey, it can be concluded that consumers' quantitative decision making is influenced by perceived product value through a process of anchoring and adjustment that justifies stockpiling. It was found that consumer purchase can be increased by creating a seemingly low-cost and product-value deal to justify stockpiling on the consumer's end. Knowledge of the anchoring and adjustment process can be incorporated into marketing strategies to increase individual consumer sales through stockpiling.
Introduction
The average human being spends a considerable amount of time purchasing products which can be either essential in nature or simply a convenience. Entire economic systems are based on infinite human consumption. At the center of modern existence are grocery stores which are the focal point for the purchasing of both essential and non-essential products. With availability made easy, the average human only has to decide on what to get depending on their economic capability. A lot of study in the past revolves around the type of goods humans buy and what influences bias against brands and different types of products. These types of qualitative studies have offered great insight into what drives human purchase power and how this can be manipulated by brands to increase their sales and establish a niche in the competitive market.
However, little advancement has been made on the quantitative front with regards to what influences the number of units of a product a consumer buys. Research shows that purchasing decisions follow a distinct pattern that revolves around the distinction between needs and wants, brand bias, and quantitative decision making (Wansink et al., 1998). This shows that consumers decide on how many units of a product to buy as the final stage of their thought process. For producers and retailers, this offers a unique opportunity to increase their sales if they have a better understanding of this quantitative thought process.
Wansink et al., (1998) notes that marketing campaigns tend to focus on growing the consumer base of the company which causes an increase in sales. However, understanding quantitative decision making could be a way of influencing stockpiling so that the organization not only gains more consumers but also records an increased sale of units with every purchase. The purpose of this experiment is to investigate the factors that influence quantitative decision making and how these factors can be manipulated to increase sales of products through stockpiling. The experiment involves a survey which is a list of products on sale that are marketed differently in terms of units. It is expected that consumers will be drawn to products being marketed in multiples over those marketed as single units. It is also expected that consumers will be drawn to products whose units per purchase have been limited.
Hypothesis
- Shoppers will miss the pricing “error” and purchase more than 1 item in the rip-off condition.
- Anchoring will make consumers to purchase extra items when they are listed as “5 for” all goods
- Anchoring will make consumers to purchase extra items when they are limited to five per customer
Methods
For this experiment, a consumer was subjected to a survey containing a list of 14 popular products found in a grocery store that was on sale and whose prices had been discounted. The list had the prices of the products attached. The consumer was then asked to name the number of units they would buy for each of the products. The results were recorded as below.
Results
The table below contains the list of products that were contained in the survey, their respective prices and the number of units that would have been purchased by the consumer had they been shopping.
|
Product |
Price |
Units Purchased |
|
Coca-Cola 375 ml bottle |
$0.75 |
2 |
|
Mr. Noodles Instant Noodles |
5 for $1 |
10 |
|
Campbell’s Soup |
5 cans for $5 |
10 |
|
McCain’s Pizza Pops Package of 4 |
$2.50 each, Limit of 5 |
5 |
|
Nature Valley Granola Bars box |
2 for $5 or $2.29 each |
4 |
|
Smart Bread |
$1.50 a loaf |
2 |
|
Dorito Corn Chips 326 g bag |
5 for $10 |
5 |
|
Michelina Frozen Pasta Dinners |
$1.50 each |
2 |
|
Craft Dinner Box |
$0.75 , Limit of 5 |
5 |
|
Old South Frozen Juice Concentrate |
$1 a box |
2 |
|
Lays Potato Chips |
2 Large bags for $6 or $2.89 each |
2 |
|
Orville Redenbacher Lt. Butter Microwave Popcorn-3 pack |
$3.50 |
3 |
|
Frozen Chicken Breast 1kg bag |
$0.75 |
2 |
|
Yop Yogurt Drinks per Bottle |
$0.75 |
2 |
From hypothesis 1, it is evident that will have the potential of purchasing extra items in case the mean purchasing amount is valued at 1.53. In this case, it implies that the statistical tested will have to relatively greater than 1. Therefore, t (38) = 4.22. It was found out that 69% of the participants could have managed to purchase more than one item in case it was valued at 1.53. On the other hand, in case the anchoring of the shoppers made them to purchase extra items, it means that the sellers could have valued them at 5.
Figure 1: A bar graph showing the units of merchandize bought against price
Y-axis
10
9
8
Units bought 7
6
5
4
3
2
1
1 2 3 4 5 6 7 8 9 10 X-axis
Price in $
From the statistical test conducted I hypothesis 2, it means that the mean will be 3.72, taking into consideration the number of participants who participated in the survey. That implies that t (38) = 3.32.
Figure 2: A bar graph showing the units of merchandize bought against price
Y-axis
10
9
8
Units bought 7
6
5
4
3
2
1
1 2 3 4 5 6 7 8 9 10 X-axis
Price in $
From hypothesis 3, shoppers will be able to purchase extra items in case the selling price will be valued at 5. From the mean number obtained (2.14), it implies that the purchasing of 2.14 items will be significantly different as compared to the purchase of 1.87 items. Such a difference is anticipated to happen because of the small marketing changes.
Figure 3: A bar graph showing the units of merchandize bought against price
Y-axis
10
9
8
Units bought 7
6
5
4
3
2
1
1 2 3 4 5 6 7 8 9 10 X-axis
Price in $
Discussion
From the results above, it is clear to see that consumers are generally more inclined to purchase products if they are on sale as the consumer in question ticked all the products. This is attributed to competitive pricing during sales which enable the consumer to get more value for their money despite budgetary restrictions. However, it is also important to note that there is a variation with the quantities of the products bought. From the results, products marketed in single units such as the Coca-Cola bottle have the lowest units purchased by the consumer.
In comparison, products marketed in multiples record the highest purchase a seen with the noodle brand. The same trend is observed with products whose purchase units have been limited such as the pizza pops package which the consumer chooses to buy the maximum units allowed. Wansink et al., (1998) attribute the above observation to an Anchoring and Adjustment process which determines quantitative decision making. The process postulates that before a purchase is made, the consumer must decide on the brand and number of units to be purchased which is the anchoring part of the process.
Ordinarily, the consumer will anchor on the lowest number of units. The adjustment process involves the increase of the units to be purchased. This depends on the product value of the deal in question. If consumers perceive that they will be getting more units for a seemingly reduced cost, they are more likely to make an adjustment to their initial anchor value which is in alignment with Kahneman et al., (1982) teachings on rationalization. With regard to limited purchase quantity, this style of marketing has been found to suggest the anchor value to the consumer (Wansink et al., 1998). For instance, if the limit for a product is 4 units per person, the consumer is likely to purchase 4 units of the product because they set 4 as their anchor value. The same observation has been made with even higher limits of up to 12 when consumers were found to purchase the limited 12 units.
In alignment with Kahneman et al., (1982) teaching on heuristics, it can be concluded that consumers make judgments based on the alternative that seems to have a higher value in terms of reduced cost and increased product units. Wansink et al., (1998) report that marketing agendas based on these findings have been found to work as consumers have been found to gravitate towards deals that offer more product value at a seemingly reduced cost even though the discount is often modest and the consumer ends up spending more money than they were planning to. The authors further opined that the trick lies with the justification of the stockpiling for the consumer (Wansink et al., 1998).
The consumer should feel as if they are getting a good deal for them to make an upward adjustment during purchase. For marketing purposes, multiple-unit pricing is a viable strategy that has been found to influence consumer decision-making. The same goes for limiting the purchasing limit for consumers as this serves to suggest the anchor value to the consumer at a point higher than what they would normally settle for. Wansink et al., 1998 reiterate that these values should be high but not unreasonable for them to serve as a justification for stockpiling. The above results offer better insight into what influences consumer quantitative decision making during purchase and how they can be manipulated through specific marketing strategies to benefit producers and retailers.
One limitation of this study is that the purchasing power of each consumer is ultimately influenced by individual income. The reason for that is because the purchase of extra items depends on individual preference and choice. The need of consuming any product is based on the market value of such a product. On the other hand, it implies that the justification of stockpiling cannot be used as the ultimate choice for influencing consumer purchasing power. Consumer quantitative decision making can only be influenced by how each seller markets his or her products. The marketing strategies that are utilized by each seller are the ones that induce a competitive advantage. Each seller has the motive of increasing sales as a result of influencing consumer purchasing power.
References
Kahneman, D., Slovic, S. P., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under uncertainty: Heuristics and biases. Cambridge university press.
Wansink, B., Kent, R. J., & Hoch, S. J. (1998). An anchoring and adjustment model of purchase quantity decisions. Journal of Marketing Research, 35(1), 71-81.
