Completeness Effect
We place a greater value on products seen as whole in shape
We often estimate how much we should consume of a product based on aspects of its physical shape. If a product looks incomplete, we’re likely to incorrectly see it as having less value and so consume more of it. (e.g. Wansink, 2006).
Sevilla & Kahn (2014) The Completeness Heuristic: Product Shape Completeness Influences Size Perceptions, Preference, and Consumption. Journal of Marketing Research.
Could I take your attention for just a moment?
Great.
Now, picture in your mind two sandwiches. These sandwiches are pretty much identical to one another, but the only difference between them is that while one sandwich is left whole, the other one is sliced diagonally in half. Remember that besides the fact that it’s been sliced, the second sandwich is of the same size, quality and quantity as the first. Now, if you were asked to choose one of the two sandwiches, would you have a strong preference for either one?
Unless for some reason you strongly preferred sliced sandwiches, you’d rationally not mind choosing between the two. But in a study, people were placed in an identical scenario as you, and asked the same question. Fascinatingly, researchers found that people were significantly more likely to choose the “complete” (unsliced) version of the sandwich (Sevilla & Kahn, 2014).
But why? Well, when questioned further about their preference, it was found that they felt that the unsliced sandwich ‘had more quantity’ than the sliced one. More generally, research has shown that we humans desire completeness (Hull, 1932; Nunes and Dreze, 2006), and especially aesthetic designs that suggest unity (Veryzer and Hutchinson, 1998). We also feel that incomplete experiences feel ‘unresolved’ (Bieke et al, 2007).
This has led the researchers to conclude that “incompletely” shaped products are assumed to be of lesser quantity than completely shaped ones. We’re also much more likely to purchase complete products over those seen as incomplete. Perceiving that incomplete items are smaller can also influence people to consume more of them. In another study, healthcare professionals were served sandwiches during a lunchtime buffet. Some were given incomplete, sliced sandwiches and others were offered whole ones. Those served sliced sandwiches were more likely to eat more than those served whole sandwiches!
Key Takeaways for Decision-Makers
- If you’re trying to reduce consumption of a given product, such as unhealthy food, make sure the items are complete in shape. This will influence people to believe they’re consuming more, making them believe they are satiated, faster.
- On the other hand, if you’re trying to increase consumption of a product, incomplete sizes will often leave customers coming back for more. For example, in one of their follow-up studies, the authors found that people who were given chocolate pieces that were incomplete in shape (irregular) consumed significantly more chocolate than participants given complete shaped (whole) chocolates.
- This bias will be of particular interest to dieters who think that eating half of a piece of food is a better choice than eating the whole. It suggests that the “eat only half rule” can backfire and serve as a dangerous incentive to let one’s guard down and go on a mindless binge (Sevilla & Kahn, 2014).
- Completeness can also be influenced by expectations about the typical shape of an item within the given product category. For example, for a bagel, a hole in the middle is considered complete.
- Despite being the focus for this Brain Gem, researchers suggest that these findings go far beyond food; they found the same results for shampoo, for instance.
- Aim for completeness in your product design. Customers prefer this, and will buy more of it next to a product that looks incomplete. An example of an incomplete product would be a shampoo bottle with a hole in the middle for easy holding. Be aware of the implications of such a design.
- Check out the Zeigarnik Effect Brain Gem to understand why incompleteness also applies to tasks we undertake.
What’s a Rich Text element?
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
Static and dynamic content editing
- Aspirational membership schemes and belonging The category size bias provides a credible explanation for why we human beings tend to associate with large groups that are viewed favourably by society. Being part of a large and “desirable” social group can make others believe that we also possess the many qualities of its members. For small businesses, it suggests that forming or being a part of a consortium or large and high quality networking group can dramatically elevate your brand image.
- Communicating category sizes to nudge effectively Highlighting the differences between the large and small categories is highly likely to enhance the effect of the Category Size Bias. For instance, for software companies, stating that there are 10 features in the premium version versus 4 in the free version will help nudge a decision towards the premium version
How to customize formatting for each rich text
- The findings from this braingem can nudge better healthcare choices, encourage consumption of a given product, and lead to more confident consumer decisions.
- We mistakenly believe that items in larger categories have a higher probability of being picked than ones in smaller categories, despite all items having an equal chance of being picked.
- We’ll spend or gamble more money on items put in larger categories.
- We’re more likely to take action from tasks when they’re in a bigger list, over a smaller list.
- We once we put something into a group, we perceive it to adopt all the characteristics of that group. This suggests that small companies should foster alliances with similarly-principled, more established companies.
Navigate behavioural research with ease.
Nuggets are highly-distilled research papers to help you make better data-driven decisions
Get the tool
