Background

This research’s primary objective is to help brands build prominence, by identifying why certain brands stand out from competitors in visually cluttered environments. The need to stand out for brands is an ongoing challenge, as just being on shelf (digital or physical) is not enough, a brand needs to be easy to find as part of building Physical Availability. 

This prominence challenge is more pronounced in online and mobile spaces, we have more environments, with different types of competitive clutter.  This leads to the question as to whether we need to adapt the visual design of a brand for each environment, or if there are some common factors that help a brand stand out in any environment.

Broadly speaking, consumers process visual information in two ways:

Top-down processing — where a buyer uses the information in their memory, such as the brand name, distinctive assets, anything that gives a sense of familiarity, to direct their attention to achieve a goal.  While this information must be learned before exposure to the cluttered environment, brand managers can influence the memories consumers hold about the brand via their Distinctive Asset building activities.

Bottom-up processing — where the buyer’s attention is drawn to a visual characteristic, such as a colour, image or word. In this instance, brand managers do not need to ‘teach’ buyers these characteristics. However, there is limited scope to influence the environment where bottom-up processing takes place. For example a bright pink colour might stand out when the environment has lots of muted colours, but not if the environment has other bright colours. 

These two types of processing can occur at the same time, whereby something that stands out in contrast to the environment is also familiar to the buyer. Indeed Distinctive Assets are at their best when they draw on both Top-down and Bottom-up processing. In this scenario, the buyer can draw on past links with the brand in memory and the Distinctive Asset is sufficiently prominent in the environment that it is seamlessly easy to find what is sought. 

In this research we explore the prevalence of top-down processing, and the conditions where this is higher or lower, to assess how much memory-building the brand needs to do before the buyer gets to a buying situation. 

We also explore the relative performance of different visual elements to stimulate a brand being noticed, drawing on contexts where there is little or no familiarity for buyers to draw upon. This information helps to identify potential Distinctive Assets to help the brand build prominence and be easily found in choice contexts.

Method

Our method draws on three different studies, conducted with USA and UK consumers, spanning 15 categories. Of these 15 categories, 11 are packaged goods (Eggs, Paper Towels, Dog Food, Crisps, Condiments, Canned Fruit, Coffee, Spreads, Water, Biscuit, and Chocolate) tested in both in-store and online grocery environments. Four are services (TV streaming, Fast food, Food delivery, Banking x2) tested in a mobile phone screen app environment.

Study 1: This sample comprises n=974 respondents across the USA and UK, aged over 18 years.  Respondents were shown a screenshot of an online grocery store after a search for the category from the Australian market. Australia was chosen as a slightly different country to the UK and USA. Australia’s supermarkets are not familiar enough for people to activate prior memories, but still use English and avoid distracting text in another language. Each respondent answered for only one category in each type of store (in-store or online) to reduce learning effects. This study covered eight packaged goods categories.

Study 2: This sample comprises n=910 respondents in the USA, aged over 18 years. In this case, the in-store and online grocery shelfs were mock ups, to avoid familiarity based on supermarket shopping behaviour also affecting results, but the brands were ones that were available to buy. This study covered three packaged goods categories, all containing familiar brands. 

Study 3: This sample comprises n=1,003 respondents in the USA aged over 18 years. Respondents were shown a mock up mobile phone screen with apps from a category plus fillers (e.g., calculator app or compass app) to resemble a normal phone. This study covered five categories, one with unfamiliar brands and four with familiar brands.

Examples of each study’s stimuli layout are shown in Appendix A.

In each study, respondents were recruited from a professional online panel, and compensated in line with the panel’s procedures. Relevant category and brand buying/usage information was also collected.

The research protocol was as follows. After presentation of the stimuli (in-store image, online image or mobile screen image), respondents were asked the following questions:

• Q1: What stands out to you? Whereby they clicked on that item that stood out so it could be recorded
• Q2: Why did that stand out? Whereby they were given an open ended text box to type in their reason(s). 

These reasons were then coded into a framework (see Table 1). Multiple codes were used when necessary.

Table 1: Visual element codes and descriptions

Results

The coded reasons for brand selection were tabulated for each category. To facilitate comparison across categories, results were normalised to be on a scale from 0 to 100%. 

Finding 1:

Colour is the most common visual component to build brand prominence.

The results show:

• Colour is the most common reason a brand is prominent when brands are unfamiliar, and the first or second reason when brands are familiar. It is more commonly drawn upon in unfamiliar contexts than in known contexts, which suggests it is particularly useful for those who are new to a category.
• Letters/words/font is the second most common category when brands are unfamiliar, and ranked on a par with general aesthetics when brands are familiar. Words are generally more impactful than images, probably because these environments are very image rich.
• In contexts with familiar brands, General Aesthetics also ranked highly. This is a broad category made up of comments such as I just liked the overall look of it, or It looked different to others. As this category is made up of a wide range of characteristics, it is very difficult to action. It is also much less popular when brands are unfamiliar.
• Structural Design, Placement or Faces are rarely mentioned overall, but did have traction in specific categories (see Finding 5). 

As colour was also the most common response in our earlier in-store research tests (e.g., Galliard et al, 2006), this finding is not just an artefact of the experimental research settings. 

Table 2: Average % shoppers stating response across categories

Finding 2:  

Familiarity accounts for most brand buyer responses, highlighting the value of Distinctive Assets that create familiarity with the brand’s visual identity.

As Figure 1 shows, on average across all buyers, familiarity accounts for about 40% of responses. This figure increases to nearly two-thirds for existing brand buyers. This highlights how much buyers rely on their existing memories and the value in building these memories. It also explains why it is hard to break through to non-buyers, who are buyers or other brands, and so are drawn to these other brands first. 

Around one in three non-buyers also draw on familiarity to identify brands that stand out, so it is possible to build Distinctive Assets amongst this group. Even without prior buying, the Distinctive Asset can help them find a mentally available brand.

Figure 1: % stating familiarity/usage as the reason the brand stands out, by user group

Finding 3:  

Non-buyers use colour more than any other visual element to identify brands that stand out, then word/letters.

Across all categories tested, colour is the most common visual element for brands that stood out. Similar to previous research (e.g., Gaillard et al. 2006) it was colour in general that stood out, not any specific colour. Evidence for colour’s strength is that Table 3 reveals how the lowest score for colours is higher than most other element’s highest score.

After colour, the next most common element is Text. This is because the words have meaning, and so are easily processed by our brains. If there is strong visual imagery such as in a sea of packages, words can have sufficient visual difference to cut through. 

Table 3: Non-buyer use of visual elements to find brands in cluttered environments

Finding 4:

Colour matters for brands both online and in-store

Across 11 comparisons between online grocery store and in-store settings as shown in Figure 2, colour consistently emerges as the dominant factor for standing out in both environments. When colour is more impactful in-store, at least one brand has taken advantage of the multiple facings and formed a colour block. This use of colour is harder to achieve online where white space separates single product thumbnails. 

An interesting exception was canned fruit, where colour scores low in-store. This is because the most prominent can contains images of sliced pineapple, and this product image attracts attention rather than the blue colour which takes up most of the label. The blue colour serves as a nice background to make the yellow pineapple slice more prominent (see Table 4 for an example). 

Figure 2: % stating Colour as why brands stand out in-store versus online grocery settings 

Finding 5:

Other elements can become important if built as Distinctive Assets

For each visual element, there are categories where its impact is higher, because of the use of that element by a specific brand or brands within that category (see Table 4).

Table 4: Specific examples of packs or apps that over-performed on a visual element

Key implications 

• Visual design should factor in both the environment and memory to cut through clutter

Strong design works on two levels: it grabs attention (bottom-up processing) and taps into familiar memories (top-down processing). Brands should choose elements (colour, words etc.), as potential Distinctive Assets based on their ability to initially stimulate bottom up processing, as this makes it easier to build and gives the Distinctive Asset a head start. But by building links between the Distinctive Asset and the brand name, the element becomes familiar in memory, making it is easy to draw on when finding brands in cluttered environment.

Remember: While brand managers can control the Distinctive Assets built, they often cannot control the environment in which the brand is presented. Therefore, it is risky to rely only on bottom up processing for consumers to find a brand.

• Familiarity helps findability amongst non-buyers too – but has to be built first via Distinctive Assets

Familiarity helps build brand prominence. Similar to the ‘cocktail party’ effect, whereby we can easily find our friend in a sea of faces, when we have memories around the visual identity of the brand, these memories help us more easily find the brand in cluttered environments. The fact that buyers named familiarity as the reason for the brand standing out, instead of a specific colour or image, suggests that top-down processing is the easiest cognitive path to take.  

Around one in three non-buyers also name familiarity as the reason a brand stood out, which shows that Distinctive Assets can be built outside of the choice context, such that the brand becomes something familiar when in the choice context. This gives the brand a Physical Availability advantage amongst potential new buyers, which is ready to be leveraged when the brand gains Mental Availability.

• Know your ‘prominent’ Distinctive Assets to avoid unintentionally changing them

Packs change, apps change, for a variety of reasons, whether it be modernisation, highlighting seasonal trends or to celebrate partnerships, collaborations or events. When these changes occur, it is important to make sure they do not affect something that was important for category buyers’ visual recognition. Otherwise, the change might cancel prior efforts towards building strong visual Distinctive Assets.

This is particularly important for the brand’s existing buyers, who rely heavily on memory to find what they know. Disrupting this consistency, like changing a pack’s design or app icon colour, can make it easy for buyers to (unintentionally) miss your brand in visually cluttered settings.

• Colour is Your Most Valuable Attention-Getter

Across all settings, colour consistently emerged as the most common visual element that buyers use to find brands in the absence of familiarity. Despite this, we find colour is often one of the weakest Distinctive Assets, due to poor management and assumptions about the need for colours to signal variants.  

Therefore in light of the poor performance of colour as a Distinctive Asset, we recommend marketers review the use of colour-based assets and check they are not neglecting opportunities to harness the value of colour-based assets due to faulty use or assumptions. This is particularly relevant for categories where colours have been co-opted into other meanings such as flavour or scent. For example rather than trying to own a single colour, there might be more opportunities to own a colour combination or develop a colour+design asset to help the brand build a strong colour-based asset.

But if you don’t have colour, other visual elements can be strong too…

If a brand cannot or doesn’t want to use colour, other elements can be used instead. However this only works if these elements are made the true visual hero. We will have more research coming up on how to get the most out of each potential type of Distinctive Asset, but in the interim, please ask for our Distinctive Asset Deployment seminar for asset building tips.

Key References 

1. Gaillard, Elise, Anne Sharp, and Jenni Romaniuk (2006), “Measuring brand distinctive elements in an in-store packaged goods consumer context,” in European Marketing Academy Conference (EMAC). Athens, Greece.
2. Romaniuk, Jenni (2018), Building Distinctive Brand Assets. South Melbourne, Victoria: Oxford University Press.
3. Ward, Ella, Jenni Romaniuk, Virginia Beal, and Song Yang (2021), “Are some Distinctive Assets easier to own near exclusively?,” Ehrenberg-Bass Institute for Marketing Science.

Appendix: Examples of each environment

Study 1:

Study 2:

Study 3: