The study and understanding of the buying patterns of consumers and the factors that influence their buying.
The Institute’s point of view on adding sound to video is that it usually helps, but is not a substitute for visual branding.
An academic journal article found that category-prompted brand recall was higher (55% vs 45%) for ads that used both audio and visual branding, as opposed to just visual branding (Simmonds et al., 2020). Furthermore, this additional recall was explained by attention to the audio messaging, measured by heart rate, as clearly eye-tracking can’t measure audio attention. Heart rate indicates cognitive processing that is more intense than automatic monitoring of the environment, which is the low level of attention given to most advertising. Adding audio can generate attention even when people are paying high visual attention, which is why aircraft cockpits have audio alarms in addition to visual displays (Wickens, 2008, cited in Simmonds et al.).
More recently, an Institute report (Bond et al., 2021), based on 14 MediaScience studies, found that even just one audio mention in an ad improved unaided brand recall (18% vs 16%) and brand recognition (69% vs 52%). More audio mentions, particularly when they occurred early (during the first third of the ad), further improved brand recall. But when audio and visual branding were compared in the same logistic regression model, visual branding was still important, and was the only variable related to brand recognition.
Finally, another Institute academic paper highlights that while motion captures attention, what really captures attention is rarity (Wooley et al., 2022). On a made-for-advertising site with 10 or more video ads on the same page, video is less likely to attract attention. Lack-of-rarity would likely reduce the effectiveness of audio branding as well. In the LinkedIn environment, however, with only one ad on the screen at a time, video and audio should have positive effects on attention and memory.
S.B
22 Aug 2024
We classify heavy, medium and light category buyers using (20, 30, 50) breakdown based on purchase frequencies, where the top 20% of buyers with the highest purchase frequencies are classified as heavy, the next 30% as medium, and the bottom 50% as light buyers. However, as purchase frequencies advance in integers, the actual breakdown can be more or less than 20, 30, and 50 (e.g. 19, 22 and 49). This breakdown is quite similar across categories but the purchase frequencies used to classify buyers are different (e.g. the top 20% of milk buyers purchase 17+ times while the top 20% of toothpaste buyers purchase 8+ times)
G.T
22 July 2024
You’re absolutely right that survey data won’t be useful in this context. Unfortunately, good observational research is going to be expensive.
The first shopper report to read is this one: https://sponsors.marketingscience.info/reports/the-fundamentals-of-shopper-behaviour/
It sets the scene for what we do know about shopping. Namely, it’s super fast, and just for a few items. People visit only a small proportion of a store. This means that secondary placements are SUPER important for achieving reach of all people in the store. This also means that being placed at the register could be the best place in the store! Maybe the main benefit of being on the shelf is that you’re next to direct competitors, so that when people are buying a similar product, you’re also there to be considered?
This report might also be interesting, in terms of giving more ways to think about those patterns of behaviour we see, in the context of parents and children: https://sponsors.marketingscience.info/reports/the-incidence-and-influence-of-children-in-supermarkets/
In terms of determining the actual importance of the shelf, I’ve a few ideas:
We found that people do still use the aisle, even when the endcap is present. It’s not quite the situation you’re talking about, but it’s similar.
B.P
18 July 2024
Ehrenberg-Bass talks about focusing on the category buyer profile in order to grow.
The target audience we recommend is to target Category Buyers. This aligns with the extensive data we have that shows brands grow primarily through expanding the brands penetration, hence, to do this you want your advertising to nudge the purchase propensities of all potential buyers for your brand.
Following the example that you provided, of your brand’s latest ad, “We know he performs better with younger males so normally our recommendation would be to target that demo with our digital ads.”
If you have a creative that doesn’t work broadly across your category buyers, in this case, women and older males, it would be missed in the media target. We suggest that if you can, create an ad you can use across all – but if you have a skewed appeal ad, that is fine to target younger men. However, the total campaign (ie including other creatives) should be designed to reach out to those other buyers (ie women/older men), to ensure you are reaching all category buyers.
Below some more pieces from the Institute’s research to read:
Smart Targeting
https://sponsors.marketingscience.info/marketing-commentary/smart-targeting/
Sophisticated mass marketing – explained
https://sponsors.marketingscience.info/marketing-commentary/sophisticated-mass-marketing-explained/
V.B
24 June 2024
While there is knowledge related to visual search, there is very little replicated, published research regarding search at supermarket shelves (Kasneci, 2014). Visual search is not a definite flowchart type process. It relies on neurons and neural networks, which operate on probabilities, not definites (Eckstein, 2011).
One thing to keep in mind when considering this type of research is that the time spent at shelf is so so short that the order in which people see thing on shelf are unlikely to be meaningful.
Report 67: Shopping Takes Only Seconds…in-store and online
People are only buying a few items, and most of these they have bought before, so an active “search” process is a very rare behaviour.
Report 64: The Fundamentals of Shopper Behaviour
That means when we’re talking about “search”, we’re really looking at “search of visual fields”. One way of thinking about it is that if you’re looking for your partner at the airport, if you had the most powerful computer in the world that could see everywhere at once, you could find them instantaneously. But, we have brains and eyes that need to search the visual field to find them. How they do that is the subject of a huge amount of research, as we still don’t have a single answer like “from the top down,” because that’s not how eyes or brains work.
Preattentive processing (Kristjánsson & Egeth, 2020; Treisman & Gelade, 1980) is the idea that before even attending to a scene, our eyes and brains use a range of strategies (see below) to determine where to focus first. These vary in the number of layers of processing from triadic models (Rensink, 2000), to computational salience models eg (Tsotsos, 2011).
There are more directed models of processing, e.g., the Target Acquisition Model (Zelinsky, 2008), but these usually involve some parallel processing similar to the pre-attentive processing models.
Guided search (Wolfe et al., 2015) is where people look for something and already have some idea of what they are looking for, e.g., looking for the green pack. However, people probably can’t tell you what exactly it was that they were using to help them find what they were looking for. In a marketing context, we would say that Distinctive Assets are those things!
There are at least five factors that guide attention during visual search: bottom-up salience, top-down feature guidance, scene guidance, history, and value (Wolfe & Horowitz, 2017). Bottom-up salience is where your eyes themselves direct attention to visual features that might be important. This is processing in the eye, rather than the cortex. This means features like centre-surrounds (think of the Target logo) attract the most attention. Top-down feature guidance is where your conscious brain directs attention. Scene guidance is knowing that a toaster is more likely to be found on a bench than on the floor, or that a big bag of rice will be on a lower shelf. History is knowing where an object was last time, i.e., don’t move shelves around unnecessarily, or what the object looked like last time. And value is how important the object is to them – which is going to vary tremendously, but still not be very high, and so if shoppers can’t find an object, then they are likely to give up well within the 20 seconds maximum they spend at shelf.
Bottom-up guidance
People are more likely to see and find objects closer to the centre of their field of vision (Tatler, 2007, 2011). This does mean that you shouldn’t be on the very top or very bottom shelves. And, given that people are of varying heights, there is no perfect height for your product to be at.
If the search task is easy, then peripheral vision is enough to find a pack, without needing to fixate (Eckstein, 2011). Fixations on a pack at shelf aren’t needed to find it either (due to preattentive processing) – so if research is using fixations to determine “findability” then it’s not necessarily measuring the right thing. Your job should be to make sure that your pack comes up looking bad on eye-tracking because people don’t need to fixate on it to find it!
History
Pre-exisiting mental structures guide search: people aren’t coming to the shelf for the first time, but have some idea of what they’re looking for. Their history will shape the search strategy they use to find the product (Wolfe, 2020). People are faster at finding things they have found before. This applies to simple objects, in a clinical setting, where the colour of the object they found in one trial influences how fast they find the next object of the same colour (Theeuwes, 2018), but will also apply to products on shelf. Changing the packaging will disrupt this, and slow search.
Most important is that you give shoppers a known target to search for: that is, you don’t change the pack without a very, very good reason. People who buy the brand less than once a year make up 40% of the brand’s sales
Report 73: Ultra-lights – The Unbearable Lightness of Buying,
and if they are looking for the pack they bought last time, and it has been changed, then you may as well not be on the shelf.
Scene guidance
People look for objects in the place they last saw them (Walthew & Gilchrist, 2006; Maljkovic & Nakayama, 1996), so if a product that used to be at the bottom of the shelf moves to the top, they will look at the bottom shelf first.
Or, people can use knowledge of what other brands are usually near the brand they are looking for to find things more easily (e.g., search times: Posner, Snyder, & Davidson, 1980; accuracy: Luck et al., 1994; Palmer, Ames, & Lindsey, 1993; Smith & Ratcliff, 2009).
Value
The importance of the search task will shape the search strategies people use – if the reward for getting it right is higher, then they will be more likely to spend more effort and energy searching before giving up (Van Wert, Horowitz, & Wolfe, 2009; Rich et al., 2008, Failing & Theeuwes, 2017). The more often people are rewarded for finding an object, the faster and better they are at it (Navalpakkam, Koch, Rangel, & Perona, 2010) – in the context of shopping, that means the better your product is, and the more often people buy it, the faster they will be able to find it. (Eckstein, Schoonveld, & Zhang, 2010).
This article is well-written and relatively easy to read:
Visual Search: How Do We Find What We Are Looking For?.
It also has some great content about the search templates that people use, which are more about “don’t change your pack unnecessarily” in section 4.
This is a deeper look that includes more about the specific neural pathways and processing that occurs: Visual search: A retrospective
You can see from even a cursory reading of these articles that “people shop from the top down” is misleading at best, and more likely completely wrong.
B.P.
14 May 2024
Some facts and figures from the Institute itself were published in a Journal of Advertising Research article a few years ago, but are still relevant today (Barwise et al., 2020). In that article, we obtained Nielsen data in 2017 to compare younger television viewers (aged 18 to 34 years) with older viewers (35 to 54 years). Those born from 1981 to 1996 (aged 21 to 35 in 2017) would be Gen Y (Millennials) and those born later (aged 18 to 20 in 2017) would be Gen Alpha. These younger television viewers were different from the older viewers because they watched less live TV and more online TV (via smart TVs and connected-TV devices, or other online devices, such as PCs and smartphones). Compared with 18-34 year olds in 1992, 25 years earlier, the 2017 18-34 year olds watched slightly less TV (live + online) per week (29.1 hours per week vs 30.1 hours in 1992, a 3.6% reduction). In contrast, the older group (35-54) had increased their TV hours (live + online) per week (from 33.3 hours in 1992 to 38.8 in 2017, a 17.5% increase). We can probably assume that 18-34 year olds in 2017 dedicated as much of their week to media consumption as 35-54 year olds, and that the nearly 10 hours difference was absorbed by consuming social media and other alternatives to television.
This suggests that advertisers need to use other media in addition to television to reach Gen Y and Gen Alpha, such as social media, radio, and out-of-home.
Which social media to use to target younger people changes when they migrate to alternatives less likely to be used by their parents. Currently, a Statista report from October 2023 shows that most (68%) of the audience for TikTok was aged 18 to 34. Only 25% was aged 35 to 54.
These numbers are about media usage, and useful for deciding which media to use to reach consumers of different ages with advertising messages. Another of our Institute articles suggests there are no differences between age groups in brand usage (Anesbury et al., 2022), which should be the main metric for brands to consider.
References:
S.B.
11 January 2024
I think the most succinct and important thing to know is that while people will enter categories and brands naturally as they age, they will do so with their existing Mental Availability (MA), which is built mostly by usage. So, if you can provide a way for pre-family shoppers to have purchase and usage experiences with your brands before they regularly buy from the categories of interest, they will be more likely to buy your brands when they do get there. Which is a strategy that looks an awful lot like sophisticated mass marketing: making sure that you have offerings for anyone who has the potential to buy from your category.
For the first two questions, the answer is “yes, of course” – people are going to be more likely to buy school snacks when they have a school aged child and aren’t likely to put out treats for Father Christmas when they have teenagers. But equally, aunts and uncles and grandparents who might not have a child in the household will still buy these things, and there are some people who might like to buy the occasional child-focused treat for themselves.
In terms of specific research we’ve conducted related to aging and consumption, here’s what we’ve found:
This all leads to the conclusion that there is some value in making sure that you have products for all ages, and that value comes in two ways. The first is simply in making sure that you are targeting the whole market: making sure that anyone who has influence over a purchase (either direct or indirect e.g., Report 113: The Incidence and Influence of Children in Supermarkets) can buy something from your brand. This buying behaviour will help the second source of value – Mental Availability.
The second value comes from making sure that potential buyers have Mental Availability for the brand that you can leverage down the track. So, if you are thinking in a decades-long environment, make sure you use your Distinctive Assets, don’t change the pack too much, and don’t use shrinkflation to ruin a product. When people begin to buy a category, they will use their existing MA to shape what they notice and buy.
That is, people will both naturally age in and out of categories, but they won’t enter a category with completely blank minds. I’m not sure what you mean by older brands (aimed at old people, or have been around for longer?), but the key thing to remember is that new people will be entering a category for the first time every day, and existing buyers will be forgetting about your brand every day too. So your key tactic should be to remind new and existing buyers that you exist and are a good option to fulfil the Category Entry Points for each category. Even for established brands and categories, light buyers are key – and they are far lighter than even we imagined: Report 73: Ultra-lights – The Unbearable Lightness of Buying.
But, we do see that simply because people have bought a product before, they aren’t going to be 100% loyal to that brand. There is no way to ensure that shoppers become super-loyal just because they tasted it at a young age!
Thinking more about pre-family shoppers, the key would be to reach them where they are at, rather than looking at them only as potential future consumers. The key to all of the above is that current behaviour – not attitudes – is what drives future behaviour. That is, if you can get pre-family shoppers buying from you now, they will be more likely to buy from you down the track. One way to do this would be to sell the same product to them, by reaching them with messages relevant to them e.g., Snack X is great to have at work, not just at school, or by formulating products relevant to their current lives, and with consistent Distinctive Assets between the family vs pre-family variants. I wouldn’t rely on anyone finding out about your brands by luck, but would rather have campaigns designed to reach all potential category buyers.
22 November 2023
B.P.
We have definitely done research in situations where unbranded choices are very high, including diverse categories like exercise or transport choices (including walking, own car use or brands like uber in the mix), aviation fuel contracts and concrete. Perhaps one of the more relevant examples is fruit and veg. I’ve attached some examples of papers below, including one which includes Indian data. There is also one article (a bit more academic) that looks at branded and unbranded snacks and the importance of mental availability on choice.
Patterns of fruit and vegetable buying behaviour in the United States and India
The fallacy of the heavy buyer: Exploring purchasing frequencies of fresh fruit and vegetable categories
Analysing proprietary, private label and non-brands in fresh produce purchases
The Effect of Mental Availability on Snack Food Choices
In some markets, different regions can look like quite distinct markets. In big cities bigger brands dominate, with more non branded and local brands being more popular in other markets. In such situation, the expected patterns are easier to identify at the regional level, but still hold more broadly (just with some important deviations or sub-markets).
R.K.
6 September 2023
Research has shown that the frequency with which shoppers look at the back of a product’s packaging when making a purchase decision can vary depending on several factors, such as the product category, consumer demographics, and the information provided on the pack.
A study by Grunert and Wills (2007) found that, on average, about 50% of shoppers claimed to look at the back of the pack when buying food products, while other studies have shown that the proportion of claimed behaviours can be as high as 70% (e.g., Grunert et al., 2004) or as low as 20% (e.g., Antonides and van der Lans, 2002). However, this is claimed behaviour, and we know consumers usually over-claim behaviour. We suspect those using the back of the packaging to make purchase decisions to be very low.
When we look at the evidence of time taken to make decisions in-store, we know the speed of purchase decision-making can vary depending on various factors. Still, it occurs very, very quickly, most often in a matter of seconds (Report 67). This means it’s highly unlikely many shoppers will use the back of the packaging to make decisions.
Nutritional information: One of the most common uses of back-of-pack information is to obtain information about the product’s nutritional content. This information can help consumers make more informed food choices (Aschemann-Witzel et al., 2015; Grunert & Wills, 2007).
Ingredient list: Consumers may also use the ingredient list on the back of the pack to learn about the components of a product. This can be particularly important for individuals with food allergies or intolerances who must check for specific ingredients (Hieke & Taylor, 2012).
This would differ greatly by the design of the product’s back of the packaging. It is hard for us to give generalisable results as these studies are usually commercial in confidence. We have not seen any large-scale study to support one layout over another.
Based on my expertise, the below should still be important.
I suspect recipes are less valuable. If someone is looking at the back of the pack, they have already navigated to the category and narrowed their consideration set. I.e., you’ve already made it over the biggest hurdle. Recipes, at this point, are likely to have very low ROI in terms of purchase rates.
References:
Aschemann-Witzel, J., Grunert, K. G., & van Trijp, H. C. (2015). Effects of nutrition label format and product assortment on the healthfulness of food choice. Appetite, 91, 56-64.
Grunert, K. G., & Wills, J. M. (2007). A review of European research on consumer response to nutrition information on food labels. Journal of Public Health, 15(5), 385-399.
Hieke, S., & Taylor, C. R. (2012). A critical review of the literature on nutritional labelling. Journal of Consumer Affairs, 46(1), 120-156.
Corporate Report 67: Shopping Takes Only Seconds…in-store and online
W.C.
11 April 2023
We have done some in-store observational work about pester power – see the publications linked below. We also have a corporate report (where this is all laid out) under development, which should be released later this year.
The upshot is that parents often leave children at home to do the shopping, and shop faster than “normal” shoppers (even if the kids aren’t there), so you have even less chance to influence them in-store than the usual – which is only a few seconds to begin with. We saw that children ask for all kinds of things – not necessarily what you would expect – and parents are quite good at saying no. We think that this is likely to be culturally bound: researchers in the USA have found that (for some categories) parents give in more than parents in Australia.
We didn’t see much evidence that pester power is important in a direct sense, where children see a product in-store and ask for it. There is still the chance for children to ask for products while they’re at home, but there isn’t much evidence for or against how important this might be. The third type of pester power, which is likely to be the most important, is more of a “passive power”, where parents buy what they know their children will eat.
While getting Marvel characters on-pack could be good in terms of the first two types of children-power, the primary target in-store should still be parents. Children may ask for products they see in-store, but far more often it will be purchased by parents. More important is using Distinctive Assets that you have built up with parents outside of the store, to make your products easier to notice and buy in the very short window of opportunity you have with parents.
It’s good for kids to like the product, but far more important that it’s acceptable to parents, that they know about it, and can notice it easily on shelf.
In terms of communication targets, reaching parents is more likely to have success than reaching children. We know that advertising works mostly by refreshing memories, rather than persuading. And, as parents are the ones doing the buying, it is their memories we care about. This isn’t to say that there is no reason to target children, but their experience with the product is more likely to be important in making sure that it is acceptable to them than the advertising.
So perhaps the best way forward is to target the product experience at the children, and the marketing comms and in-store at the parents.
Using the Eyberg Child Behaviour Inventory to investigate Pester Power
Parents and Children in Supermarkets: Incidence and Influence
B.P.
30 March 2022
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