UNIDAD 6.- ANUALIDADES VENCIDAS
6.5. PAGO PERIÓDICO DE UNA ANUALIDAD VENCIDA
in 2011, advertising agency ogilvy & mather released data from a market research survey that asked consumers which brands they trusted to handle mobile payments. patel (2011b) summarised the finding as ‘consumers trust the same brands that handle their payments today’, implying bad news for new potential entrants such as Google and apple.
C h a p t e r 2 : C o n s u m e r B e h a v i o u r a n d B u s i n e s s B u y e r B e h a v i o u r 6 1
Even if we wanted our behaviour to be based on our attitudes, our ability to use our attitudes to guide our behaviour depends on memory. Our recall of brand attitudes is highly variable: one time we recall something nice about one brand, and next time we recall another brand.
What this means for the practical marketer is that they should spend very little time worrying about consumers’ attitudes, and instead spend more time thinking about how to make the brand easier for consumers to notice, to think about and to buy—mental and physical availability. Here are three facts about brand attitudes that show how little influence attitudes have in changing buying behaviour.
1 Brand attitudes reflect past buying behaviour
By the late 1960s, research evidence was clear: attitudes were not strong causes of behaviour. Instead, the evidence showed that behaviour was a better predictor of attitude (Foxall, 2002). Forty years later, surprisingly few marketing textbooks have caught up, and much academic and market research is still predicated on the belief that there is a simple relationship where attitudes cause intentions, which in turn cause behaviour. But the evidence shows a picture that is more often around the other way—brand attitudes largely reflect buying behaviour, and changes in behaviour mostly precede changes in attitude.
So, in market research attitude surveys we see a clear pattern where brands that have more users in the survey score higher on evaluative questions (such as ‘do you like this brand?’)—and brands with fewer users score lower on the attitude metric. So larger market share brands tend to score higher. This is largely driven by familiarity. If people don’t use a brand, they are more likely to know nothing or little about it, and they are less likely to say they like it. But even when the scores are compiled only for those who know of the brand, the brands with more users still score a little higher. For example, among viewers of a particular television program, the more often a viewer watches it, the more favourably they will rate it in a survey (Barwise & Ehrenberg, 1987).
The more attitudinal (evaluative rather than descriptive and/or factual) in nature a question is, the more precisely we can predict a brand’s score on that question—simply by knowing how many past users the brand has in the survey and how often they have used the brand.
So, brand attitudes largely reflect existing loyalties. If someone uses a brand, they are much more likely to say nice things about it than someone who does not use it. And the more often that they buy the brand the more favourably they tend to rate it.
2 Intentions reflect past buying behaviour
Early follow-up surveys after the US Census showed that households who said they intended to buy a new car were, unsurprisingly, more likely to actually buy one than households that said they did not intend to buy (40 per cent, compared to 7 per cent). However, since most (90 per cent or more) of households fell into the non-intenders group, this is where most car sales came from (Theil & Kosobud, 1968). This is quite counterintuitive for a car marketer—to realise that most of next year’s sales will come from households who when interviewed say they are not planning on buying
6 2 M A R K E T I N G : T h E o R y, E v I d E N c E , P R A c T I c E
a car next year. Clearly it is easy to be deflected from one’s intentions (in both directions—note that 60 per cent of people who said they would buy next year didn’t).
For many repeatedly purchased categories (such as groceries, shoes, television programs, petrol or lunch) we don’t really form plans in our head—at least, not long before actual purchase. So, when we are asked about our intentions, we instead largely report an estimate of our future behaviour, which we, quite reasonably, base on our past behaviour. Again, this means that brands that have more users will score higher on intentions: the more people who have bought them in the recent past, the more people who will say they intend buying them in the near future.
The strong influence of past behaviour on intentions produces the counterintuitive result that intentions are unexpectedly low for growing brands, and unexpectedly high for dying brands. If there are two brands that have currently equal market share, but one is a new, growing brand and the other is an old, declining brand, then intention surveys will record a higher score for the dying brand than the growing one. This is because the dying brand has more past users who know the brand and are therefore more likely to mention it in an intention survey (such as ‘which brands of chocolate bar do you intend buying in the next three months?’), while the growing brand has fewer past users, so it isn’t mentioned as much. In the future, the growing brand’s sales will exceed the dying one, so common sense would suggest that the growing brand should have more people intending to buy it in the future, but what actually happens is that when people are asked their intentions they base their reply on what they have been doing (or the effect that this has had on their memories). What’s actually happening in the marketplace is that the growing brand is rolling out physical availability and building mental availability (for example through advertising and publicity), so more people than thought they would actually end up buying it in the future, while the opposite story holds for the declining brand.
3 Brand attitudes are probabilistic
Attitudes have long been thought to be difficult to change and therefore strongly held. This view seemed to be supported by the stability of brand scores in attitude surveys—brands pretty much get the same score on this month’s survey as they got last month. For example, if 28 per cent of people say they like Zim and only 4 per cent of people say they like Zappo, then on the next survey Zim won’t just dominate again, it will score around 28 per cent and Zappo will again score around 4 per cent. However, in 1994 an academic research team (that included the famous Andrew Ehrenberg) looked at something that previously had been largely ignored. Instead of asking different people in each survey, they re-interviewed the same people as in the previous survey. They did this because they were interested in how many people changed their answer from one survey to the other. Surprisingly, they found that, on average, only around half the time did people give the same attitudinal response they gave previously. This was a shocking finding. Were people really changing their opinions all the time?
So while 28 per cent of people might say they like Zim on each survey, only about half of the people who endorsed Zim on the first survey do it again on the second survey. Zim still scores 28 per cent, because every person who said they liked it on the first survey but not on the second is replaced by someone who didn’t say they liked Zim on the first survey but now does on the second survey.
C h a p t e r 2 : C o n s u m e r B e h a v i o u r a n d B u s i n e s s B u y e r B e h a v i o u r 6 3
Previously, marketers interpreted attitude survey data like this: if 28 per cent of people ticked the ‘like’ box (or upper end of a liking scale question) for Zim, that means that there are consumers who like Zim (around 28 per cent of the population) and consumers who don’t (the remaining 78 per cent of the population). But now we know that the correct interpretation is that much more than 28 per cent of consumers like Zim, but only sometimes—attitudes are probabilistic.
This discovery has been replicated and extended many times since, with several PhDs written on the topic. We now know that individuals’ attitudinal responses over time follow very similar patterns to their buying behaviour. Consumers buy brands in a polygamous manner, not buying the same brand each time but selecting from a personal repertoire—and this is how they give attitudinal responses too. Sometimes they say Omo washes whiter, sometimes they say Surf does. If they buy Omo more often than Surf, they say Omo more often, and they rarely express attitudes about brands not in their buying repertoire.
Consumers’ responses vary, in a probabilistic way. This is similar to how the result of a coin toss varies (either heads or tails) but each coin tossed has a probability of 50 per cent of landing on either side; there is lots of variation from toss to toss, but an overall pattern (50/50). The probabilistic behaviour in market research surveys is probably largely due to the fact that consumers’ responses depend on their memories, which aren’t perfect, and so which particular brand comes to mind in any instance varies. Professor Frank Bass once speculated that the human brand might have an inherently probabilistic aspect to it (1974); decades later, this discovery supports his view. This doesn’t mean that consumers are doing complex calculations in their heads; it just means that which brand comes to mind and which one they choose to tick on the survey is due to many highly variable causes, some inside the brain (such as particular synapses firing in the brain at just the right time) and others out in the environment (such as seeing a brand’s pack in the rubbish bin shortly before doing the survey).
This also strongly suggests that brand attitudes, while enduring, are typically not strongly held. In the same way that we are rarely 100 per cent behaviourally loyal to one brand, neither are we 100 per cent attitudinally loyal—sometimes we say one brand is best and sometimes another, because we like them both, but not in a particularly passionate way.