Do different awareness measures measure the same thing ?

There is a history of discussion amongst marketers about the relative merits and meaning of different awareness measures. Then in 1995 an article was published that appeared to lay all this debate to rest:

Laurent, Gilles, Jean-Noel Kapferer, and Francoise Roussel (1995), “The Underlying Structure of Brand Awareness Scores,” Marketing Science, 14 (No. 3, Part 2), G170-G79.

Gilles Laurent and colleagues appeared to show that different brand awareness measures were systematically related, simply reflecting different levels of difficulty for respondents (i.e. brand prompted being easier than unprompted). So the different measures all tapped one construct, and a score on one measure could be used to accurately predict a score on another measure. We thought that was an incredibly important and practical finding. However, not was all that it seemed.

Nearly a decade later we replicated this research, and extended it to ad awareness. We achieved the same empirical results, but in doing so we were able to more clearly see what the previous research had, and had not, found. The measures tend to vary together, brand to brand, because some brands are much larger and more salient than others, so all their awareness metrics are higher too. However, we also examined the relationships between the loyalty metrics for each brand over time. Contrary to Laurent’s conclusion we empirically found that it isn’t possible to use their model to predict a brand’s score on one metric from its score on another.

So while all these brand awareness measures share something in common they do not perfectly tap one underlying construct. That’s as important a finding as Laurent’s might have been (if it had turned out to be true). Different awareness measures measure (somewhat) different things, even if they are all loosely related to the brand’s overall salience (and market share).

Romaniuk, Jenni, Byron Sharp, Samantha Paech, and Carl Driesener (2004) “Brand and advertising awareness: A replication and extension of a known empirical generalisation” Australasian Marketing Journal, 12 (3), 70-80.

The power of familiarity

I few years ago Emma Macdonald and I published this work showing the power of familiarity. When we did this in the late 1990s there wasn’t a great deal of interest in heuristics, snap judgements, and gut feeling. But today psychologists and behavioural economists are gaining a great deal of attention for their work showing how reluctant consumers are undertake a lot of cognitive effort when buying.

I’ve often said it is wrong to call much buying “consumer decision making”, it’s more buying (doing) than decision making (thinking).

Macdonald, Emma and Byron Sharp (2000) “Brand Awareness Effects on Consumer Decision Making for a Common, Repeat Purchase Product: A Replication” Journal of Business Research, 48 (Number 1, April), 5-15.

Snake (oil) and loyalty ladders

Many market research houses now market a “loyalty ladder” or “loyalty pyramid” product. These dissect a brand’s customer base into 4-6 groups, starting with something like “no awareness” at the bottom and ending with something like “passionate loyals” at the top. This classification is usually based on behaviour (or claimed behaviour) such as share of category purchases devoted to the brand in question. Some add attitudinal statements into the customer classification. Others, like The Conversion Model, claim to be entirely attitidudinal.

All these do is reflect the brand’s relative popularity (i.e. market share) and random sampling error (which looms large when you have 4-6 groups).

Marketing Science has known for decades that loyal behaviours and attitudes follow a set statistical distribution, and so any brand’s true loyalty ladder can be accurately predicted simply from knowing its size compared to rivals. And if it has 100% relative share, then all customers will be at the top of the ladder, but not until then.

I suppose these ladders are attractive because intuitively marketers feel it’s their job to move people along this path, sorry up this ladder. Yet I notice that my practitioner colleagues rarely draw any practical insights from these ladder metrics, they provide more entertainment value (”that looks interesting”) than knowledge. Which is fine, because that’s all they are, an entertaining expensive way of presenting, and obscuring, loyalty metrics.

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Is recognition a better advertising metric ?

Robert Heath makes a sound case that advertising campaign recall is not the perfect measure of advertising effectiveness. This is not controversial, indeed it would be hard to find anyone who would argue against this position. It’s one thing to recall that a brand has been advertising, another to recall a particular ad, and yet another for the ad to build/refresh brand memories.

More interestingly Heath makes an argument for the use of visually prompted recognition to evaluate advertising performance, especially for affective (non persuasive) ads. Then he presents empirical evidence that shows that non-brand users who recognised the ad felt better about the brand. Whereas the (few) who recalled the advertising did not feel any better about the brand than those who did not recall the campaign.

Very interesting. Except that his sample size is 2, i.e. two (non persuasive, affective) ads.

Both these articles cover the same arguments and same 2 ad tests:

1) Heath, Robert and Agnes Nairn (2005), “Measuring affective advertising: implications of low attention processing on recall,” Journal of Advertising Research, 45

(2), 269-81.2) Heath, Robert and Pam Hyder (2005), “Measuring the hidden power of emotive advertising,” International Journal of Market Research, 47 (5), 467-86.

Memory is complex, so is communication. Different metrics give different insight into how the communication is affecting memory. The problem with using visually prompted ad recognition as test of memory is that people have fantastic ability to recognise images. So it functions more as a test of exposure, than of memory - which makes it a useful measure but in different ways, i.e. not as a direct measure of advertising effect.

Verbally prompted recognition (i.e. verbally describing the ad) is possibly a better way of assessing whether it was seen and processed a little, and helps diagnose if the problem is that the communication doesn’t get noticed or if the branding is off. It essentially gives a lot of cues but is less complete than visually prompted ad recognition.

Both my and Heath’s hypotheses need more testing.