Advertising Reach And Frequency: What Really Works?July 2004

'Reach' (Cover in US) and 'frequency' are easy to define. Reach means the proportion of the target population who will see our campaign at all, 'frequency' means the number of times those people will see it. Advertising schedules aim to achieve the best affordable combination of reach and frequency. An ad should be seen often enough to cut through clutter and get noticed, but too often is wasteful, or even counterproductive (15). The term 'effective frequency' denotes the 'right' level of frequency, and effective frequency planning (EFP) has been the basis for most schedule modelling for the past 30-odd years.

Unfortunately, this simple account begs some key questions (1, 3). First, frequency of what? Are we talking about opportunities to see/hear (OTS or OTH), ie exposure to the medium containing the ad (usually the only thing for which there is any available measurement) or proved exposure to the ad itself? We know that proved exposure is a lot lower than OTS, but how much lower may vary between different media and products. Secondly, frequency when? Two exposures may have very different effects if they are concentrated within a day, or close to the next shopping occasion, than if they are spread over weeks. Thirdly, what effects (sales, purchase probabilities, awareness measures and such like) are we to use to compare frequencies - they may all be different? Underlying these questions is continued uncertainty - and disagreement - about the psychology of how people respond to ads in different circumstances (4). Much of the argument in recent years has arisen from people trying to fit limited evidence into different all embracing theories.

Rise and fall of the 'magic number' (1, 2, 3, 4, 5)

Before EFP, planners worked with average frequencies, which were flawed by the fact that many different media exposure patterns could lead to the same average figures. When computers appeared in the 1960s, it became possible to work with frequency distributions. Planners could now see how many people would be reached once, twice, three times, and so on. But they needed guidance to use this knowledge: what was the 'right' level? A rule of thumb was very attractive. If 3+ (say) could be agreed as the 'effective' frequency, then scheduling plans could be compared on the basis of which one delivered the best 'effective reach' (ie maximised reach at 3+).

Effective frequencies of two or three are intuitively appealing, since they assume a threshold that a new ad must break through to get noticed (4, 6). The idea was given weight by Krugman's 'Three Hit Theory' (7, 8): the first exposure simply gains attention ('what is it?'), the second establishes relevance ('so what?'), and the third consolidates, either positively ('for me') or negatively ('forget it'). Subsequent exposures simply reinforce the third, unless there is a long interval, in which case one goes back to the first level. Empirical support was found in McDonald's study of switching behaviour (9), and other evidence gathered together in Naples' 1979 book (10), which seemed to show that frequencies of 2-3+ were indeed 'effective' in influencing actual purchases. Critics attacked both the theory and practicality of this rule of thumb. The research evidence showed that thresholds are rare. The most common response curve is 'concave downwards', or diminishing returns (4, 14, 16) - the first exposure has the greatest effect. Krugman's finding may be relevant in learning situations, but most advertising seen by potential buyers is for something already very familiar. Jones's analysis of single-source data (2) appeared to confirm strongly that diminishing returns are normal, and gave immediate support to 'recency planning'.

Recency planning is often presented as an alternative to EFP, but is really a special case of it - the objective is to maximise reach, even with a frequency of one. The recency argument is that ads work when people are in the market to buy, and there are always some people in the market, although one never knows who or when. The objective, therefore, is to be present as continuously and widely as possible (11, 12, 13). With any plan (even for 1+ cover) a frequency distribution is inevitable: if you plan for higher frequencies, you cannot afford more than occasional bursts and the highest frequencies go to the heaviest media users (who may well be your heavy buyers anyway), thus wasting the extra money, 'a schedule bought to reach many viewers twice will waste most of its impressions reaching heavier viewers four, five and six times' (13). Moreover, too many advertising impressions can be counterproductive, for creative reasons (15).

The new complexity

Recency planning has largely superseded the two or three-hit theory, but has come under fire as a rule of

thumb in itself. Critics deny that it is right for all occasions, even if it may be appropriate for most (1, 18, 20). For example, new campaigns, for new brand launches or repositionings, may well have thresholds to overcome in their early stages, and may need heavier advertising weights then than later (19). Roberts found that established brands tend to have diminishing returns, but that new brands are often S-shaped (with thresholds) or linear (24). It is not just a matter of brands being different, the way campaigns are responded to may also change at different stages in the campaign's life (17). Du Plessis (19) argues for tactical monitoring of these changes, so that advertising weights can be adjusted. Beaumont (17) reports four evaluations conducted over two years for the same advertiser, from single- source data on TVSpan, showing how response changed from S-shaped (new campaign, needing at least three exposures), through a reminder phase (optimal returns at two exposures, declining thereafter), an 'established brand' phase (a classic diminishing-returns curve), to, finally, another S-shaped curve like the first, following a change in creative strategy. This is a striking confirmation of du Plessis' claim.

We have, therefore, what looks like a new consensus emerging: new ideas or brands may need higher frequencies to make an impact, but once they become established, the function of the ad is to remind, and reach/continuity becomes more important than weight. But it is  more complex than that (28), we have toconsider timing (frequency when?). Analyses of Adlab and TVSpan have confirmed earlier evidence (23) that short-term effects decay rapidly (an average decay rate of 4.4% a day has been calculated), and that concentration can make a big difference, especially if it is close to purchase (17, 25). So, not all high frequencies are equal, 'concentrated repetition makes a communication more memorable than the same number of repeated messages strung out at intervals' (6).

Other factors also affect results; the type of customer (there is some evidence that light buyers are more responsive than heavy buyers), synergy or lack of it with other promotions (26), and, underlying all else, the effectiveness of the creative treatment. All this leads away from the idea of any single rule-of-thumb or magic number, 'there are no convincing analyses to tell us what 'effective frequency' to use' (18). How then should a planner proceed?

Simon Broadbent (1) recommends that the planner needs the following information to construct and evaluate a schedule; the costs and values to the advertiser of gross rating points (GRPs) in each week, the expected rate of decay (which he uses adstock to estimate), the expected rate of diminishing returns, and the minimum cover criterion (reach plus frequency) during the campaign period. He discusses how all these may be estimated, from historical data about the brand, and demonstrates how to conduct evaluations to compare schedules. As opposed to EFP, this can be seen as a form of 'frequency value planning' (FVP), an approach taken by other writers (for example, 4). The one limitation of Broadbent's book is that it is based entirely on TV. Other media, separately or in combination, may behave differently. This has been far too little studied, but recent commentators have begun to take it seriously (for example, 22, 27).

White and Dawson (5, 28) describe a device, the 'frequency thermometer', for assessing the appropriate level of frequency a media plan should aim for. It is broadly in line with the evidence quoted distinguishing between new and established brands: lowest frequency (or recency) for simple reminders, teasers, simple responses; highest frequency for introducing new concepts, new products or changing earlier associations. But they add a new dimension: other media (28). Low frequency on TV may be converted into higher frequencies, more cheaply and flexibly, by using linked campaigns elsewhere. They propose using separate 'thermometers' for print, radio, internet, etc. in parallel, estimating the weekly duplication between them and TV (from single-source bases such as TGI), and then using the parallel 'thermometers' to achieve an aggregate frequency (judged appropriate to deliver recency of impact) in the most cost-effective way across all the media.

Changing viewing habits and the ever-increasing cost of TV are stimulating increasing interest in mixed-media planning. But more evidence is needed of how buyers respond to other media, separately or combined, and whether their response differs from that to TV alone. Key research studies like the Media Multiplier reports, the Millward Brown study for the Magazine Publishers Association in the USA, and others which have been reported, are relevant (27). The complexity resulting from the current expansion of media, and how planners may try to deal with it by using multi-media optimisers, is discussed in (21).

Core reading

1.  S Broadbent: When to advertise, Admap Publications, 1999. 2.  J P Jones: When ads work: new proof that advertising triggers sales. Lexington Books,

1995.

3.  C McDonald: Advertising reach and frequency: maximising advertising results through effective frequency. Association of National Advertisers and NTC Business Books, 1995.

Historical summaries

4.  H Cannon, J Leckenby and A Abernethy: Beyond effective frequency: evaluating media schedules using frequency value planning. Journal of Advertising Research, November/December 2002.

5.  S White: How effective are your frequency models? Admap, November 1999.

Effective frequency theory

6.  L Bogart: Is there an optimum frequency in advertising? Admap, February 1995. 7.  H Krugman: Why three exposures may be enough. Journal of Advertising Research,

December 1972. 8.  H Krugman: Memory without recall, exposure without perception, Journal of

Advertising Research, August 1977. 9.  C McDonald: What is the short-term effect of advertising, ESOMAR Conference 1970

and Admap, November 1970. 10.  M Naples: Effective Frequency: the relationship between frequency and advertising

effectiveness, Association of National Advertisers, Inc., 1979.

Recency theory

11.  E Ephron: Recency planning, Admap, February 1997. 12.  E Ephron: A scheduler’s hymnal, Admap, May 2000. 13.  E Ephron and M Heath: Teaching tap to the elephant, Advertising Research

Foundation Workshop, Improving Television Measurement, October 2001. 14.  L Gibson: What can one exposure do? Journal of Advertising Research, Mar/Apr

1996. 15.  P Gullen: An excess of OTS, Admap, May 1996. 16.  J Simon and J Arndt: The shape of the advertising response function, Journal of

Advertising Research, August 1980.

No 'magic number' - new evidence

17.  L Beaumont: 5 steps to effective frequency. Admap, December 2003. 18.  S Broadbent: Effective frequency: there and back. Admap, May 1998. 19.  E du Plessis: The shifting response curve. Admap, October 2000. 20.  P Gallucci: There are no absolutes in media planning. Admap, July/August 1997. 21.  T Jarvis and B McElroy: Can optimisers provide a lifeline for media? Admap, Feb

2004.

22.  A Macdonald: Effective reach and frequency: identify and manage media choices to increase communication effectiveness. ESOMAR, Integrated Communications, Paris, April 1997.

23.  W Reichel and L Wood: Recency in media planning - redefined, Journal of Advertising Research, July/August, 1997.

24.  A Roberts: Measuring the short-term effects of TV advertising. Admap, April 1998.

25.  A Roberts: Recency, frequency and the sales effects of TV advertising. Admap, Feb 1999.

26.  A. Roberts: TVSpan: the medium-term effects of TV advertising, Admap, Nov 2000

27.  A. Smith: Take a fresh look at print: building on the media multiplier proposition, ESOMAR, Strategic Publishing, Milan, October 1999

28.  S. White and C. Dawson: Frequency and recency: keeping your customers close, Admap, July/August 2003