So you have done your promotional planning, does that mean no more problems? Unfortunately not. It is still quite easy to end up with a severe overspend situation. This is because most promotions have no limit on the amount the chain may wish to buy. Why this should be so is one of those things that has become ‘part of the way we do business’, and has no basis in logic. It is just as illogical as extended buy periods, for businesses where there is perpetual motion and a pipeline of product! But it causes very real problems. Even with the most careful of planning, unless you monitor the trade spend during the year, you will almost certainly get a big surprise at the end of the year. Planning alone will not control trade spend. In this section we are not concerned whether the trade spend is worthwhile, only with keeping the total costs within predefined boundaries.

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The smaller food suppliers seem to swap their own sales force for a broker service, only to go back to a direct force a few years later. Sometimes they then return to a broker yet again. Brokers naturally present themselves as an efficient and experienced alternative. Even large grocery companies sometimes go with a broker service – Kelloggs did that here in Australia. The question that has puzzled many a Sales Director is ‘How can you decide whether a broker would be less expensive?’ (The question of better I leave to another day!) And why should a broker be able to offer a better service that is lower in cost?

A couple of years ago I was able to compare the merchandising costs of a number of Australian Food suppliers. These companies differed in size, and indeed differed in the objectives they set for their field force. Nevertheless I was intrigued to discover that costs can be predicted with relative ease.

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This is a precis of a research paper entitled ‘The Decomposition of Promotional Response: An Empirical Generalisation’ by David R. Bell, Jeongwen Chiang and V. Padmanabhan, published by Marketing Science.

This very interesting paper based on research conducted in 1999, studies 173 brands in 13 categories in the USA over a 52 week period, based on the household expenditure of 250 families and 3 stores. The overall conclusion is that the percentage of promotional lift attributable to brand switching is an average of 75%, which is somewhat below previous studies. In 1988 Gupta measured this at 84%, and A.C.Nielsen more recently (precise date unknown, but published in 1996) at 80%.

Of even more interest is the category by category variance. Categories were selected to encompass both those that are known to expand consumption, as well as those that are ‘storable’ or ‘necessities’.The balance of the lift not attributable to brand switching was also analysed into the two components of category expansion (genuine additional incremental volume) and accelerated purchase (reduction in expected inter-purchase interval). A determination was also made of the relative impact of brand factors, category factors and consumer factors to identify which is the most significant. All in all, they are able to explain 70% of the actual promotional response. One of the significant findings is that category effects are more significant than brand effects, and consumer effects (i.e. demographics) are quite minimal.

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The important few – the unimportant many

This article first appeared in print sometime around 1986. It was written by Porter Henry, President of Porter Henry & Co. This is an exact reproduction of the original article, although obviously the tables and charts have had to be recreated. Reproduction here is not intended to infringe the copyright of the original author or the unknown publisher of the original article. Attempts have been made to contact Porter Henry and Co, and the original publisher is unknown, as the photocopied article has no identifying marks.

Theoretically, for every customer, there is a call frequency that will give you your maximum volume, or profit, per call. There is a bell-shaped curve for every customer – a little curve for a little customer, a big curve for a big customer. The maximum return per call might be realized from 3 calls per year for one customer, 6 for another, and 17 for another. It’s just not practical to establish a different call frequency for each customer, however, so we advocate using a short-cut. Presented here is an accurate method of allocating your time based on both your present and your potential business. This method, which requires you to divide your customers into three categories, is based on a principle we call ‘IFUM’ – the Important Few and the Unimportant Many.

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