Download the full Controlling Trade Spend Case Study PDF

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.

Download the full When brokers can offer a low cost merchandising service Case Study PDF

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.

Download the full Composition of incremental lift Case Study PDF

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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In 1987, I read an article written by Porter Henry, President of Porter Henry & Co. In an article entitled ‘The Important Few – The Unimportant Many’ he mentioned in passing that the 80:20 distribution with which we all are so familiar, does not describe the distribution of things in FMCG. In his original article he used data to construct calling plans for a territory, and to illustrate how easy it is to over-service small customers – and thus by definition under-service the few big ones who count. In fact Porter Henry did not make a big song and dance about the fact that 80:20 does not fit grocery, so I will address that issue now.

The 80:20 rule is so well known because it does describe distributions which fit many situations in business. In fact it describes accurately the distribution of sales in industrial selling, where one or two big customers will dominate your orders. But wherever consumers play a large part, there is a different distribution. In this situation the sales are far more evenly spread.

So if you are looking to:

• optimise your sales territories, and ensure your merchandisers or sales reps allocate their time efficiently
• determine if your sales are adequately distributed across a territory
• find out if your product range is too deep
• find out if you should expand your product range

Download the full article The distribution of sales in FMCG / Grocery Case Study PDF

The strategy planner in Promax PX has been specifically designed to enable this scenario planning (What If Planning) to be carried out. Promotional programs can be rapidly constructed with productivity tools that enable cut-and-paste and repetitive copy. The graphical environment facilitates a drag-and-drop mechanism with colour coding of each promotional type.

The spreadsheet style of Promax PX facilitates an easy “what if” analysis of an individual promotion, and entire promotional program or multiple scenarios involving the exploration of pricing elasticity and promotional frequency. Tools like the strategic optimiser allow the business to explore new strategies of pricing and frequency to maximise profitability or marketshare objectives. The strategy planner allows the assembly of scenarios testing tactical plans for any group of products or customers. Full financial evaluation of every strategy is created and easy comparative techniques provide a clear path for the account manager to evaluate the best plan.