How MMM helps optimize pricing decision for FMCG players

One of the key functions of the marketing/sales department in fast moving consumer goods players is to get the pricing right. The pricing decisions are an everyday activity, as inflation leads to price changes at periodic intervals but more importantly competition is always playing the pricing game through promotions such as 10% more volume, Rs 5 off or a free spoon with every biscuit packet and so on.

Given that wrong pricing decisions impact the bottom line negatively – too much of an increase hits sales and too little hits margins. So how can marketers do a better job when it comes to pricing?

Marketing Mix Modelling (MMM) is a good process to use to get a number of insights for this problem. The advantage with Marketing Mix Modelling is that is takes into account every other factor that may be influencing sales such as distribution changes, advertising (own or competition) apart from price changes. This makes the analysis more robust and therefore much better than simple sensitivity tests that pass for pricing analytics

What insights can we get from an MMM study?

1. What is the elasticity for my brand? How much sales will I lose if I increase price? Conversely how much sales will I gain if I give a promotion?

2. Who is competing with me on the basis of price? We can identify the competing brand and focus our pricing and marketing actions to nullify their effect

3. MMM can also help us identify the elasticity at a key SKU level. This is particularly useful in optimizing pricing at an SKU level, helping gain sales and margins.

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Case study

An FMCG brand wanted to understand how to price individual SKUs, when price had to be taken up due to inflationary pressures on inputs. The question was that while price had to be increased overall by 5%, the SKU pricing had to be so optimized so that margin is maximized post pricing increase.

An MMM study revealed the overall price elasticity over the past few years. This meant that if the competition maintained or took a lower price increase, the brand would lose 7% of its value sales. By using an optimization technique – the SKU price increases were calibrated such that the lowest increase was for the most sensitive SKU and the highest for the least sensitive. This lead to the brand actually maintaining its value sales, in a highly charged price competitive market.

(RainMan is an expert MMM consultancy that has helped over a 100 brands with ROI, Promotional and pricing analytics over the last 15 years. Check out www.therainman.in for more details)

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