New Product Launches -- Tobacco

In the last year or so, I’ve had the chance to monitor several product extension launches in the cigarette industry; all the big players have made some moves. For example, Marlboro has sequentially launched several Special Blend sub-brands, while Newport has successfully launched a non-menthol brand. Despite the different success levels we observe in terms of market share for these launches, all of them share a remarkable similarity in terms of their share diffusion in the market. I want (briefly) to look at some of the implications of this fact as it relates to the cigarette industry.

The basic Bass model suggests that the volume (share) of a new product is determined by the interaction of two effects. The first is the innovation/advertising effect, which is taken to drive people to experiment with the product quickly. The second effect is the imitation/word-of-mouth effect, which is assumed to spread the desire to try the product over time.

The sales as a function of time can be expressed:

Nt = Nt-1 + p(m-Nt-1) + q(Nt/m)(m- Nt-1)

Where N is the number of units sold (or, scaled appropriately, market share), m is the total market size for the product, p is the innovative/advertising effect, and q is the imitation/word-of-mouth effect. Typical values for p are said to be around 0.03 and for q around 0.4.

You might be able to see that the last term on the right hand side is the difference term that we see in simple models of population growth with carrying capacity, used to model the size of a colony of bacteria in a Petri dish, for example. So, the “q” term is the logistic or organic growth and the “p” term is the exponential or advertising-related growth. And overall volume is determined by the balance between these two effects.

So far, so good. But here is where it gets interesting. Below are a pair of simulated new product launches, the first from a product with typical coefficients and the second with coefficients that have been calibrated to yield weekly changes in volume that mimic those of the new products in the cigarette industry. Check out the graphs at the top of the page to see what I mean.

The overriding fact of all the new product introductions was a peak in the share change that happens in week #2, and the share changes generally fell to near zero by week #4 (though I haven’t modeled the drift that some products display subsequently). But the coefficients as calibrated are very far outside what is considered typical: the “p” value is 0.3 (up from 0.03) and the “q” value is 0.8 (as compared to a typical value of 0.4).

Now, these numbers are merely the result of a quick and dirty calibration, but they suggest the possibility that cigarettes are an unusual industry with respect to new product introduction.