I am looking to estimate the price premium that can be charged for a clients new product vs. an existing product they already have on the market.
To do this I have conducted sensitivity simulations using randomised first choice method, varying price of one product at a time while keeping all other products prices constant at the market average, to generate a price demand curve for each brand.
What I wanted to do was compare the curves for the two different products and observe the price point at which the new product obtains the same share % as the existing product does at the actual price it is sold at in the market.
However, the results I am getting do not allow me to do this as the model suggests share % is so high for the new product and so low for the existing product, that there is no overlap between the two brands curves - i.e. even if existing product was sold at a very low price and new product at a very (unrealistically) high price, the simulator still makes out the new product would have higher share. (also, just to note that even before entering the new product into the simulation, the existing product receives very low share which is not reflective of its performance in the market).
I think this problem may be down to the fact that all existing products in the market are very similar, with little to differentiate them other than brand, and the new product has quite a few innovative features that are different to everything in the market at present. While it is sensible that people would pay more for the new product, I think the extent of the premium is being exaggerated by the model.
I have looked into a few solutions for this. Firstly, changing the sim method to shares of preference which doesn't seem to have much of an effect. Secondly, I have looked at changing the exponent from the default value of one to flatten shares. This does help, but I feel its a little arbitrary... Finally, I wonder if because the new product is so different to the others on the market it might actually make more sense to do a purchase likelihood simulation rather than put it in a competitive scenario, and try to visualise the pricing threshold that way.
Any advice on this issue would be much appreciated. Has anyone experienced a similar problem and how did you overcome it? Based on the scenario I have explained, what in your view is better - to change the exponent and keep simulation within a competitive scenario - or to use the purchase likelihood method as an alternative due to the new products lack of similarity to existing competitors in the product category?