Revenue Index Curves: Maximizing Gross Sales through Pricing Research
Posted by Vovici Blog on Tue, Mar 08, 2011
You’ve conducted a pricing survey and have come up with a list of prices and purchase likelihoods at each price (see Willingness to Pay, Monadic Price Testing, Sequential Monadic Testing and Conjoint Analysis for techniques to get you there). While there are dozens of pricing strategies for a firm to follow, from maximizing market share to maximizing profitability, maximizing gross sales is a common strategy.
For sake of illustration, let’s look at the following fabricated data about likelihood to buy a tablet computer at different prices:
According to this data, to maximize unit sales, a tablet computer should be priced at $300. At lower prices, presumably, consumers think the table computer is too underpowered to be useful.
What’s the best price to maximize gross sales instead?
For this, we multiply each price point by its corresponding purchase likelihood, then divide by the maximize price we find, to create a revenue index.
Performing this analysis shows that $500 produces the greatest gross sales. Lowering the price to $400 actually produces only 93% of the gross sales at $500, while raising the price to $600 generates under two-thirds of the gross sales at $500.
The next question to ask is about maximizing profits. This becomes more complex, requiring accounting for channel margin, fixed costs, variable costs and – for products as opposed to services – economies of scale at different manufacturing volumes. Such models are highly specific to each firm, its channel and its capabilities.
For the simpler question of maximizing gross sales, calculating a revenue index is a basic but useful analytical technique.