According to Consumer Reports in this article Today article, for many consumer products there is very little difference between private-label or store brands and the national brands they compete with, so consumers should not be afraid to try them. In a 2011 study, McKinsey determined that the willingness to try private-label products depended on the respondents’ confidence in the economy, but frugality was becoming entrenched. In September 2011, 45% of the respondents said they were looking for ways to save money and their private label experiences had been generally positive. I won’t debate their point about trying private-label products. Instead I will focus on how private-label products affect the price setting process. Whether you are setting pricing strategy for the name brand or the private-label product, it is critical that you make data-driven decisions, not emotional decisions. In other words, don’t guess – do the math and use the analytics.
There have been countless studies of the impact of private-label products over the years. I have completed a couple of those studies myself. One of the common themes that come from those studies is that there is a distribution of switching points. Customers will switch at different price points for different reasons. For example, some customers are very price sensitive and will switch from name brand to private label for a 10% price reduction. Other customers will not switch for a 75% price difference. Why the differences? Here are some reasons:
- Not all customers are equally price sensitive
- If the risk of a poor result from the private-label product is high, small price differences are not worth the risk
- If the product is a critical component of the buyer’s products or processes, the risk of failure will be higher
- There are multiple sources of value that can be different across customers
- The functional value of the product attributes
- The packaging and aesthetic value
- The perception or prestige value. “My image or the image of my company would be lower if I were using off-brand products”
- The service value of the provider of the product
- The value of the sales person to customers
- The value of consistency across a range of products that a name brand might offer that private label does not
- Others
With all those variables, it is critical for the pricing practitioner to 1) try to quantify the differences in value of the brand vs. private label, and 2) quantify the impact on profit of various prices vs. volumes.
There are a number of approaches that can be used to estimate the value differences of brand vs. private label. One approach to be strongly considered is choice-based conjoint analysis. With a sample of customers and prospective customers, the conjoint would offer a series of choices that involve different trade-offs the customer can make in their product selection decision. More specifically the customer would choose between the branded product with a list of features and a specified price, a private label product with a list of features and a specified price, and perhaps a third brand with its own list of attributes and price. With a controlled assortment of different scenarios in which the customer makes choices between products with varying attributes and prices, the relative values of each attribute can be estimated statistically. A curve of the relative price points at which customers will switch can also be estimated. A conjoint analysis is not the only option, but it can be very useful in the important step of objectively estimating the value of a product and its attributes, rather than relying on gut feel and anecdotes.
Equally important to estimating value is quantifying the impact on profit at a range of prices and volumes. For example, if your company makes the branded product and your analysis indicates 20% of your customers would switch to private label for a 10% price cut, what would happen if you matched that price cut? Well if you currently generate 40% margins on your products and you drop your price 10%, at the same unit volume your total margin dollars would decrease by 25%. However, if you did nothing and all 20% of those customers switched to private label, your total margin dollars would decrease by 20%, better than if you lowered prices. Neither scenario is great, but matching prices would make you worse off.
I am not suggesting that when a private-label product enters a market the best course of action is to do nothing and let the volume go. The answer is to build your strategy when you have the data. Identify and quantify the sources of value, and include those values in your messaging. Create profiles of the customers on the low end of the switching curve and offer promotions tailored to them. Compete for the value-minded, less price-sensitive customers with the services and attributes they want. Finally, simulate different scenarios of volumes and price points so you understand how your choices will impact your P&L.
A very well written article. The problem arises when companies have all the data, but still end up making gut based decisions because there is no way to quantify the data. I see very few companies using conjoint analysis techniques..
Agreed. Perhaps we can change that by reminding everyone there is a better way.