The problem with dynamic pricing: when women pay over 80 percent more

The sociology of gender sees itself as a pioneering when it comes the equality of man and women. But this kind of enlightenment has had relatively little effect on trade so far. Here the motto is still: blue is cheaper than pink. As soon as demographic data is used in dynamic pricing, price setting becomes discriminatory.

When dynamic pricing becomes unfair

If the provider sets the price with the dynamic pricing model, there is always the danger that you will offend certain groups. Dynamic pricing means adjusting the price according to lot of different factors, e.g. distance from warehouse, amount ordered, or demographic data, like age, sex, or nationality.

Some factors are a simple cost-profit calculation, which can be explained by supply and demand. But the use of demographic data is often discriminatory. When profit is the main focus, you want to get the most out of each demographic, without have to takeethical or moral questions into account – big data makes it possible.

Gender pricing – a prime example

Particularly when looking at gender, you can see that pricing favours one side. Women pay up to 90 more for almost identical products. The gap is especially huge with beauty products. Why? The argument is that female products come with higher consultation expenditure – but how do online shops justify such a large price difference?

Some branches have been familiar with accusations of gender pricing for a long time. Hairdressers keep having to explain why the price of a hair cut isn’t based on hair length, but biological sex. The state of California and the city of New York have now forbidden gender pricing.

Legitimate in some cases

This is not a new problem: Back in 2000 Amazon.com upset customers with difference prices. Back then, a user deleted his cookies and entered the Amazon site as a ‘new’ customer…suddenly DVDs cost up to 4 US dollars less. Are these kids of price difference justifiable?

In some cases – yes. Discounts for loyal customers for instance, can be viewed as a reward for their loyalty. Raising prices for repeat offenders when it comes to returns also seems to be legitimate, as these customer consciously and actively create costs.

Price optimisation vs. price discrimination

Especially for onlineshops swimming in big data, dynamic pricing is the perfect tool for optimising the price and getting the most out of it individually. But if you take demographic data, like age or sex, into account when pricing, you should be prepared for accusations of discrimination.

What can customers do? Women should take a look at the ingredients in equivalent products “for men” and use them. Difference prices for the product, which can happen with cookies ofr instance, are not easy to manipulate. The Incognito mode in modern browsers does help you to find out what the prices are like for people not being tracked by cookies.