A group for whom we believe we will see the maximum effect is deliberately chosen. For example, a new menu system would be tested more effectively for short-term memory requirements on an elderly user group who are more likely to have some short-term memory loss, rather than on a younger user group. Targeted user groups increase effect in the noise-effect-number triangle and so increase statistical power. However, targeting can be misleading if you are not careful as the targeted user group may not be representative of the full range of users who are likely to use the system, therefore generalisation can be difficult.
Also known as targeted user