Conjoint Analysis is a technique used to assess the different weights individuals place on the variables presented to them in a given purchase situation. A conjoint study usually involves showing respondents product profiles and asking them to indicate (in a variety of ways) how much they like or prefer these alternative product profiles. Statistics are then used to work out the contribution that each product attribute is making to the overall likeability.

• Self Explicated Conjoint
• Discrete Choice
• Ratings Based

Total Unduplicated Reach and Frequency Analysis is used to identify a subset of items that, when taken together, maximizes the net level of consumer interest in a superset of choices. Example: you've just tested consumer interest in 10 proposed new ice cream flavors but marketing constraints only allow you to introduce three flavors. TURF can identify the three flavors that, taken together, generate the highest net level of interest for the total line.

Gap Analysis can help determine the "Gap" or difference between various attributes (Eg. Importance, Satisfaction etc.) in a visible format.

The Trend Analysis module allows you to plot aggregated response data over time. This is especially valuable, if you are conducting a long running survey and would like to measure differences in perception and responses over time.