Statistically Significant is short for “Statistically Significant Difference” and is relevant when the Sig Testing flags a pair of numbers as statistically likely to be different from each other in the larger population.

Syndicated research is research which is conducted and funded by a market research firm but not for any specific client. The result of such research is often provided in the form of reports, presentations, raw data, etc., and is made available in the open market for anyone to purchase.

TDI stands for “Telephone Depth Interviews.” These are qualitative one-on-one interviews that are specifically conducted via telephone, in a way where follow-up questions can be asked and responses are free-form.

Top Box refers to the response to a scale question (like 1-5, 1-7, or 0-10) where there is a highest rating point, or the “top box.” This is generally reported as the % of respondents who selected that response.

A Tracker study is one that is repeated and allows comparisons of the same measures over time. Some trackers are “point in time” studies and are conducted annually, quarterly, or monthly, depending on the desired cadence, and data collection pauses between waves; and some trackers are “continual” studies and are conducted on an ongoing basis (continually collecting data without stopping between waves).

Online material such as comments, profiles photographs that is produced by end users.

UX stands for User Experience, which refers to the overall experience of a person using a product or service, including the design, functionality, and ease of use. It encompasses the emotions, attitudes, and perceptions that a person has while interacting with a product or service. In market research, UX research is used to understand how people interact with a product, website, or service, and to identify areas for improvement. It can involve usability testing, where users are asked to perform specific tasks while researchers observe and record their interactions. It can also include surveys, interviews, and other methods to gather qualitative and quantitative data on users’ attitudes and perceptions.

When the responding sample doesn’t match the population in question (for example, if the population is equal parts Blue: 33.3%, Red: 33.3%, and Yellow: 33.3%, but the responding sample has more Blue than that — Blue: 45%, Red: 11.7%, Yellow: 33.3%), in order to make projections and assumptions about the larger population based on these responses, we want to make sure that we’re not under-representing the Reds or over-representing the Blues, so we “weight” the responses to match the “weight” of the population. In this case, each Blue response will count as 0.74 responses, Red responses will count as 2.84 responses, and Yellow responses will simply count as 1 response, resulting in a balance that matches the population: Blue: 45%*0.74=33.3%, Red: 11.7%*2.84=33.2%, and Yellow: 33.3%