As online research becomes more integrated into the everyday methodology of industries across the board, we find the need to target for very specific groups of people. Whether we need to target people who use a specific brand of antiperspirant or those with a rare form of cancer, some rare populations can be almost impossible to find on an online access panel. While the use of additional sample sources increases the feasibility for some of these projects there are still valuable untapped resources that could make a world of difference in the success of a project. The great advantage we have in the struggle find these rare populations is that people with similar lifestyles or experiences tend to cluster—often sharing similar beliefs or banding together based on a commonality such as a disease, an interest in the same model car, or alumni from the same college. The practice of “Snowball sampling” (identifying one person who fits the profile and asking that person to “spread the word” within their community) has been a technique criticized by some, who have feared it will introduce unacceptable biases. But with average project incidences continuing to fall, it may be time to take another look. SSI will conduct side-by-side tests to compare data from snowball sample to both online access panels and intercept sample. SSI will also test to find the optimal combination of sources and sample types (panel, snowball, river, etc.) yielding the most sound data available from an online sample frame. Topics for this test will include consumer goods, healthcare, known offline benchmarks and more. The findings will help researchers in all industries create methodologically sound sampling plans as they have in the past with the possible introduction of a broader reach made possible by the use of snowball sampling.