Lookalike Audience Modeling (LAM) is a marketing analytics methodology used to ultimately generate more leads and increase their conversions. The algorithm discovers similarities between internet users based upon the domain level URLs that they've visited. After a dimensionality reduction step through SVD, we calculate cosine-similarities between users of interest and users at large, based on internet behavior during a fixed period of time. We show that the recall rate is over 90%. We also present clients' key performance indicators.