Decades of social and behavioral science research has established the importance of interactions between different factors in influencing human behavior. However, interactions are too often overlooked in retail analytics when examining consumer behavior. One exception where the importance of interactions has been embraced in retail analytics is product endorsements. Research has clearly shown that product endorsements have an effect on buying behavior. It has also shown that endorsements by friends or family members are more effective than endorsements from experts (i.e., an interaction effect). This is why companies want you to endorse your new favorite toothbrush on Facebook more than they want 9 out of 10 doctors to do it. In this talk I discuss the importance of interaction effects within retail analytics, including an example of how to statistically test and examine potential interaction effects.