Digital platforms promise unmatched precision when it comes to reaching consumers with specific profiles. While these platforms typically deliver when the requirement is a behavior, accuracy often suffers when the objective is to reach consumers with specific attitudes or sentiments (e.g. pycho-graphic or attitudinal segments, intenders for a specific product or service, etc.) Challenges to their accuracy range from privacy regulation that limit what information can be garnered about a potential impression, to analytical limitations that lead to flawed qualification of those impressions even when data isn’t sparse, to complexities with the digital eco-system that lead to breakdowns in the portability of information from one platform to the next. In this breakout session, ENGINE shares insights on steps it has taken in the past several years to overcome these challenges, thus substantially improving the accuracy of delivery to attitudinal targets without comprising scale.