Which of these definitions best describes what data-driven attribution models can do?
Data-driven attribution models help you get a more accurate picture of your conversion by analyzing interactions in your campaigns and creating a model for distributing conversion credit based on where an interaction occurs in a conversion path.
Data-driven attribution models help you to monitor the performance of keywords and product groups. These models adjust bids to achieve the highest number of conversions, the greatest amount of revenue, the best position, or highest number of clicks your campaign budgets allow.
Data-driven attribution models enable you set and manage the budget for groups of campaigns and enable a budget bid strategy to allocate the money and adjust bids.
Data-driven attribution models help you determine which ads within an ad group are best at helping you to achieve your conversion goals by starting all the ads at the same time and displaying them evenly.