Abstract: To determine an impression metric for an organization, a server device generates a statistical model for estimating the impression metric using machine learning techniques. The server device obtains training data for the statistical model by randomly selecting geographic locations within a geographic area and determining the number of users eligible to receive a particular type of advertisement for each randomly selected geographic location. For example, a user may be deemed eligible when displaying the geographic location via a mapping application. When an organization requests an estimate of a number of impressions for an advertising campaign, the server device applies data included in the request (e.g., the time period for the advertising campaign, the number of organization locations, identifiers for the organization locations such as geographic coordinates or an address, etc.) to the statistical model to estimate an impression metric for the organization.

Abstract: To determine an impression metric for an organization, a server device generates a statistical model for estimating the impression metric using machine learning techniques. The server device obtains training data for the statistical model by randomly selecting geographic locations within a geographic area and determining the number of users eligible to receive a particular type of advertisement for each randomly selected geographic location. For example, a user may be deemed eligible when displaying the geographic location via a mapping application. When an organization requests an estimate of a number of impressions for an advertising campaign, the server device applies data included in the request (e.g., the time period for the advertising campaign, the number of organization locations, identifiers for the organization locations such as geographic coordinates or an address, etc.) to the statistical model to estimate an impression metric for the organization.

Abstract: To measure the increase in location awareness for an organization's locations using a map display, a server device identifies each of the locations belonging to an organization and applies a random filter to select a subset of the locations. An indication of the organization is presented on a map display at each of the selected organization locations within the subset. When an indication of the organization location is presented to a user a threshold number of times, an icon such as a question mark may be presented in place of the indication at the organization location. The icon may provide a link to a location awareness survey which may request that the user identifies the organization corresponding to the location. Several users may receive the location awareness survey for the same organization location and the users' answers may then be analyzed to determine a location awareness metric.

Abstract: To measure the increase in location awareness for an organization's locations using a map display, a server device identifies each of the locations belonging to an organization and applies a random filter to select a subset of the locations. An indication of the organization is presented on a map display at each of the selected organization locations within the subset. When an indication of the organization location is presented to a user a threshold number of times, an icon such as a question mark may be presented in place of the indication at the organization location. The icon may provide a link to a location awareness survey which may request that the user identifies the organization corresponding to the location. Several users may receive the location awareness survey for the same organization location and the users' answers may then be analyzed to determine a location awareness metric.