list(filterSetName, pageSize=None, pageToken=None, x__xgafv=None)

Lists all metrics that are measured in terms of number of bids.

Args:
filterSetName: string, Name of the filter set that should be applied to the requested metrics. For example: - For a bidder-level filter set for bidder 123: `bidders/123/filterSets/abc` - For an account-level filter set for the buyer account representing bidder 123: `bidders/123/accounts/123/filterSets/abc` - For an account-level filter set for the child seat buyer account 456 whose bidder is 123: `bidders/123/accounts/456/filterSets/abc` (required)
pageSize: integer, Requested page size. The server may return fewer results than requested. If unspecified, the server will pick an appropriate default.
pageToken: string, A token identifying a page of results the server should return. Typically, this is the value of ListBidMetricsResponse.nextPageToken returned from the previous call to the bidMetrics.list method.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # Response message for listing the metrics that are measured in number of bids.
"bidMetricsRows": [ # List of rows, each containing a set of bid metrics.
{ # The set of metrics that are measured in numbers of bids, representing how many bids with the specified dimension values were considered eligible at each stage of the bidding funnel;
"bids": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids that Ad Exchange received from the buyer.
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"bidsInAuction": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids that were permitted to compete in the auction.
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"billedImpressions": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids for which the buyer was billed. Also called valid impressions as invalid impressions are not billed.
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"impressionsWon": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids that won the auction.
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"measurableImpressions": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids for which the corresponding impression was measurable for viewability (as defined by Active View).
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"reachedQueries": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids that won the auction and also won the mediation waterfall (if any).
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
"rowDimensions": { # A response may include multiple rows, breaking down along various dimensions. Encapsulates the values of all dimensions for a given row. # The values of all dimensions associated with metric values in this row.
"publisherIdentifier": "A String", # The publisher identifier for this row, if a breakdown by [BreakdownDimension.PUBLISHER_IDENTIFIER](https://developers.google.com/authorized-buyers/apis/reference/rest/v2beta1/bidders.accounts.filterSets#FilterSet.BreakdownDimension) was requested.
"timeInterval": { # An interval of time, with an absolute start and end. # The time interval that this row represents.
"endTime": "A String", # The timestamp marking the end of the range (exclusive) for which data is included.
"startTime": "A String", # The timestamp marking the start of the range (inclusive) for which data is included.
},
},
"viewableImpressions": { # A metric value, with an expected value and a variance; represents a count that may be either exact or estimated (for example, when sampled). # The number of bids for which the corresponding impression was viewable (as defined by Active View).
"value": "A String", # The expected value of the metric.
"variance": "A String", # The variance (for example, square of the standard deviation) of the metric value. If value is exact, variance is 0. Can be used to calculate margin of error as a percentage of value, using the following formula, where Z is the standard constant that depends on the preferred size of the confidence interval (for example, for 90% confidence interval, use Z = 1.645): marginOfError = 100 * Z * sqrt(variance) / value
},
},
],
"nextPageToken": "A String", # A token to retrieve the next page of results. Pass this value in the ListBidMetricsRequest.pageToken field in the subsequent call to the bidMetrics.list method to retrieve the next page of results.
}

Ad Exchange Buyer API II . bidders . filterSets . bidMetrics

Instance Methods

Method Details