Prognosen

Einführung

In diesem Leitfaden werden die verschiedenen Verwendungsmöglichkeiten Prognose in der Google Ads- Manager API

Traffic-Prognose

Mit einer Traffic-Prognose können Sie Daten zu bisherigem Traffic und Umsatzchancen für zukünftige Impressionen, um bessere Segmentierung und Bündelung von Inventar.

Java

// Create the date range. Include the previous and next 7 days.
Interval interval =
    new Interval(
        Instant.now().plus(Duration.standardDays(-7)),
        Instant.now().plus(Duration.standardDays(7)));
DateRange dateRange = new DateRange();
dateRange.setStartDate(DateTimes.toDateTime(interval.getStart()).getDate());
dateRange.setEndDate(DateTimes.toDateTime(interval.getEnd()).getDate());

// Request the traffic data.
TrafficDataRequest trafficDataRequest = new TrafficDataRequest();
trafficDataRequest.setRequestedDateRange(dateRange);
trafficDataRequest.setTargeting(targeting);
TrafficDataResponse trafficData = forecastService.getTrafficData(trafficDataRequest);
    

Python


# Create a start date that's 7 days in the past and an end date that's 7 days
# in the future.
today = datetime.date.today()
start_date = today - datetime.timedelta(days=7)
end_date = today + datetime.timedelta(days=7)

# Create targeting.
targeting = {
    'inventoryTargeting': {
        'targetedAdUnits': [
            {
                'includeDescendants': True,
                'adUnitId': root_ad_unit_id,
            }
        ]
    }
}

# Request the traffic forecast data.
traffic_data = forecast_service.getTrafficData({
    'targeting': targeting,
    'requestedDateRange': {
        'startDate': start_date,
        'endDate': end_date
    }
})
    

PHP


// Create the date range. Include the previous and next 7 days.
$startDate = AdManagerDateTimes::fromDateTime(new DateTime('-7 day'))
    ->getDate();
$endDate = AdManagerDateTimes::fromDateTime(new DateTime('+7 day'))
    ->getDate();
$dateRange = new DateRange();
$dateRange->setStartDate($startDate);
$dateRange->setEndDate($endDate);

// Request the traffic forecast data.
$trafficDataRequest = new TrafficDataRequest();
$trafficDataRequest->setRequestedDateRange($dateRange);
$trafficDataRequest->setTargeting($targeting);
$trafficData = $forecastService->getTrafficData($trafficDataRequest);
    

C#


TrafficDataRequest trafficDataRequest = new TrafficDataRequest() {
    requestedDateRange = new DateRange() {
        startDate =
            DateTimeUtilities.FromDateTime(startDate, "America/New_York").date,
        endDate = DateTimeUtilities.FromDateTime(endDate, "America/New_York").date
    },
    targeting = new Targeting() {
        inventoryTargeting = new InventoryTargeting()
        {
            targetedAdUnits = new AdUnitTargeting[] {
                new AdUnitTargeting() {
                 adUnitId = rootAdUnitId,
                 includeDescendants = true
                }
            }
        }
    }
};
TrafficDataResponse trafficData =
    forecastService.getTrafficData(trafficDataRequest);
    

Ruby


# Create a start date that's 7 days in the past and an end date that's 7 days
# in the future.
today = ad_manager.today
start_date = today - 7
end_date = today + 7

# Create targeting.
targeting = {
  :inventory_targeting => {
    :targeted_ad_units => [
      {
        :include_descendants => true,
        :ad_unit_id => root_ad_unit_id
      }
    ]
  }
}

# Request the traffic forecast data.
traffic_data = forecast_service.get_traffic_data({
  :targeting => targeting,
  :requested_date_range => {
    :start_date => start_date.to_h, :end_date => end_date.to_h
  }
})
    

Verfügbarkeitsprognosen

Eine AvailabilityForecast gibt die maximale Anzahl der verfügbaren Einheiten mit für die die Werbebuchung gebucht werden kann. Diese Prognose ist analog zur Prüfung Inventar auf der Benutzeroberfläche.

Die Prognose enthält die verfügbaren, übereinstimmenden, möglichen, ausgelieferten und reservierten Einheiten. Er kann auch alle konkurrierenden Werbebuchungen und die verfügbaren Anzeigenblöcke enthalten. für jede Ausrichtung Aufschlüsselung je nachdem, welche Optionen AvailabilityForecastOptions. Standardmäßig wird keiner der beiden Werte in der Prognose berücksichtigt.

Die Targeting-Aufschlüsselungen umfassen die übereinstimmenden und verfügbaren Einheiten für jedes Targeting Kriterien. Diese Aufschlüsselungseinträge werden automatisch generiert gemäß dem Werbebuchungs-Targeting. Beispiel: Wenn eine Werbebuchung auf die Anzeigenblock-ID 123456 ausgerichtet ist, würde eine Aufschlüsselung in etwa so aussehen:

<targetingCriteriaBreakdowns>
  <targetingDimension>AD_UNIT</targetingDimension>
  <targetingCriteriaId>123456</targetingCriteriaId>
  <targetingCriteriaName>My Ad Unit Name</targetingCriteriaName>
   <excluded>false</excluded>
   <availableUnits>1000</availableUnits>
   <matchedUnits>2300</matchedUnits>
</targetingCriteriaBreakdowns>

Sie können Verfügbarkeitsprognosen sowohl für eine vorhandene als auch für eine potenzielle Werbebuchung ausführen. ein.

Vorhandene Werbebuchung

Sie können eine Verfügbarkeitsprognose für eine vorhandene Position anhand ihrer ID durchführen.

Java


  // Get the ForecastService.
  ForecastServiceInterface forecastService =
      adManagerServices.get(session, ForecastServiceInterface.class);

  // Get forecast for line item.
  AvailabilityForecastOptions options = new AvailabilityForecastOptions();
  options.setIncludeContendingLineItems(true);
  options.setIncludeTargetingCriteriaBreakdown(true);
  AvailabilityForecast forecast =
      forecastService.getAvailabilityForecastById(lineItemId, options);

  long matched = forecast.getMatchedUnits();
  double availablePercent = (forecast.getAvailableUnits() / (matched * 1.0)) * 100;
  String unitType = forecast.getUnitType().toString().toLowerCase();

  System.out.printf("%d %s matched.%n", matched, unitType);
  System.out.printf("%.2f%% %s available.%n", availablePercent, unitType);

  if (forecast.getPossibleUnits() != null) {
    double possiblePercent = (forecast.getPossibleUnits() / (matched * 1.0)) * 100;
    System.out.printf("%.2f%% %s possible.%n", possiblePercent, unitType);
  }

  System.out.printf(
      "%d contending line items.%n",
      forecast.getContendingLineItems() == null ? 0 : forecast.getContendingLineItems().length);
    

Python


  # Initialize appropriate service.
  forecast_service = client.GetService('ForecastService', version='v202408')

  # Set forecasting options.
  forecast_options = {
      'includeContendingLineItems': True,
      'includeTargetingCriteriaBreakdown': True,
  }

  # Get forecast for line item.
  forecast = forecast_service.getAvailabilityForecastById(
      line_item_id, forecast_options)
  matched = int(forecast['matchedUnits'])
  available_units = int(forecast['availableUnits'])

  if matched > 0:
    available_percent = (float(available_units) / matched) * 100.
  else:
    available_percent = 0

  contending_line_items = getattr(forecast, 'contentingLineItems', [])

  # Display results.
  print('%s %s matched.' % (matched, forecast['unitType'].lower()))
  print('%s%% %s available.' % (
      available_percent, forecast['unitType'].lower()))
  print('%d contending line items.' % len(contending_line_items))

  if 'possibleUnits' in forecast and matched:
    possible_percent = (int(forecast['possibleUnits'])/float(matched)) * 100.
    print('%s%% %s possible' % (possible_percent, forecast['unitType'].lower()))
    

PHP


      $forecastService = $serviceFactory->createForecastService($session);

      // Get forecast for line item.
      $options = new AvailabilityForecastOptions();
      $options->setIncludeContendingLineItems(true);
      $options->setIncludeTargetingCriteriaBreakdown(true);
      $forecast = $forecastService->getAvailabilityForecastById(
          $lineItemId,
          $options
      );

      // Print out forecast results.
      $matchedUnits = $forecast->getMatchedUnits();
      $unitType = strtolower($forecast->getUnitType());
      printf("%d %s matched.%s", $matchedUnits, $unitType, PHP_EOL);

      if ($matchedUnits > 0) {
          $availableUnits = $forecast->getAvailableUnits();
          $percentAvailableUnits = $availableUnits / $matchedUnits * 100;
          $possibleUnits = $forecast->getPossibleUnits();
          $percentPossibleUnits = $possibleUnits / $matchedUnits * 100;
          printf(
              "%.2d%% %s available.%s",
              $percentAvailableUnits,
              $unitType,
              PHP_EOL
          );
          printf(
              "%.2d%% %s possible.%s",
              $percentPossibleUnits,
              $unitType,
              PHP_EOL
          );
      }

      printf(
          "%d contending line items.%s",
          count($forecast->getContendingLineItems()),
          PHP_EOL
      );
    

C#


using (ForecastService forecastService = user.GetService<ForecastService>())
{
// Get forecast for line item.
AvailabilityForecastOptions options = new AvailabilityForecastOptions();
options.includeContendingLineItems = true;
options.includeTargetingCriteriaBreakdown = true;
AvailabilityForecast forecast =
    forecastService.getAvailabilityForecastById(lineItemId, options);

// Display results.
long matched = forecast.matchedUnits;
double availablePercent =
    (double) (forecast.availableUnits / (matched * 1.0)) * 100;
String unitType = forecast.unitType.ToString().ToLower();

Console.WriteLine("{0} {1} matched.\n{2} % {3} available.", matched, unitType,
    availablePercent, unitType);
if (forecast.possibleUnitsSpecified)
{
    double possiblePercent =
        (double) (forecast.possibleUnits / (matched * 1.0)) * 100;
    Console.WriteLine(possiblePercent + "% " + unitType + " possible.\n");
}

Console.WriteLine("{0} contending line items.",
    (forecast.contendingLineItems != null)
        ? forecast.contendingLineItems.Length
        : 0);
    

Ruby


  # Get the ForecastService.
  forecast_service = ad_manager.service(:ForecastService, API_VERSION)
  # Set forecasting options.
  forecast_options = {
    :include_contending_line_items => True,
    :include_targeting_criteria_breakdown => True,
  }

  # Get forecast for the line item.
  forecast = forecast_service.get_availability_forecast_by_id(
      line_item_id, forecast_options
  )

  unless forecast.nil?
    # Display results.
    matched = forecast[:matched_units]
    available_percent = forecast[:available_units] * 100.0 / matched
    unit_type = forecast[:unit_type].to_s.downcase
    puts '%.2f %s matched.' % [matched, unit_type]
    puts '%.2f%% of %s available.' % [available_percent, unit_type]
    puts '%d contending line items.' % forecast[:contending_line_items].size
    unless forecast[:possible_units].nil?
      possible_percent = forecast[:possible_units] * 100.0 / matched
      puts '%.2f%% of %s possible.' % [possible_percent, unit_type]
    end
  end
    

Die Ausgabe dieses Beispiels sieht in etwa so aus:

100 clicks matched.
2 contending line items.

Potenzielle Werbebuchung

Alternativ können Sie eine potenzielle Werbebuchung instanziieren und eine Prognose erstellen, ohne und dauerhaft speichern. Instanziieren Sie dazu ein lokales Werbebuchungsobjekt und legen Sie es im ProspectiveLineItem aus. Wenn Sie eine Werbetreibenden-ID festlegen, wird für die Prognose auch eine einheitliche Blockierung Regeln berücksichtigt.

Java


  // Get forecast for prospective line item.
  ProspectiveLineItem prospectiveLineItem = new ProspectiveLineItem();
  prospectiveLineItem.setAdvertiserId(advertiserId);
  prospectiveLineItem.setLineItem(lineItem);
  AvailabilityForecastOptions options = new AvailabilityForecastOptions();
  options.setIncludeContendingLineItems(true);
  options.setIncludeTargetingCriteriaBreakdown(true);

  AvailabilityForecast forecast =
      forecastService.getAvailabilityForecast(prospectiveLineItem, options);
    

Python


  prospective_line_item = {
      'lineItem': line_item,
      'advertiserId': advertiser_id
  }

  # Set forecasting options.
  forecast_options = {
      'includeContendingLineItems': True,
      # The field includeTargetingCriteriaBreakdown can only be set if
      # breakdowns are not manually specified.
      # 'includeTargetingCriteriaBreakdown': True,
      'breakdown': {
          'timeWindows': [
              now_datetime,
              now_datetime + datetime.timedelta(days=1),
              now_datetime + datetime.timedelta(days=2),
              now_datetime + datetime.timedelta(days=3),
              now_datetime + datetime.timedelta(days=4),
              end_datetime
          ],
          'targets': [
              {
                  # Optional, the name field is only used to identify this
                  # breakdown in the response.
                  'name': 'United States',
                  'targeting': {
                      'inventoryTargeting': {
                          'targetedAdUnits': [
                              {
                                  'includeDescendants': True,
                                  'adUnitId': root_ad_unit_id,
                              }
                          ]
                      },
                      'geoTargeting': {
                          'targetedLocations': [
                              {
                                  'id': '2840',
                                  'displayName': 'US'
                              }
                          ]
                      }
                  }
              },
              {
                  # Optional, the name field is only used to identify this
                  # breakdown in the response.
                  'name': 'Geneva',
                  'targeting': {
                      'inventoryTargeting': {
                          'targetedAdUnits': [
                              {
                                  'includeDescendants': True,
                                  'adUnitId': root_ad_unit_id,
                              }
                          ]
                      },
                      'geoTargeting': {
                          'targetedLocations': [
                              {
                                  'id': '20133',
                                  'displayName': 'Geneva'
                              }
                          ]
                      }
                  }
              }
          ]
      }
  }

  # Get forecast.
  forecast = forecast_service.getAvailabilityForecast(
      prospective_line_item, forecast_options)
    

PHP


      // Get forecast for prospective line item.
      $prospectiveLineItem = new ProspectiveLineItem();
      $prospectiveLineItem->setAdvertiserId($advertiserId);
      $prospectiveLineItem->setLineItem($lineItem);
      $options = new AvailabilityForecastOptions();
      $options->setIncludeContendingLineItems(true);
      $options->setIncludeTargetingCriteriaBreakdown(true);

      $forecast = $forecastService->getAvailabilityForecast(
          $prospectiveLineItem,
          $options
      );
    

C#


// Get availability forecast.
AvailabilityForecastOptions options = new AvailabilityForecastOptions()
{
    includeContendingLineItems = true,
    // Targeting criteria breakdown can only be included if breakdowns
    // are not speficied.
    includeTargetingCriteriaBreakdown = false,
    breakdown = new ForecastBreakdownOptions
    {
        timeWindows = new DateTime[] {
            lineItem.startDateTime,
            DateTimeUtilities.FromDateTime(tomorrow.AddDays(1),
                "America/New_York"),
            DateTimeUtilities.FromDateTime(tomorrow.AddDays(2),
                "America/New_York"),
            DateTimeUtilities.FromDateTime(tomorrow.AddDays(3),
                "America/New_York"),
            DateTimeUtilities.FromDateTime(tomorrow.AddDays(4),
                "America/New_York"),
            lineItem.endDateTime
        },
        targets = new ForecastBreakdownTarget[] {
            new ForecastBreakdownTarget()
            {
                // Optional name field to identify this breakdown
                // in the response.
                name = "United States",
                targeting = new Targeting()
                {
                    inventoryTargeting = new InventoryTargeting()
                    {
                        targetedAdUnits = new AdUnitTargeting[] {
                            new AdUnitTargeting()
                            {
                                adUnitId = rootAdUnitId,
                                includeDescendants = true
                            }
                        }
                    },
                    geoTargeting = new GeoTargeting()
                    {
                        targetedLocations = new Location[] {
                            new Location() { id = 2840L }
                        }
                    }
                }
            }, new ForecastBreakdownTarget()
            {
                // Optional name field to identify this breakdown
                // in the response.
                name = "Geneva",
                targeting = new Targeting()
                {
                    inventoryTargeting = new InventoryTargeting()
                    {
                        targetedAdUnits = new AdUnitTargeting[] {
                            new AdUnitTargeting()
                            {
                                adUnitId = rootAdUnitId,
                                includeDescendants = true
                            }
                        }
                    },
                    geoTargeting = new GeoTargeting()
                    {
                        targetedLocations = new Location[] {
                            new Location () { id = 20133L }
                        }
                    }
                }
            }
        }
    }
};
ProspectiveLineItem prospectiveLineItem = new ProspectiveLineItem()
{
    advertiserId = advertiserId,
    lineItem = lineItem
};
AvailabilityForecast forecast =
  forecastService.getAvailabilityForecast(prospectiveLineItem, options);
    

Ruby


  prospective_line_item = {
    :advertiser_id => advertiser_id,
    :line_item => line_item
  }

  # Set forecasting options.
  forecast_options = {
    :include_contending_line_items => true,
    # The field includeTargetingCriteriaBreakdown can only be set if breakdowns
    # are not mannually specified.
    # :include_targeting_criteria_breakdown => true,
    :breakdown => {
      # Break down forecast by day from start_time to end_time
      :time_windows => time_windows,
      # Break down forecast by any targeting configuration
      :targets => [
        {
          # Optional, the name field is only used to identify this breakdown in
          # the response.
          :name => 'United States',
          :targeting => {
            :inventory_targeting => targeting[:inventory_targeting],
            :geo_targeting => {
              :targeted_locations => [
                {
                  :id => '2840',
                  :display_name => 'US'
                }
              ]
            }
          }
        },
        {
          # Optional, the name field is only used to identify this breakdown in
          # the response.
          :name => 'Geneva',
          :targeting => {
            :inventory_targeting => targeting[:inventory_targeting],
            :geo_targeting => {
              :targeted_locations => [
                {
                  :id => '20133',
                  :display_name => 'Geneva'
                }
              ]
            }
          }
        }
      ]
    }
  }

  # Get forecast for the line item.
  forecast = forecast_service.get_availability_forecast(
      prospective_line_item, forecast_options)
    

Auslieferungsprognosen

Wenn Sie die Auslieferung mehrerer konkurrierender Werbebuchungen simulieren möchten, können Sie dies mit einer DeliveryForecast auszahlen

Vorhandene Werbebuchungen

Sie können eine Auslieferungsprognose für vorhandene Werbebuchungen anhand ihrer IDs ausführen.

Java


  // Get the ForecastService.
  ForecastServiceInterface forecastService =
      adManagerServices.get(session, ForecastServiceInterface.class);

  DeliveryForecastOptions options = new DeliveryForecastOptions();

  DeliveryForecast forecast =
      forecastService.getDeliveryForecastByIds(Longs.toArray(lineItemIds), options);

  for (LineItemDeliveryForecast lineItemForecast : forecast.getLineItemDeliveryForecasts()) {
    String unitType = lineItemForecast.getUnitType().toString().toLowerCase();
    System.out.printf("Forecast for line item %d:%n", lineItemForecast.getLineItemId());
    System.out.printf("\t%d %s matched%n", lineItemForecast.getMatchedUnits(), unitType);
    System.out.printf("\t%d %s delivered%n", lineItemForecast.getDeliveredUnits(), unitType);
    System.out.printf(
        "\t%d %s predicted%n", lineItemForecast.getPredictedDeliveryUnits(), unitType);
  }
    

Python


  # Initialize appropriate service.
  forecast_service = client.GetService('ForecastService', version='v202408')

  # Get forecast for line item.
  forecast = forecast_service.getDeliveryForecastByIds(
      [line_item_id1, line_item_id2], {'ignoredLineItemIds': []})

  for single_forecast in forecast['lineItemDeliveryForecasts']:
    unit_type = single_forecast['unitType']
    print('Forecast for line item %d:\n\t%d %s matched\n\t%d %s delivered\n\t'
          '%d %s predicted\n' % (
              single_forecast['lineItemId'], single_forecast['matchedUnits'],
              unit_type, single_forecast['deliveredUnits'], unit_type,
              single_forecast['predictedDeliveryUnits'], unit_type))


if __name__ == '__main__':
  # Initialize client object.
  ad_manager_client = ad_manager.AdManagerClient.LoadFromStorage()
  main(ad_manager_client, LINE_ITEM_ID_1, LINE_ITEM_ID_2)

    

PHP


      $forecastService = $serviceFactory->createForecastService($session);

      // Get forecast for the line items with no options set.
      $forecast = $forecastService->getDeliveryForecastByIds(
          [$lineItemId1, $lineItemId2],
          new DeliveryForecastOptions()
      );

      // Print out forecast results.
      $lineItemDeliveryForecasts = $forecast->getLineItemDeliveryForecasts();
      foreach ($lineItemDeliveryForecasts as $lineItemForecast) {
          $unitType = strtolower($lineItemForecast->getUnitType());
          printf(
              "Forecast for line item ID %d:%s",
              $lineItemForecast->getLineItemId(),
              PHP_EOL
          );
          printf(
              "    %d %s matched%s",
              $lineItemForecast->getMatchedUnits(),
              $unitType,
              PHP_EOL
          );
          printf(
              "    %d %s delivered%s",
              $lineItemForecast->getDeliveredUnits(),
              $unitType,
              PHP_EOL
          );
          printf(
              "    %d %s predicted%s",
              $lineItemForecast->getPredictedDeliveryUnits(),
              $unitType,
              PHP_EOL
          );
      }
    

C#


using (ForecastService forecastService = user.GetService<ForecastService>())
{
// Get a delivery forecast for the line items.
DeliveryForecastOptions options = new DeliveryForecastOptions();
options.ignoredLineItemIds = new long[]
{
};
DeliveryForecast forecast = forecastService.getDeliveryForecastByIds(new long[]
{
    lineItemId1,
    lineItemId2
}, options);

// Display results.
foreach (LineItemDeliveryForecast lineItemForecast in forecast
    .lineItemDeliveryForecasts)
{
    String unitType = lineItemForecast.unitType.GetType().Name.ToLower();
    Console.WriteLine("Forecast for line item {0}:",
        lineItemForecast.lineItemId);
    Console.WriteLine("\t{0} {1} matched", lineItemForecast.matchedUnits,
        unitType);
    Console.WriteLine("\t{0} {1} delivered", lineItemForecast.deliveredUnits,
        unitType);
    Console.WriteLine("\t{0} {1} predicted",
        lineItemForecast.predictedDeliveryUnits, unitType);
}

    

Ruby


  # Get the ForecastService.
  forecast_service = ad_manager.service(:ForecastService, API_VERSION)
  # Get forecast for the line item.
  forecast = forecast_service.get_delivery_forecast_by_ids(
      [line_item_id1, line_item_id2], nil)

  unless forecast.nil? || forecast[:line_item_delivery_forecasts].nil?
    forecast[:line_item_delivery_forecasts].each do |single_forecast|
      # Display results.
      unit_type = single_forecast[:unit_type]
      puts ('Forecast for line item %d:\n\t%d %s matched\n\t%d %s ' +
          'delivered\n\t%d %s predicted\n') % [single_forecast[:line_item_id],
          single_forecast[:matched_units], unit_type,
          single_forecast[:delivered_units], unit_type,
          single_forecast[:predicted_delivery_units], unit_type]
    end
  end
    

Die Ausgabe dieses Beispiels sieht in etwa so aus:

Forecast for line item 14678:
    100 clicks matched
    0 clicks delivered
    98 clicks predicted

Wenn Sie Werbebuchungen aus der Auslieferungssimulation ausschließen möchten, haben Sie folgende Möglichkeiten: indem Sie ihre IDs in der DeliveryForecastOptions.

Potenzielle Werbebuchungen

Ähnlich wie bei den Verfügbarkeitsprognosen können Sie Auslieferungsprognosen Elemente, die nicht persistent sind. Verwenden Sie dazu ProspectiveLineItem-Objekte in der ForecastService.getDeliveryForecast .

Berichte für zukünftige Umsätze

Bericht für zukünftige Umsätze die Verfügbarkeit von Impressionen für Ihre Google Ad Manager-Netzwerk, damit Sie Ihre Umsätze und Umsatzrate zu erzielen. Berichte für zukünftige Umsätze können über die ReportService erstellt werden.

FAQ

Ich habe viele Werbebuchungen, für die ich die Verfügbarkeit prognostizieren möchte. Kann ich mehrere Prognosen in einer Anfrage ausführen?
Nein. Sie müssen für jede Zeile eine separate Anfrage für die Verfügbarkeitsprognose stellen oder potenzielle Werbebuchung aus.
Ich habe mehrere Prognosen ausgeführt und erhalte jetzt EXCEEDED_QUOTA Fehler. What gives?
Prognosen sind rechenintensiv und das Kontingentsystem sorgt dafür, dass der Dienst zuverlässig ist. Sie können einfach abwarten und alle Prognosen wiederholen, die Kontingentfehler.
Wodurch werden NO_FORECAST_YET- oder NOT_ENOUGH_INVENTORY-Fehler verursacht?
Prognosen werden basierend auf dem Traffic Ihres Netzwerks erstellt . Manchmal sind nicht genügend historische Daten vorhanden, um eine Prognose durchzuführen. Weitere Informationen Details zu diesen Fehlern erhalten Sie in der ForecastError Dokumentation.
Was ist eine AlternativeUnitTypePredict?
Manchmal ist es hilfreich zu wissen, welches Inventar noch verfügbar ist. Für bei der Prognose für eine CPC-Zeile Artikel, der alternative Anzeigenblocktyp Prognosen enthält Informationen zur Anzahl der Impressionen.
Ich habe weitere allgemeine Fragen zu Ad Manager-Prognosen.
Prüfen, ob die Inhalte durch das Produkt abgedeckt sind FAQs oder in der Entwickler-App Forum.