openapi: 3.1.0 info: title: Media Planning description: "## Overview\n\nMedia Planning API can help Media Planners understand the reach and ROI that LinkedIn can offer to their client. It allows them to make budget allocation recommendations with confidence and know how to improve the results, even before spending the first dollar. Media Planning API helps Media Planners make that decision by giving the forecasted reach, impressions (and more in future, like clicks, leads) curve over the budget, based on inputs provided like targeted audience, campaign start/end date and more.\n\nNote: This is a private API that is available to qualified developers who meet additional criteria for access. To learn more about eligibility qualifications and how to request access, please see the [FAQ](https://learn.microsoft.com/en-us/linkedin/marketing/lms-faq#how-do-i-get-access-to-media-planning-api-product). If you wish to apply for access, please submit a [Zendesk support ticket](https://linkedin.zendesk.com/).\n\n## Permissions\n\nMedia Planning API requires a [3-legged OAuth](https://learn.microsoft.com/en-us/linkedin/shared/authentication/authorization-code-flow) member token and your developer application needs to be provisioned with the Media Planning API product. Once you have been approved to access, you can use any valid member access token associated with the authenticated user with any valid scope permissions for member authentication. If there is no valid member token for the relevant user from any previous integration, we recommend using the bare minimum scope permissions like `r_ads` which will be required to fetch authenticated user's ad accounts. \nNote: This API is application-specific; hence, explicit member consent is not required. Any valid member access token associated with the authenticated user can be used, and you do not need to add any additional permission in the scope of your Oauth2 flow for authorization.\n\nThis collection aims to focus on different Media Planning use cases and should be used with the **media-planning-env-versioning** environment.\n\n\\--All requests for the Media Planning API collection are in the Restli 2.0 format--" version: 1.0.0 servers: - url: https://api.linkedin.com description: LinkedIn Marketing API Production Server tags: - name: Ad Targeting Entities description: 'The LinkedIn ads platform allows advertisers to target different types of audiences on the professional network. The two core concepts for targeting are facets and entities. Facets are high-level categories of the types of targeting available to you. Facets contain multiple entities which are the specific demographic values within that facet. For example, Industries is a facet. Specific industries such as Computer Software, Biotechnology, and Telecommunications are entities within the Industries facet. Use facets to narrow down your intended audience. Refer to [Targeting Criteria Facet URNs](https://learn.microsoft.com/en-us/linkedin/shared/references/v2/ads/targeting-criteria-facet-urns?view=li-lms-2023-09) for the list of available facets and their URNs. The `adTargetingFacets` API returns available targeting facets. Once you''ve identified the facet type(s) you''d like to target, you can fetch their entity values. Use the `adTargetingEntities` API to fetch available options for each facet type. To learn more, see [Ad Targeting Entities](https://learn.microsoft.com/en-us/linkedin/shared/references/v2/ads/adtargetingentities?context=linkedin%2Fmarketing%2Fcontex&view=li-lms-2023-09). ### Permissions Any application approved for the LinkedIn Marketing API Program can make these API calls using any 3-legged access token. No additional permissions need to be requested during the OAuth flow.' - name: Fetch Media Plan description: Media Planning API can help Media Planners understand the reach and ROI that LinkedIn can offer to their client. It allows them to make budget allocation recommendations with confidence and know how to improve the results, even before spending the first dollar. Media Planning API helps Media Planners make that decision by giving the forecasted reach, impressions (and more in future, like clicks, leads) curve over the budget, based on inputs provided like targeted audience, campaign start/end date and more. paths: /adTargetingFacets: get: tags: - Ad Targeting Entities summary: LinkedIn Get a List of Available Ad Targeting Facets parameters: - name: LinkedIn-Version in: header schema: type: string example: '{{insert_version}}' - name: X-Restli-Protocol-Version in: header schema: type: string example: 2.0.0 responses: '200': description: OK headers: Content-Type: schema: type: string example: application/json X-RestLi-Protocol-Version: schema: type: string example: 2.0.0 Date: schema: type: string example: Tue, 22 Aug 2023 01:34:20 GMT Transfer-Encoding: schema: type: string example: chunked Connection: schema: type: string example: keep-alive X-Li-Fabric: schema: type: string example: prod-lva1 X-Li-Pop: schema: type: string example: prod-lva1-x X-LI-Proto: schema: type: string example: http/1.1 X-LI-UUID: schema: type: string example: AAYDeP50GndIRiDUNqZFNA== Set-Cookie: schema: type: string example: lidc="b=VB52:s=V:r=V:a=V:p=V:g=3817:u=1714:x=1:i=1692668060:t=1692748247:v=2:sig=AQEExcZ9-g2kMBwFJV4hRYBz8S5UhRNr" X-LI-Route-Key: schema: type: string example: '"b=VB52:s=V:r=V:a=V:p=V:g=3817:u=1714:x=1:i=1692668060:t=1692748247:v=2:sig=AQEExcZ9-g2kMBwFJV4hRYBz8S5UhRNr"' content: application/json: schema: $ref: '#/components/schemas/GetAListOfResponse200' examples: default: $ref: '#/components/examples/GetAListOfResponse200Example' operationId: getGetAListOf x-microcks-operation: dispatcher: FALLBACK dispatcherRules: '{}' delay: 0 /adTargetingEntities: get: tags: - Ad Targeting Entities summary: LinkedIn Get Bing Geo Locations Using Search Typeahead parameters: - name: LinkedIn-Version in: header schema: type: string example: '{{insert_version}}' - name: X-Restli-Protocol-Version in: header schema: type: string example: 2.0.0 - name: q in: query schema: type: string example: typeahead - name: query in: query schema: type: string example: united%20states - name: facet in: query schema: type: string example: urn%3Ali%3AadTargetingFacet%3Alocations - name: queryVersion in: query schema: type: string example: QUERY_USES_URNS - name: start in: query schema: type: integer example: '0' - name: count in: query schema: type: integer example: '10' responses: '200': description: OK headers: Content-Type: schema: type: string example: application/json X-RestLi-Protocol-Version: schema: type: string example: 2.0.0 Date: schema: type: string example: Tue, 22 Aug 2023 19:18:41 GMT X-Li-Fabric: schema: type: string example: prod-lor1 Transfer-Encoding: schema: type: string example: chunked Connection: schema: type: string example: keep-alive X-Li-Source-Fabric: schema: type: string example: prod-ltx1 X-Li-Pop: schema: type: string example: prod-ltx1-x X-LI-Proto: schema: type: string example: http/1.1 X-LI-UUID: schema: type: string example: AAYDh9zhVpvVljNr6Bd2Lw== Set-Cookie: schema: type: string example: lidc="b=OB52:s=O:r=O:a=O:p=O:g=3439:u=1715:x=1:i=1692731921:t=1692736001:v=2:sig=AQG3v245ve1coreRexh5O2dpV2Gnfhpa" X-LI-Route-Key: schema: type: string example: '"b=OB52:s=O:r=O:a=O:p=O:g=3439:u=1715:x=1:i=1692731921:t=1692736001:v=2:sig=AQG3v245ve1coreRexh5O2dpV2Gnfhpa"' content: application/json: schema: $ref: '#/components/schemas/GetBingGeoLocationsResponse200' examples: default: $ref: '#/components/examples/GetBingGeoLocationsResponse200Example' operationId: getGetBingGeoLocations x-microcks-operation: dispatcher: FALLBACK dispatcherRules: '{}' delay: 0 /mediaPlanning: post: tags: - Fetch Media Plan summary: LinkedIn Forecast Avg Lifetime Frequency requestBody: content: application/json: schema: $ref: '#/components/schemas/ForecastAvgLifetimeFrequencyRequest' parameters: - name: Authorization in: header schema: type: string example: Bearer {{Access_Token}} - name: X-RestLi-Protocol-Version in: header schema: type: string example: 2.0.0 - name: Linkedin-Version in: header schema: type: string example: '{{insert_version}}' - name: action in: query schema: type: string example: forecastImpressions responses: undefined: content: text/plain: examples: default: $ref: '#/components/examples/ForecastAvgLifetimeFrequencyResponseundefinedExample' schema: $ref: '#/components/schemas/ForecastAvgLifetimeFrequencyResponseundefined' operationId: postForecastAvgLifetimeFrequency x-microcks-operation: dispatcher: FALLBACK dispatcherRules: '{}' delay: 0 components: schemas: GetAListOfResponse200: type: object properties: paging: type: object properties: start: type: integer count: type: integer links: type: array items: {} elements: type: array items: type: object properties: entityTypes: type: array items: type: string facetName: type: string availableEntityFinders: type: array items: type: string GetBingGeoLocationsResponse200: type: object properties: paging: type: object properties: start: type: integer count: type: integer links: type: array items: type: object properties: type: type: string rel: type: string href: type: string elements: type: array items: type: object properties: name: type: string urn: type: string facetUrn: type: string ForecastAvgLifetimeFrequencyRequest: type: object example: request: sponsoredAccountUrn: urn:li:sponsoredAccount:{{sponsoredaccount_id}} targetingCriteria: include: and: - or: urn:li:adTargetingFacet:ageRanges: - urn:li:ageRange:(18,24) - or: urn:li:adTargetingFacet:locations: - urn:li:geo:103644278 targetBudgetMicros: 300000000 optimizationType: MAX_REACH objectiveType: BRAND_AWARENESS enableAudienceExpansion: true enableAudienceNetwork: true startDateOn: day: 1 month: 4 year: 2024 endDateOn: day: 1 month: 5 year: 2024 ForecastAvgLifetimeFrequencyResponseundefined: type: string examples: GetAListOfResponse200Example: summary: Example 200 response for GetAListOf value: paging: start: 0 count: 10 links: [] elements: - entityTypes: - FUNCTION facetName: jobFunctions $URN: urn:li:adTargetingFacet:jobFunctions availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - AGE facetName: ageRanges $URN: urn:li:adTargetingFacet:ageRanges availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - GROUP facetName: groups $URN: urn:li:adTargetingFacet:groups availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - COMPANY facetName: employers $URN: urn:li:adTargetingFacet:employers availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - $UNKNOWN facetName: dynamicSegments $URN: urn:li:adTargetingFacet:dynamicSegments availableEntityFinders: - $UNKNOWN - entityTypes: - COUNTRY_GROUP - COUNTRY - STATE - REGION facetName: profileLocations $URN: urn:li:adTargetingFacet:profileLocations availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - GENDER facetName: genders $URN: urn:li:adTargetingFacet:genders availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - COMPANY facetName: firstDegreeConnectionCompanies $URN: urn:li:adTargetingFacet:firstDegreeConnectionCompanies availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - FIRMOGRAPHIC facetName: companyCategory $URN: urn:li:adTargetingFacet:companyCategory availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - TITLE facetName: titlesAll $URN: urn:li:adTargetingFacet:titlesAll availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - LOCALE facetName: interfaceLocales $URN: urn:li:adTargetingFacet:interfaceLocales availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - FIRMOGRAPHIC facetName: growthRate $URN: urn:li:adTargetingFacet:growthRate availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - INDUSTRY facetName: industries $URN: urn:li:adTargetingFacet:industries availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - TITLE facetName: titles $URN: urn:li:adTargetingFacet:titles availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - COMPANY facetName: followedCompanies $URN: urn:li:adTargetingFacet:followedCompanies availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - SCHOOL facetName: schools $URN: urn:li:adTargetingFacet:schools availableEntityFinders: - TYPEAHEAD - entityTypes: - COMPANY_SIZE facetName: staffCountRanges $URN: urn:li:adTargetingFacet:staffCountRanges availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - COMPANY facetName: employersPast $URN: urn:li:adTargetingFacet:employersPast availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - SKILL facetName: skills $URN: urn:li:adTargetingFacet:skills availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - MEMBER_BEHAVIOR facetName: memberBehaviors $URN: urn:li:adTargetingFacet:memberBehaviors availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - $UNKNOWN facetName: audienceMatchingSegments $URN: urn:li:adTargetingFacet:audienceMatchingSegments availableEntityFinders: - $UNKNOWN - entityTypes: - FIELD_OF_STUDY facetName: fieldsOfStudy $URN: urn:li:adTargetingFacet:fieldsOfStudy availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - YEARS_OF_EXPERIENCE facetName: yearsOfExperienceRanges $URN: urn:li:adTargetingFacet:yearsOfExperienceRanges availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - DEGREE facetName: degrees $URN: urn:li:adTargetingFacet:degrees availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - SENIORITY facetName: seniorities $URN: urn:li:adTargetingFacet:seniorities availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - COUNTRY_GROUP - COUNTRY - STATE - REGION facetName: locations $URN: urn:li:adTargetingFacet:locations availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - entityTypes: - TITLE facetName: titlesPast $URN: urn:li:adTargetingFacet:titlesPast availableEntityFinders: - AD_TARGETING_FACET - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - COMPANY facetName: employersAll $URN: urn:li:adTargetingFacet:employersAll availableEntityFinders: - TYPEAHEAD - SIMILAR_ENTITIES - entityTypes: - FIRMOGRAPHIC facetName: revenue $URN: urn:li:adTargetingFacet:revenue availableEntityFinders: - AD_TARGETING_FACET - entityTypes: - INTEREST facetName: interests $URN: urn:li:adTargetingFacet:interests availableEntityFinders: - TYPEAHEAD - AD_TARGETING_FACET GetBingGeoLocationsResponse200Example: summary: Example 200 response for GetBingGeoLocations value: paging: start: 0 count: 10 links: - type: application/json rel: next href: /rest/adTargetingEntities?q=typeahead&query=united%20states&start=10&count=10&facet=urn%3Ali%3AadTargetingFacet%3Alocations&queryVersion=QUERY_USES_URNS elements: - name: United States urn: urn:li:geo:103644278 facetUrn: urn:li:adTargetingFacet:locations - name: California, United States urn: urn:li:geo:102095887 facetUrn: urn:li:adTargetingFacet:locations - name: Texas, United States urn: urn:li:geo:102748797 facetUrn: urn:li:adTargetingFacet:locations - name: New York, United States urn: urn:li:geo:105080838 facetUrn: urn:li:adTargetingFacet:locations - name: Florida, United States urn: urn:li:geo:101318387 facetUrn: urn:li:adTargetingFacet:locations - name: Los Angeles County, California, United States urn: urn:li:geo:103104382 facetUrn: urn:li:adTargetingFacet:locations - name: New York, New York, United States urn: urn:li:geo:102571732 facetUrn: urn:li:adTargetingFacet:locations - name: Illinois, United States urn: urn:li:geo:101949407 facetUrn: urn:li:adTargetingFacet:locations - name: Pennsylvania, United States urn: urn:li:geo:102986501 facetUrn: urn:li:adTargetingFacet:locations - name: Georgia, United States urn: urn:li:geo:103950076 facetUrn: urn:li:adTargetingFacet:locations ForecastAvgLifetimeFrequencyResponseundefinedExample: summary: Example undefined response for ForecastAvgLifetimeFrequency value: "{\n \"value\": {\n \"averageFrequency\": {\n \"metricCurve\": [],\n \"singlePointMetric\": {\n \"metricValue\": 1.8164758594903745,\n \ \ \"budgetMicros\": 300000000\n }\n },\n \"impressionCurve\": {\n \"metricCurve\": [\n {\n \"metricUpper\": 41043.86773686674,\n\ \ \"metricValue\": 34203.22265625,\n \"budgetMicros\": 100000000,\n \"metricLower\": 27362.57781168749\n },\n \ \ {\n \"metricUpper\": 44137.06060459373,\n \"metricValue\": 36780.8828125,\n \"budgetMicros\": 108898986,\n \"metricLower\"\ : 29424.706338958636\n },\n {\n \"metricUpper\": 47193.100333790324,\n \"metricValue\": 39327.58203125,\n \"\ budgetMicros\": 117797981,\n \"metricLower\": 31462.06610782465\n },\n {\n \"metricUpper\": 50215.1916253171,\n \ \ \"metricValue\": 41845.9921875,\n \"budgetMicros\": 126696968,\n \"metricLower\": 33476.793585472864\n },\n {\n \ \ \"metricUpper\": 53206.06663343318,\n \"metricValue\": 44338.38671875,\n \"budgetMicros\": 135595962,\n \"metricLower\": 35470.7102080308\n\ \ },\n {\n \"metricUpper\": 56168.063824241995,\n \"metricValue\": 46806.71875,\n \"budgetMicros\": 144494949,\n\ \ \"metricLower\": 37445.37495286201\n },\n {\n \"metricUpper\": 59103.22017574705,\n \"metricValue\": 49252.6796875,\n\ \ \"budgetMicros\": 153393936,\n \"metricLower\": 39402.14580526844\n },\n {\n \"metricUpper\": 62013.31725117974,\n\ \ \"metricValue\": 51677.76171875,\n \"budgetMicros\": 162292922,\n \"metricLower\": 41342.210474041545\n },\n \ \ {\n \"metricUpper\": 64899.932261183494,\n \"metricValue\": 54083.2734375,\n \"budgetMicros\": 171191925,\n \"metricLower\"\ : 43266.62043291748\n },\n {\n \"metricUpper\": 67764.4524833402,\n \"metricValue\": 56470.375,\n \"budgetMicros\"\ : 180090911,\n \"metricLower\": 45176.30053359452\n },\n {\n \"metricUpper\": 70608.13213893079,\n \"metricValue\"\ : 58840.10546875,\n \"budgetMicros\": 188989898,\n \"metricLower\": 47072.08692357255\n },\n {\n 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366969696,\n \"metricLower\": 82868.00838108321\n },\n {\n \"metricUpper\": 126866.53312570408,\n \ \ \"metricValue\": 105722.109375,\n \"budgetMicros\": 375868682,\n \"metricLower\": 84577.68664995971\n },\n {\n \ \ \"metricUpper\": 129422.09698663955,\n \"metricValue\": 107851.7421875,\n \"budgetMicros\": 384767669,\n \"metricLower\": 86281.39584827129\n },\n {\n \"metricUpper\": 131968.94454708393,\n \"metricValue\": 109974.1171875,\n \"budgetMicros\"\ : 393666656,\n \"metricLower\": 87979.2941797331\n },\n {\n \"metricUpper\": 134507.3016077688,\n \"metricValue\"\ : 112089.4140625,\n \"budgetMicros\": 402565643,\n \"metricLower\": 89671.53217816251\n },\n {\n \"metricUpper\"\ : 137037.39192660234,\n \"metricValue\": 114197.8203125,\n \"budgetMicros\": 411464660,\n \"metricLower\": 91358.25901549454\n \ \ },\n {\n \"metricUpper\": 139559.40326904142,\n \"metricValue\": 116299.5,\n \"budgetMicros\": 420363647,\n \ \ \"metricLower\": 93039.59986869738\n },\n {\n \"metricUpper\": 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