Lift Study

Conversion Lift Measurement is currently limited. Please contact your Meta Representative for information about obtaining access.

Create and run an experiment to measure your Facebook campaign's efficiency. Determine what ads strategy drives the most business impact. See Ad Study, Reference.

When you create a lift study, you create a randomized test group of Accounts Center accounts that see your ads and control group who don't see your ads.

You can securely share conversion data from your ad campaign with Facebook using Facebook pixels, or App Events. Facebook determines the increased conversions generated from your campaign. We compare the number of conversions, Accounts Center accounts converting, and available sales revenue between test and control groups.

Set Up Studies

Set up a study with one or more groups, called cells. When you set up your study, Facebook randomizes the audience for your ads and assigns Accounts Center accounts to either the test or control group. After you run a study, Facebook calculates the difference between the test groups and control groups so that you evaluate the impact of your Facebook ads towards business goals.

To set up a study, make a POST call:

'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'

You can set up a study with a single test group to see how Facebook ads lead to additional business. You can also set up a study with multiple test groups, which lets you determine what advertising approach works best for your audience.

Example - Set up a lift study with one test group

curl \
  -F 'name="new study"' \
  -F 'description="description of my study"' \
  -F 'start_time=1435622400' \
  -F 'end_time=1436918400' \
  -F 'cooldown_start_time=1433116800' \
  -F 'observation_end_time=1438300800' \
  -F 'viewers=[<USER_ID1>, <USER_ID2>]' \
  -F 'type=LIFT' \
  -F 'cells=[{name:"test group",description:"description of my test group",treatment_percentage:90,control_percentage:10,adaccounts:[<ACCOUNT_ID1>,<ACCOUNT_ID2>]}]' \
  -F 'objectives=[{name:"new objective",is_primary:true,type:"CONVERSIONS",applications:[{id:<APP_ID>}]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'

To create a new study, provide the following:

ParameterDescription

name

Name of study.

description

Brief description of the study's purpose.

cooldown_start_time

Deprecated. Facebook still delivers during the time between observation_end_time and end_time. If you use cooldown_start_time, you should now set this time using start_time.

start_time

Start time of campaign active period. Study start time must be in the future.

end_time

End time of campaign active period.

observation_end_time

End of the post test conversion window. During this window (that is, between end_time and observation_end_time), all Facebook ads (including ones added to this study) are delivered normally to both the test and the control group, but no new users will be opportunity logged. We will continue to match conversions during this period to users in their respective groups. If you don't need a post test conversion window for your study, set this to end_time.

cells

Cells in study that define test and control groups.

objectives

Objectives of the study. See Defining Study Objective.

viewers

Share this study to a list of Facebook user IDs.

type

For Conversion Lift, the type should be LIFT.

RESTRICTIONS - Once the study starts, you cannot update start_time and treatment_percentage of the cells. You also cannot remove the associated objects, such as adaccounts or campaigns, of the test groups. You can still update the end_time and observation_end_time to a future time if the study has not yet ended, and add new associated objects to test groups.

To run Reach and Frequency in conjunction with Lift measurement, you must set up a Lift study first and make sure the duration of the Reach and Frequency is within the duration of the Lift study.

Create a Test Group

To begin, determine how many Accounts Center accounts recieve your ads and how many Accounts Center accounts do not. You must create a test group when you set up the study; pass a list of JSON objects in cells under ad_studies. See Ad Study Cell, Reference. A test group contains the following information.

ParameterDescription

name

Name of test group.

description

Brief description of test group.

treatment_percentage

Defines the Accounts Center accounts who receive your ads.

control_percentage

Defines a holdout percentage of the Accounts Center accounts who will not see ads. Treatment plus control percentages must equal 100.

ad_studies

List of ad entities, such as adaccounts or campaigns, to study. Facebook runs and measures all ads under active ad entities during the study period.

Example - Read test groups in a study

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_ID>/cells'

Example - Update or modify cell information and treatment and control percentages by providing the cell ID in cells

curl \
  -F 'cells=[{id:<CELL_ID>,treatment_percentage:80,control_percentage:20}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_ID>'

Example - Read all the studies that you created at ad_studies for your business

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'

You can also see all studies associated with your ad account by making a GET request at {ad-account-ID/include_all_studies=true} with your access token.

Set Up Multiple Test Groups

Set up a study with multiple test groups of Facebook users. This helps measure incremental impact of different Facebook strategies on business goals, such as using different ads targeting options. To set up a study with multiple test groups, provide a list of test groups in cells.

curl \
  -F 'name="new study"' \
  -F 'description="description of my study"' \
  -F 'start_time=1435622400' \
  -F 'end_time=1436918400' \
  -F 'cooldown_start_time=1433116800' \
  -F 'observation_end_time=1438300800' \
  -F 'viewers=[<USER_ID1>, <USER_ID2>]' \
  -F 'type=LIFT' \
  -F 'cells=[{name:"group A",description:"description of group A",treatment_percentage:50,control_percentage:20,campaigns:[<CAMPAIGN_ID1>]},{name:"group B",description:"description of group B",treatment_percentage:20,control_percentage:10,campaigns:[<CAMPAIGN_ID2>]}]' \
  -F 'objectives=[{name:"new objective",is_primary:true,type:"CONVERSIONS",applications:[{id:<APP_ID>}]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'

control_percentage determines the holdout for each test group respective to the total population. For example, you have a study with two test groups: group A is 50% treatment with 20% control and group B is 20% treament with 10% control. This results in ~28.6%, or 20%/70% of the population in group A, to be control users and ~33.3%, or 10%/30% of the population in group B, to be control users.

The sum of treatment and control percentages across test groups normally should equal 100. However, it can be less than 100 for some specific use cases. For example, when you have three test groups that are split evenly at 33%.

You can update, add, and remove test groups in a study.

  • To update an existing test group, refer to its ID in test group.
  • To add a new test group, provide a new test group object.
  • To remove a test group, simply omit it from cells when you update the study:
curl \
  -F 'cells=[{id:<CELL_ID1>,treatment_percentage:60,control_percentage:10},{name:"group C",description:"replacing group B",treatment_percentage:25,control_percentage:5,campaigns:[<CAMPAIGN_ID3>]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_ID>'

Define Advertising Objectives

Define advertising objectives you want to measure and how you pass conversion data to Facebook. A lift study requires at least one objective. You cannot modify objectives after the study starts running. See Ad Study Objective, Reference.

Example - Create and add the CONVERSIONS objective to a study

curl \
  -F 'name="new study"' \
  -F 'description="description of my study"' \
  -F 'start_time=1435622400' \
  -F 'end_time=1436918400' \
  -F 'cooldown_start_time=1433116800' \
  -F 'observation_end_time=1438300800' \
  -F 'viewers=[<USER_ID1>, <USER_ID2>]' \
  -F 'type=LIFT' \
  -F 'cells=[{name:"test group",description:"description of my test group",treatment_percentage:90,control_percentage:10,adaccounts:[<ACCOUNT_ID1>,<ACCOUNT_ID2>]}]' \
  -F 'objectives=[{name:"new objective",is_primary:true,type:"CONVERSIONS",applications:[{id:<APP_ID>}]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'


Name Description Data Sources

CONVERSIONS

Measure the lift in conversions.

CAPI-based Facebook pixels

If you use CONVERSIONS and use Facebook pixel or Mobile App as event sources, you must provide a list of the event names that you want to capture for the objective. Facebook can then report results based on these specific conversion events.

Measurement Source Event Names

Facebook Pixel

fb_pixel_view_content, fb_pixel_search, fb_pixel_add_to_cart, fb_pixel_add_to_wishlist, fb_pixel_initiate_checkout, fb_pixel_add_payment_info, fb_pixel_purchase, fb_pixel_lead, fb_pixel_complete_registration, custom

Mobile App

fb_mobile_activate_app, fb_mobile_complete_registration, fb_mobile_content_view, fb_mobile_search, fb_mobile_rate, fb_mobile_tutorial_completion, fb_mobile_add_to_cart, fb_mobile_add_to_wishlist, fb_mobile_initiated_checkout, fb_mobile_add_payment_info, fb_mobile_purchase, fb_mobile_level_achieved, fb_mobile_achievement_unlocked, fb_mobile_spent_credits

Create an Objective

Create an objective by passing a list of JSON objects objectives when you create a new study. Objectives contain the following information:

ParameterDescription

name

Name of the objective.

is_primary

A boolean specifying that this is your primary advertising objective. A study can only have one primary objective.

type

Objective value of CONVERSIONS.

adspixels

List of Facebook pixel IDs along with the relevant list of event_names per ID, if applicable.

applications

List of your mobile apps including relevant event_names per ID.

offline_conversion_data_sets

List of Offline Event set IDs if applicable. Currently, we don't support event breakdowns for Offline Conversion.

customconversions

List of Custom Conversion IDs, if applicable.

You can also have multiple objectives per study. The result will be aggregated based on objectives. Below is an example of a study with multiple objectives.

curl \
  -F 'name="another study"' \
  -F 'description="description of another study"' \
  -F 'start_time=1435622400' \
  -F 'end_time=1436918400' \
  -F 'cooldown_start_time=1433116800' \
  -F 'observation_end_time=1438300800' \
  -F 'viewers=[<USER_ID1>, <USER_ID2>]' \
  -F 'type=LIFT' \
  -F 'cells=[{name:"test group",description:"description of my test group",treatment_percentage:90,control_percentage:10,adaccounts:[<ACCOUNT_ID1>,<ACCOUNT_ID2>]}]' \
  -F 'objectives=[{name:"first objective objective",is_primary:true,type:"CONVERSIONS",applications:[{id:<APP_ID1>},{id:<APP_ID2>}]},{name:"scond  objective",type:"CONVERSIONS",applications:[{id:<APP_ID3>,event_names:["fb_mobile_purchase"]}],adspixels:[{id:<FB_PIXEL_ID>,event_names:["fb_pixel_purchase","fb_pixel_lead"]}]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<BUSINESS_ID>/ad_studies'

You can update, add, and remove objectives in a study by doing so at the study level similar to modifying test groups. To update an existing objective, refer to its ID in the objectives object. To add a new objective, provide a new objective object. To remove an objective, simply omit it from the objectives parameter when you update it.

Example - Update an objective's applications measurement sources and remove its adspixels measurement sources

curl \
  -F 'objectives=[{id:<OBJECTIVE_ID>,name:"new objective name",applications:[{id:<APP_ID>}],adspixels:[]}]' \
  -F 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_ID>'

Example - Read objectives for a study

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_OBJECTIVE_ID>?fields=results&breakdowns=["cell_id"]'

Reporting

Retrieve Objectives

All "buyers" metrics will show up for studies started before the cut-off date 7/13/2021. Studies started after 7/13 will not have "buyers" metrics and breakdown by gender, age and country. This change will impact fields below that start with “buyers" (buyers_test, buyers_control_scaled2, and so on).

Note also that you need to use the cell_id breakdown in order to get cell level results.

A study's objectives are defined during the study setup. See the setup guide on how to define your study's objectives

You can read the objectives that were created for a study by making a GET call to the study's objectives edge.

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_OBJECTIVE_ID>?fields=results&breakdowns=["cell_id"]'

For more details on objectives, refer to the Ad Study Objective reference documentation.

Retrieve Results

To retrieve results for an objective, you can make a GET call to the objective node by specifying results in the fields parameter. The last_updated_results field also tells you when the results data for this particular objective was last updated.

Sample response shown as parsed JSON for ease of reading.

Command:

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_OBJECTIVE_ID>?fields=results&breakdowns=["cell_id"]'

The resulting data is a JSON object, containing metrics name and values strings. Please refer to Facebook Lift Metrics Glossary.

With buyers:

{
	"results": [
	"{"cell_id":"<cell_id>",
	"population_test":2334212,
	"population_control":123407,
	"population_reached":1862084,
	"impressions":19020874,
	"spend":26059,
	"buyers_control_raw_scaled":37672.615701199,
	"buyers_exposed":30085.482427228,
	"buyers_frequentist_pValue":0.00064950107027983,
	"conversions_control_raw_scaled":110918.27003534,
	"conversions_exposed":86961.044050743,
	"conversions_raw_pValue":0.12863848309723,
	"conversions_test":104412.89695396,
	"conversions_control_scaled":104575.81331581,
	"conversions_incremental":-162.91636184894,
	"conversions_notExposed":87123.960412592,
	"conversions_confidence":0.69291721817069,
	"conversions_multicell_confidence":null,
	"conversions_incremental_lower":-3470.6251396487,
	"conversions_incremental_upper":3235.0644420632,
	"conversions_multicell_rank":null,
	"conversions_incremental_share":-0.001873440730011,
	"conversions_CPiC":-159.95324044961,
	"buyers_test":40732.369934386,
	"buyers_control_scaled":41990.129061459,
	"buyers_incremental":-1257.7591270729,
	"buyers_notExposed":36617.935710157,
	"buyers_confidence":0.19318944031404,
	"buyers_multicell_confidence":null,
	"buyers_incremental_lower":-2905.5296282828,
	"buyers_incremental_upper":426.25813050358,
	"buyers_multicell_rank":null,
	"buyers_incremental_share":-0.041806181107957,
	"buyers_CPiB":-20.718593440578}"
	  ],
	  "id": "<objective_id>"
}


Without buyers:

{
	"results": [
	"{"cell_id":"<cell_id>",
	"population_test":2334212,
	"population_control":123407,
	"population_reached":1862084,
	"impressions":19020874,
	"spend":26059,
	"conversions_control_raw_scaled":110918.27003534,
	"conversions_exposed":86961.044050743,
	"conversions_raw_pValue":0.12863848309723,
	"conversions_test":104412.89695396,
	"conversions_control_scaled":104575.81331581,
	"conversions_incremental":-162.91636184894,
	"conversions_notExposed":87123.960412592,
	"conversions_confidence":0.69291721817069,
	"conversions_multicell_confidence":null,
	"conversions_incremental_lower":-3470.6251396487,
	"conversions_incremental_upper":3235.0644420632,
	"conversions_multicell_rank":null,
	"conversions_incremental_share":-0.001873440730011,
	"conversions_CPiC":-159.95324044961}"
	  ],
	  "id": "<objective_id>"
}

Breakdown Results

In addition to retrieving the results per objective, you may choose to breakdown the results by providing the breakdowns parameter.

curl -G \
  -d 'access_token=<ACCESS_TOKEN>' \
  'https://graph.facebook.com/<API_VERSION>/<STUDY_OBJECTIVE_ID>?fields=results&breakdowns=["cell_id"]'

The following are the available breakdown dimensions:

Studies started after 7/13 will not have breakdowns by gender, age and country.

Breakdown Values

age

13-17, 18-24, 25-34, 35-44, 45-54, 55-54, 65+

cell_id

IDs of the available cells in the study.

gender

M or F

country

Two-letter country codes (ISO 3166-1 alpha-2). Example: US, GB, IN, AU.

Currently supported only when queried in combination with cell_id.

Example: breakdowns=['cell_id','country']

The results return multiple JSON objects in the array based on the available breakdowns. For example, if cell_id is provided, the results are broken down by the number of cells in the study. You may provide one or more breakdowns; however, the combination of breakdowns must at least 100 conversions from test and control groups combined for results to display.

{
  "id": "<STUDY_OBJECTIVE_ID>",
  "results": [
  {
    "cell_id": "<CELL_ID1>",
    ...
    Default fields where the values are specific to the <CELL_ID1> breakdown
    ...
  },
  {
    "cell_id": "<CELL_ID2>",
    ...
    Default fields where the values are specific to the <CELL_ID2> breakdown
    ...
  }],
}

Results for a Specific Date Stamp

You can specify a date stamp in your API call to obtain study results from a specific date. Note that the call returns the same result that it would if you made the same call on that specific date without including the date stamp field. The date should be within the prior 30 days.

curl -G \
      -d 'access_token=<ACCESS_TOKEN>' \
      'https://graph.facebook.com/<API_VERSION>/<STUDY_OBJECTIVE_ID>?fields=results&ds=2020-03-01'