Set up Conversion Lift based on users

Conversion Lift isn’t available for all Google Ads accounts. To use Conversion Lift, contact your Google account representative.

Conversion Lift measures the actual number of conversions, site visits, and any other action directly driven by your audience viewing your ad. Conversion Lift data can help you adjust and improve your ads to generate more sales, leads, and app installs.

Before you begin

Before you can set up Conversion Lift measurement, you need to create a campaign to serve on a supported Google Ads platform. You can use Conversion Lift based on users for Video, Discovery, and Demand Gen campaigns. If you’re interested in using Conversion Lift based on users for Display, Search, Shopping, or Performance Max campaigns, reach out to your Google account representative for more information. Learn more About Conversion Lift.

 


Conversion Lift feasibility

To use Conversion Lift, your Google Ads account must be tracking at least one compatible conversion action. A feasibility rating—high, medium, or low—and a budget recommendation are shared to help you detect lift. The feasibility rating is based on your estimated conversions.

It’s recommended to run studies with a “High” feasibility rating for a 60–90% chance of providing conclusive results. It isn’t recommended to run a study with a “Low” feasibility rating, since the study will have 0–30% chance of achieving conclusive results.

Lift isn't guaranteed, which is why it's recommended to have a testing schedule that includes running several studies over the course of a year.

To increase your estimated conversions, optimize your campaigns to get a lower CPA or higher conversion volume or increase your budget. For more information, contact your account manager.

 


Best practices for measuring Conversion Lift

Conversion categories

We’ve found that upper and mid-funnel conversion actions such as pageviews, submit lead form, add to cart, and more show higher lift, and thus have a higher likelihood of measuring statistically significant lift. We recommend measuring not only bottom-of-the-funnel conversion actions, such as purchase actions, but also upper- and mid-funnel actions. These upper-funnel actions are useful as secondary KPIs or leading indicators that people are responding positively to the ads, in cases when the bottom-funnel action doesn’t have enough data to measure statistically significant results.

Bidding strategies

We've found that campaigns that are utilizing conversion-based or conversion-value-based bidding strategies, such as Target cost per acquisition (CPA), Maximize Conversions, or Target return on ad spend (ROAS) have higher lift than others such as Manual cost per click (CPC) or Target cost per thousand impressions (CPM). We recommend trying conversion-based or conversion-value-based bidding strategies to verify whether this leads to stronger lift for your campaigns.

Attribution model

We've found that campaigns using data-driven attribution have been associated with higher lift. Our data-driven attribution model is calibrated based on incrementality signals. We recommend trying data-driven attribution when trying to optimize towards incremental conversions to verify whether this leads to stronger lift for your campaigns.

Experiment duration

It’s important to set your experiment duration to a length that appropriately captures the average conversion lag, which is the average time between impression and conversion. We allow for studies as short as 7 days but typically recommend more than 14 days, especially if the business has a relatively longer conversion lag or higher value conversion. For example, short purchase cycles such as ordering pizza or purchasing movie tickets may be able to run a short 7–14 day study, whereas a more expensive product such as a mattress or travel accommodations require a longer study that runs for more than 14 days. We’ve found as much as a -17% drop in Absolute Lift in studies with a longer conversion lag measuring lift for less than 14 days, so therefore we recommend to run a study of 14 days minimum.

Frequency with which to run Conversion Lift studies

Any type of incrementality experiment comes with an opportunity cost. This means that by running the experiment and holding back a portion of your audience from viewing your ads, you’re potentially missing out on driving incremental conversions. Because of this, advertisers should be thoughtful about when and how frequently they run incrementality experiments. Experiment frequency tends to align with budget cycles. For example, advertisers should test before making major budget decisions or to validate hypotheses from Media Mix Model results to ensure the most accurate allocation of funds. Additionally, like all experiments, lift results fall within a confidence interval, so it’s encouraged to implement a testing plan to measure incrementality regularly. Based on our historical data, we find most advertisers run about 1–2 studies per year. Speak with your account manager if incrementality optimization is your goal.

Creative matters

It’s important to remember that the creative is what the user views and what can compel them to convert. Stronger creatives will lead to stronger incrementality. Ultimately, the ads should be aligned with the goal that you’re trying to measure. Great ads start with the Core ABCD Principles:

  • Attention: Hook and sustain attention with an immersive story
  • Branding: Brand early, often, and richly
  • Connection: Help people think or feel something
  • Direction: Ask them to take action

 


Instructions

Note: The instructions below are part of the new design for the Google Ads user experience. To use the previous design, click the "Appearance" icon, and select Use previous design. If you're using the previous version of Google Ads, review the Quick reference map or use the Search bar in the top navigation panel of Google Ads to find the page you’re searching for.

Set up Conversion Lift based on users

  1. In your Google Ads account, click the Goals icon Goals Icon.
  2. Click the Measurements drop down in the section menu.
  3. Click Lift measurement.
  4. Click the plus button.
  5. Select Conversion Lift.
  6. Choose which campaigns you’d like to opt into Conversion Lift.
    • Note: Campaigns can only be active in one study at a time. If you’re unable to select a campaign, it most likely means that it’s already being used in another study.
  7. Select the start and end dates for your study.
  8. Review the feasibility status in the right-hand column for an estimate on how likely you are to get precise results based on the campaigns being measured.
    • Note: A “High” feasibility status will offer you the best chances of a successful study. Changing the duration of your experiment or optimizing your campaigns or budget will help you achieve a “High” feasibility status.
  9. Click Save.

View your Conversion Lift measurement data

Conversion Lift measurement data is available at the "Product" or "Brand" level in the "Lift Measurement" table. You can also click into a specific product or brand level study to view more granular results.

Here’s how you view your Conversion Lift measurement data:

  1. Click the columns icon A picture of the Google Ads columns icon.
  2. Click Modify columns.
  3. Select Conversion Lift, then click Apply.

 


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