{"id":9115,"date":"2026-10-19T11:28:48","date_gmt":"2026-10-19T08:28:48","guid":{"rendered":"https:\/\/ivitskiy.com\/blog\/?p=9115"},"modified":"2026-10-19T11:28:48","modified_gmt":"2026-10-19T08:28:48","slug":"google-ads-experiments","status":"publish","type":"post","link":"https:\/\/ivitskiy.com\/blog\/en\/google-ads-experiments\/","title":{"rendered":"Google Ads experiments: how to test a change before you commit"},"content":{"rendered":"\n
In short:<\/strong> a Google Ads experiment splits a campaign\u2019s traffic and budget between the old and the new settings, and you compare the results before you change anything for good. Google recommends a 50% split and, if the result is still undecided, at least four to six weeks. As an example of a minimum, the Help page names more than 100 conversions a day. In the small accounts I audit, an experiment often stays silent.<\/div>\n\n\n\n

A Google Ads experiment creates a copy of your campaign with your change in it and splits traffic and budget between the copy and the original. You see which one did better, and only then apply the change. This is how you test a new bidding strategy, a keyword match type or a new landing page while risking only part of your traffic.<\/p>\n\n\n\n

There is one catch to start with. An experiment limits the share of traffic that gets the change, but it does not remove the risk on that share: the new version can do worse. Also, with few leads the comparison becomes unreadable. As an example of a minimum, the Help page names more than 100 conversions a day in the base campaign. A plumber, an HVAC company or a dental clinic usually gets leads at a very different scale, and in my practice an experiment there can show \u201cno difference\u201d for months. Below: what to test, how to set it up, how to read the result and what to do instead when the data is thin. The choice of the strategy itself is covered in the guide to Google Ads bid strategies<\/a>.<\/p>\n\n\n\n

What an experiment is and why it beats \u201cjust change it\u201d<\/h2>\n\n\n\n

When you simply change a setting, you compare \u201cbefore\u201d and \u201cafter\u201d. But season, competitors and the price of a click all move at the same time. In an experiment both versions run side by side and share traffic and budget, so the season hits both of them equally.<\/p>\n\n\n\n

Here is an example of why \u201cbefore and after\u201d is unreliable. In Optmyzr\u2019s 2024 study, which covered nearly six thousand accounts, the cost per click during the Black Friday and Cyber Monday period<\/a> rose 17% against the week before in accounts without a seasonality adjustment and 34% in accounts with one. That is a comparison of two groups of accounts, not an experiment, and it does not prove why they differ. But the main point is visible: at the peak the cost per click rose in both groups. If you change a bidding strategy right then, \u201cbefore and after\u201d mixes the effect of your change with the effect of the season.<\/p>\n\n\n\n

What to test and what not to<\/h2>\n\n\n\n

Google usually points to custom experiments for these checks: Smart Bidding, keyword match types, landing pages, audiences and ad groups. For the text of Search ads there is a separate tool, ad variations. The left and right columns of the table below are not linked row by row: they are two separate lists.<\/p>\n\n\n\n

\n
Worth testing with an experiment<\/th>Not for an experiment, and why<\/th><\/tr><\/thead>
A new bidding strategy<\/td>App and Shopping campaigns: standard custom experiments are not supported for them<\/td><\/tr>\n
A keyword match type<\/td>A campaign with a shared budget or a portfolio bidding strategy: it cannot be selected for an experiment<\/td><\/tr>\n
A new landing page<\/td>A campaign with Text ads or Expanded Text ads: they have to be deleted from all ad groups first, including paused and removed ones, in the Ads and assets menu, and then you wait 24 to 48 hours for the system to update<\/td><\/tr>\n
Audiences or an ad group<\/td>The text of Search ads: Google recommends ad variations for that<\/td><\/tr>\n
One change at a time<\/td>Several edits in one experiment: if the result moves, you cannot tell which edit did it<\/td><\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n

How to create an experiment: steps<\/h2>\n\n\n\n

The steps come from the Help page on setting up a custom experiment<\/a>. Do them in your own account.<\/p>\n\n\n\n

    \n
  1. Go to Experiments within the Campaigns menu.<\/li>\n
  2. Select the plus button at the top of the \u201cAll experiments\u201d table and select Custom.<\/li>\n
  3. Select Custom experiment, choose a campaign type, then select Continue.<\/li>\n
  4. Enter a name for the experiment (a description is optional) and choose the original campaigns.<\/li>\n
  5. Add a suffix to the test campaign names, for example \u201cCampaign 2 (Holiday_test)\u201d, then select Continue.<\/li>\n
  6. On the next page, modify the test variables in the trial campaign: make the one change you are testing, for example a new bidding strategy.<\/li>\n
  7. Select up to two goals to measure success.<\/li>\n
  8. In the \u201cExperiment split\u201d section, choose the share of traffic and budget.<\/li>\n
  9. In the \u201cSchedule the experiment\u201d section, pick the start date and the duration, then select Save.<\/li>\n<\/ol>\n\n\n\n

    There is another route: while you edit the settings of an active campaign, select Save as experiment. Choose the goal before you launch. For a service business that is usually leads, not clicks. And do not change it once you have seen the numbers.<\/p>\n\n\n\n

    Traffic split and how long to run it<\/h2>\n\n\n\n

    The Help page recommends splitting traffic and budget 50\/50, because that gives the best comparison between the original and the experiment. For Search campaigns there are two ways to split. Cookie-based (recommended) shows a person only one version. Search-based picks a version after every search, so one person can see both, but it may reach statistically significant results faster. If you pick cookie-based and use audience lists, the list should have at least 10,000 users, otherwise the results may be less accurate.<\/p>\n\n\n\n

    A 50\/50 split does not guarantee equal impressions or spend: they depend on auction dynamics such as Ad Rank and the bidding strategy. Allow 7 to 14 days for the experiment side to stabilize. If an experiment has stopped serving or has zero impressions, check whether it is in the \u201cBid Strategy Learning\u201d phase. It typically lasts 7 days, and you should not make changes during it. That phase is covered in more detail in the guide to the Learning status<\/a>.<\/p>\n\n\n\n

    Now the duration. The Help page for the Experiments page has this advice: if the Results column shows In Progress, Undecided or Unavailable, give the experiment at least four to six weeks to collect enough data. If there is still no recommendation after that, the Help page suggests changing the budget or waiting longer. But a budget change in the middle of a test is also an edit, and edits make the results harder to interpret. If you make it, write down the date. If there is no rush, waiting is better. It is better to schedule the start ahead of time, so the experiment does not begin before its ads have been reviewed.<\/p>\n\n\n\n

    How to read the result<\/h2>\n\n\n\n

    On the Experiments page, Google highlights in the report the one or two metrics you chose as your goal. The rest stay next to them in a summary table that compares the original and the experiment. Look at your goal first and at the rest second, so the change does not improve one thing at the cost of another. Compare the same dates for both versions.<\/p>\n\n\n\n

    While the experiment runs, change nothing in the original or in the experiment. There is one exception: the budget, if there is still no answer after four to six weeks, and then write down the date. The Help page warns that changes to the original are not reflected in the experiment, and edits to either campaign can make the results harder to interpret. In the accounts I audit, I often see the opposite: several settings changed at once, nobody wrote down the date, and later nobody knows what worked.<\/p>\n\n\n\n

    Do not panic if one side gets fewer impressions. Each ad slot is a new auction, and if one side hits its daily budget first, it stops showing until the next day. A small difference on a small number of leads is mostly noise. If the result is undecided, it means there is no answer yet, not that the new version lost.<\/p>\n\n\n\n

    Apply it or drop it<\/h2>\n\n\n\n

    If the experiment won on your goal, you can apply it to the original campaign manually or automatically. The second option is to convert the experiment into a new campaign with the same dates and budget, and the original is paused. The performance data is kept either way. After the conversion, check the new campaign to see that all the changes were applied correctly.<\/p>\n\n\n\n

    If it did not win, end it: change the end date, or select Edit and then End now. When the numbers are close, there is nothing to switch to. And if the Results column still says Undecided, that is not a loss and not a reason to end the test before the time the Help page gives.<\/p>\n\n\n\n

    The step-by-step version of how I set this up in live accounts is in my e-book on Google Ads for business owners.<\/p>\n\n\n\n\n\n

    When this does not apply<\/h2>\n\n\n\n

    There are few conversions. This is the main limit. Then it is more honest to change one setting, write down the date and compare periods of the same length. That is weaker evidence than an experiment, but it does not stay silent for months. Remember the season: the Optmyzr example above is exactly about that. How to check whether an automated strategy holds your target is explained in the guide to whether Smart Bidding hits your target<\/a>.<\/p>\n\n\n\n

    The campaign does not qualify. It must be active, with an individual daily budget and a standard bidding strategy. If the base campaign is paused or ends before the experiment does, the experiment will not run or serve impressions.<\/p>\n\n\n\n

    You change the original during the test. Then the comparison loses its meaning, because you no longer know how the versions differ.<\/p>\n\n\n\n

    Questions and answers<\/h2>\n\n\n\n

    Does an experiment cost extra money?<\/h3>\n\n\n\n

    There is no separate budget: the experiment shares the traffic and budget of the original campaign. You choose what share it gets, and the Help page recommends 50%.<\/p>\n\n\n\n

    How many experiments can run at the same time?<\/h3>\n\n\n\n

    You can schedule up to 5 experiments for a campaign, but only one can run at a time.<\/p>\n\n\n\n

    Can I end an experiment early?<\/h3>\n\n\n\n

    Yes. Change the end date, or select Edit and then End now. More on experiment types and limits is in the Help page about custom experiments<\/a>.<\/p>\n\n\n\n

    How do I test ad text?<\/h3>\n\n\n\n

    For the text of Search ads, Google recommends ad variations instead of a custom experiment. A custom experiment fits when you test campaign settings or specific ad groups.<\/p>\n\n","protected":false},"excerpt":{"rendered":"

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