{"id":3384,"date":"2026-07-17T12:32:54","date_gmt":"2026-07-17T09:32:54","guid":{"rendered":"https:\/\/ivitskiy.com\/blog\/google-ads-campaign-graveyard\/"},"modified":"2026-07-17T13:53:32","modified_gmt":"2026-07-17T10:53:32","slug":"google-ads-campaign-graveyard","status":"publish","type":"post","link":"https:\/\/ivitskiy.com\/blog\/en\/google-ads-campaign-graveyard\/","title":{"rendered":"The Campaign Graveyard: Where 75% of Demand Gen Budgets End Up"},"content":{"rendered":"\n
In short:<\/strong> Across the sample, 75% of all Demand Gen spend on campaigns over $1,000 sits in campaigns that are now paused or removed, against just 8.9% for Search. Whole campaigns get launched, funded, and left inactive. That is a spend-share statistic, not a survival rate, and paused does not automatically mean wasted. But the gap is a strong clutter signal, and it points to how you fund experiments. Here is how to test without letting spend pile up unexplained.<\/div>\n\n\n\n

Accounts do not just waste money on bad keywords. They attach real budget to entire campaigns that later go inactive. When I sort spend by whether the campaign is still running, a clear pattern appears: for some campaign types, a much larger share of historical spend is tied to campaigns that are now paused or removed.<\/p>\n\n\n\n

Demand Gen<\/span><\/span><\/span>75%<\/span><\/div>
Search<\/span><\/span><\/span>8.9%<\/span><\/div><\/div>
Share of spend (campaigns over $1,000) now in paused or removed status. Data: 31-account analysis<\/div>\n\n\n\n

Three quarters of the Demand Gen money was attached to campaigns that are no longer running. For Search it was under one dollar in ten. This is a spend-share comparison, not a survival rate, and status alone does not prove those campaigns failed. But the size of the gap is hard to ignore.<\/p>\n\n\n\n

Status is not the same as failure<\/h2>\n\n\n\n

A paused campaign can be resumed; a removed one is deleted. Neither status, by itself, tells you whether the campaign produced value, completed a seasonal run, or was abandoned mid-test. That is exactly why a high inactive-spend share is a signal to investigate, not a verdict. The Demand Gen number stands out because the spend was large and the inactive share was extreme.<\/p>\n\n\n\n

The activity often comes in bursts. In one account the change log jumped from about 34 edits a week to 816 for roughly three months, then fell back to 8. Bid edits made up 79% of that burst. That is an operational spike, not proof of a launch spree, but it is the shape of an account being worked hard and then left alone.<\/p>\n\n\n\n

How to test without the pile-up<\/h2>\n\n\n\n
  1. Decide the kill criterion before you launch: what result, by what date, at what spend, tells you to stop. Write it down.<\/li>
  2. Give automated formats like Demand Gen a fixed test budget and a fixed window. They use Smart Bidding and need a learning period, so set the evaluation window in advance.<\/li>
  3. When a campaign fails its criterion, pause it, label the outcome, and record the lesson. Paused campaigns are not the problem; unexplained paused campaigns are.<\/li>
  4. Review your inactive campaigns by category, test, seasonal, migration, before reading anything into the count.<\/li><\/ol>\n\n\n\n

    The researcher’s take<\/h2>\n\n\n\n

    Experimentation is good. Unexplained inactive spend is just clutter you cannot learn from. The accounts with the worst pile-ups were not the ones that tested too little, they were the ones that funded automated formats open-endedly and never came back to label the outcome. Test with a kill switch defined up front, especially on the formats that spend fastest, and pause with a reason attached, not in silence.<\/p>\n\n\n\n\n\n

    FAQ<\/h2>\n\n\n\n

    Does a high paused share always mean waste?<\/h3>\n\n\n\n

    No. Some pausing is healthy pruning or a finished seasonal run. It becomes a problem when large budget went inactive with no lesson captured. Status alone does not measure profitability, which is why the number is a prompt to investigate rather than a conclusion.<\/p>\n\n\n\n

    Should I avoid Demand Gen then?<\/h3>\n\n\n\n

    No. Just fund it as a bounded test, not an open tap. It runs on Smart Bidding and needs a learning window, so a fixed budget and a pre-set evaluation date keep it from piling up unexplained.<\/p>\n\n\n\n