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What should I do with a campaign that's both budget-limited and rank-limited at the same time?

A quick primer

This is a specific, common situation in real accounts: a campaign is losing impressions to both budget (Search Lost IS budget is high) and to an insufficiently high ad rank (Search Lost IS rank is high) at the same time. The typical mistake here is to try raising both the budget and bids/loosening the target at once, hoping to "fix everything in one shot." The problem with that approach is that you won't be able to tell which change actually cleared the constraint, and which just added unspent money on top of a problem that's still bottlenecked by rank.

There's also a substantive reason these two constraints often show up together, and it's not a coincidence: a low ad rank means the campaign wins auctions less often for the same amount of money, so, all else equal, the budget gets spent more slowly and the campaign hits a real budget shortfall less often at any given moment — meaning at first glance it can look like the budget is "enough." But if rank isn't the only cause of low spend (say, the campaign is capturing a lot of cheap clicks that still exhaust the budget early in the day), both constraints can be operating in parallel and independently. The official breakdown of the Impression Share metric, which lets you quantify these two cases separately, is in Google Ads Help's article on Impression Share, and a general overview of statuses that can be present simultaneously is in Google Ads Help's article on bid strategy statuses. If both constraints are tied to a recent target change, it's also worth factoring in the length of the Smart Bidding learning cycle when assessing whether the situation has actually settled.

What to check before you touch anything

  • The exact numeric values of Search Lost IS (budget) and Search Lost IS (rank) — which is bigger, and how significant is the gap between them?
  • Do both constraints share a common root cause (an overly low target simultaneously lowering rank and — by reducing the number of won auctions — masking a real need for a bigger budget)?
  • Are technical bid limits set separately from the target itself? They could be an independent cause of low rank, unrelated to the target directly.
  • How strong are the ads and landing pages (Quality Score)? Low rank might not just be about bids/target — it could be weak Ad Relevance or Landing Page Experience, which calls for a different fix.
  • Is the business prepared for gradual, staged testing (one change first, then another), or is there pressure for a quick fix? This shapes whether it makes sense to break the process into sequential steps or look for a faster, less precise path.

Possible approaches

  • The standard, most reliable practical plan: first identify which of the two Lost IS figures is bigger, and fix that one, leaving the other parameter unchanged; then, after 1–2 weeks, assess the effect and address the second factor if needed.
  • If both figures are roughly equal, start with the budget, since it's a faster and more reversible change than adjusting the target, which kicks off a new Smart Bidding learning cycle.
  • If low rank isn't caused by the target/bids but by weak Quality Score (check Ad Relevance and Landing Page Experience separately), neither raising the budget nor loosening the target will solve the problem — you need to work on ad and landing page quality instead.
  • If a single common root cause is found (an overly aggressive target), it's more logical to fix that directly rather than treating both symptoms separately with uncoordinated changes.
  • Log the order and dates of changes in a working journal as you go, so that when you re-analyze a few weeks later, you know exactly which intervention led to which effect, rather than relying on memory.
  • Figuring out by hand which factor is bigger, whether there's a common root cause, and whether Quality Score is also a factor, for every campaign, is a labor-intensive process, especially in accounts with many campaigns. Our tool (DataMind) analyzes all these signals simultaneously for every campaign and explicitly indicates which of the two factors is stronger in a given case and whether they share a common root cause — instead of a sequential, manual check of every hypothesis.