The signals that actually matter in smart bidding

Google's smart bidding uses machine learning to set bids for every individual auction. The algorithm draws on a huge range of signals to predict conversion probability and adjust bids accordingly. You cannot control the algorithm directly, but you can control the quality of the data you feed into it.

Device and operating system

Conversion rates vary significantly by device and OS. A user on a desktop Mac converts differently to a user on an Android phone. Smart bidding accounts for this automatically - it adjusts bids higher for device/OS combinations that historically convert well in your account. You do not need to manage device bid adjustments manually when running smart bidding, because the algorithm already incorporates device signals more precisely than any manual adjustment can.

Location and location intent

Where a user is physically located and where they are searching about matters. Someone in Manchester searching "solicitor London" has different intent to someone in London searching the same thing. Smart bidding distinguishes between these. It also factors in hyperlocal signals - not just city level but specific neighbourhoods, depending on data availability.

Time of day and day of week

Conversion rates follow patterns across the week that smart bidding learns automatically. Rather than relying on your manual bid adjustments (which are based on account-level averages), the algorithm adjusts bids based on the actual historical conversion patterns for your specific campaign. This is more granular than any manual schedule could achieve.

Search query

The actual query - not just the matched keyword - is a signal. For broad match keywords, smart bidding considers the semantics of the specific query and its predicted conversion probability. This is one reason why broad match + smart bidding can outperform broad match with manual bidding. The algorithm interprets query intent in context rather than just matching keywords.

First-party data as a signal

Your Customer Match lists and remarketing audiences give the algorithm first-party signal it cannot get elsewhere. A user who has previously purchased from you, or who is on your high-value customer list, gets different bid treatment. This is why uploading and maintaining Customer Match lists is worth the effort even if you are not using them for explicit targeting. They improve the quality of smart bidding decisions across your campaigns.