Algorithmic Bid Management
Algorithmic bid management refers to using automated rules or machine learning models to set and adjust advertising bids based on real-time performance signals. These signals can include the likelihood of conversion, competition, audience behaviour, and budget pacing, reducing the need for marketers to adjust bids manually.
Why it matters
Ad auctions on platforms such as Google Ads and LinkedIn can change throughout the day. Competitor bids, audience demand, and conversion likelihood can all shift, meaning a bid that performs well in the morning may not be as effective later. Manually checking and adjusting bids across multiple campaigns can make it difficult to respond to these changes quickly.
Automated bidding allows teams to adjust bids more frequently based on current campaign performance. This becomes especially useful as the number of campaigns and advertising platforms increases. It also connects closely with AI Budget Allocation, where bid decisions and budget distribution can work together to respond to changing performance.
Platforms like Campulse can automate bid management across campaigns, helping teams adjust bids based on current performance rather than relying on a fixed schedule of manual checks.
Example
A D2C brand was manually adjusting bids across 15 campaigns twice a week. After adopting algorithmic bid management, the team could respond to changes in conversion performance throughout the week instead of waiting for the next manual review. This helped the team manage bids more efficiently and respond to opportunities that may have been missed between adjustments.