Definition
Cost optimisation is the ongoing process of moving media-buying budget toward the placements, creatives, GEOs, audiences and times of day that deliver the lowest cost per qualified result, and away from those that do not. It operates at two levels.
Macro optimisation is the portfolio decision — which campaigns and directions to fund, which to cut, where to add budget as something scales. Micro optimisation is the within-campaign work — adjusting bids, adding blacklist and whitelist entries, tuning dayparting and device splits, refreshing creatives.
The defining principle in iGaming is that optimisation is anchored to a downstream metric, not a surface one. Optimising to cost per click produces cheap traffic that often converts into low-value players; optimising to cost per first-time deposit, or better cost per depositing player at a target quality, aligns the work with revenue.
A campaign that halves its cost per click while doubling its cost per qualified FTD has been optimised in the wrong direction.
In context
Disciplined cost optimisation is evidence-gated. A segment — a zone, a creative, a country, an age band — is only cut or scaled once it has enough spend and conversions to be statistically meaningful, because acting on thin data throws away things that were merely unlucky and doubles down on things that were merely lucky.
Practitioners set explicit thresholds (cut a zone past $50 spend with cost per registration over 3x target; scale a creative past 30 conversions under target) so decisions are consistent rather than driven by the last number seen.
Optimisation also has to account for change over time. Auction prices rise as a campaign scales and competitors notice; creatives fatigue; a payout cut or a qualification-rule change at the advertiser can move the effective target overnight.
So decisions are revisited weekly rather than set once, winners are protected from over-editing (each change resets platform learning), and a small exploration budget is kept running to find the next set of winners before the current ones decay.
Worked example
After week one of a casino campaign, the zone report shows Android delivering FTDs at $41 and desktop at $88. The buyer shifts 30% of budget from desktop to Android, cuts a dozen dead zones, and holds all winning creatives untouched to protect learning. Blended cost per FTD drops from $58 to $44 over the following week.
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