- Purpose - In case you wish to give set absolute values as a ballpark for the bidding values, use this field to help AI understand what minimum and maximum bid values should be.
- Ideal Practice - Use this when you are certain about your ideal bidding range to drive the target results at target CPR. Best recommended to leverage this once you get familiar with the best-suited Bidding amount for your objectives.
- Purpose - While recommending an action, AI will always ensure and respect the limits you set here. To ensure ideal changes, the user needs to set upper limits/threshold for the Big Change % value in both increasing and decreasing directions.
- Ideal Practice - Always start with small thresholds like 4-5% and then once the user feels comfortable with the recommendations and performance optimisation, can scale up the thresholds.
- Purpose - Similar to the Bid range, here we configure the Budget range if required.
- Ideal Practice - Utlise this to ensure that the budget always stays within a limit no matter what the direction is, AI will use this to ensure the Budget actions never breach the limits.
- Purpose - Similar to Bid % change, here we deal with Budget % thresholds.
- Ideal Practice - Depending on the Budget, target results, and target CPR - users should always put ideal limits to the budget change recommendations such that the AI would be able to achieve the desired target results at the target CPR in a faster time frame.
- Purpose - Similar to the above field, here the AI understands the limits in the -ve direction or decreasing direction.
- Ideal Practice - Depending on the risk factor and targets to achieve, you can set up the limits here.
- Purpose - The Lookback period represents the number of days before today during which the performance is analyzed and actions are taken.
- Ideal Practice - We usually have a 7-day lookback period but if the account has sparse data, a longer lookback is preferred. (We’re also planning to make the lookback period dynamic where the user wouldn’t have to input a number but the model will automatically determine this.)
- Purpose - AI needs to understand the user priorities in terms of whether it needs to focus more on Scaling the performance or Optimising the Cost. There are currently 2 available approaches.
- Ideal Practice - Depending on the brand strategy and account health, users should choose the method that fulfils their requirements in the best possible manner.
- Purpose - Help AI understand what is the result metric for you so that it will be able to deploy the right model for optimizing the performance.
- Ideal Practice - The result metric completely depends on the key objective goal that a user has, ensuring the correctness of this is of utmost importance.
- Purpose - Similar to Target results but the user needs to feed in the Target Cost per result here.
- Ideal Practice - The ideal target CPR should be 15-20% lower (in case of scaling up), than the actual CPR.
- Purpose - Help AI understand what is the ideal amount of results you wish to achieve daily for all the assets(combined) tagged in the concerned AI group
- Ideal Practice - We recommended gradually scaling your targets instead of putting up a huge gap in expectation vs reality. Always go for 5-10% higher (in case of scaling up) amounts than the reality. You can look at the last 7-28 days of historical data to observe the average results trend and make a calculated decision.
