This release introduces the following updates:
- An improved recommendation algorithm
- Clearer, more useful error messaging
- The option to cancel ongoing experiments
- A host of interface updates
- Improved confidence calculations
These updates should mean higher quality recommendations and a more effective, reliable, and easy to use tool. For more information, you can read the original changelog post below, otherwise, head over to the Toolkit page to get started.
Today we're excited to release Bidding Experiments, our new tool for creating bidding strategy experiments in Google Ads. This tool makes it easy to find the top performing bidding strategies across your account, with recommended experiments that can be set up in just a few clicks. You can also create multi-campaign experiments, see all of your past experiments, and get alerts whenever an experiment ends.
To get started, head on over to Toolkit and open Bidding Experiments. Otherwise, keep reading for a brief summary of the incoming features.
Bidding Experiments — Take a campaign (or group of campaigns) and see if they perform better using a different bidding strategy. Set some basic parameters for your experiment, click Create Experiment and wait for the results to start filtering in. Opteo automatically splits your chosen campaigns into base and experiment versions, comparing their performance and recommending to either promote or remove the experiment once an appropriate confidence score is reached.
Active Experiments — Monitor the progress of your experiments in real time, see per-campaign breakdowns, overall experiment group statistics, performance graphs, experiment parameters, and more.
Multi-Campaign Experiments — Add multiple campaigns to an experiment, get the benefits of more experiment data, and save time by running one shorter experiment rather than several longer ones.
Recommended Experiments — Opteo makes recommendations for bidding experiments based on a variety of campaign attributes. Your campaign data is used to generate sensible experiment parameters, including targets, budget allocation, experiment duration, and more.
Confidence Score — A percentage score that calculates whether you have enough data to make a statistically confident decision, taking into account conversion minimums, impression data, and more.
We hope you find Bidding Experiments useful. If you have a question, please don't hesitate to send our customer support team a message.
As always, we'll be monitoring for any bugs that might come up over the next few days. If you notice anything that looks like a bug, or if you have an idea that could help improve the feature, please let us know.