實驗功能為何有助於制定良好的成效評估方法？

Experiments in Google Ads are crucial for a robust measurement strategy because they allow you to validate and test insights. By running controlled experiments, you can isolate the impact of specific changes (e.g., bidding strategies, ad copy, targeting) and determine if they genuinely lead to improved performance before fully implementing them. This data-driven approach ensures that decisions are based on proven results, not just assumptions. "Experiments help attribute credit across touchpoints" is incorrect because attribution models, not experiments, are designed for this purpose. "Experiments inform overall budget strategy" is too broad; while experiment results can influence budget allocation for specific campaigns, they don't solely dictate the overall budget. "Experiments help collect multiple data points" is true, but it's a consequence, not the primary benefit for developing a good measurement strategy; the key is using those data points to validate hypotheses.