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绘制优化可视化图表
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
本页面介绍了如何自定义优化可视化图表。优化器输出的 OptimizationResults
数据对象也包含用于直观呈现数据的绘制方法。
优化后支出的变化
您可以查看显示各渠道的优化后支出变化的可视化图表,将当前预算与优化后的支出进行比较,从而获得针对每个渠道的更精细的数据分析。
运行以下命令可绘制各渠道的优化后支出变化图表:
optimization_results.plot_spend_delta()
输出示例:
优化后的增量收入或 KPI
您可以对比历史数据和优化后的数据,了解增量收入或 KPI 的变化。此可视化图表以当前的增量收入或 KPI 为起点,显示每个渠道在达到优化后的增量收入或 KPI 时的变化。
运行以下命令可绘制优化后的增量收入或 KPI 图表:
optimization_results.plot_incremental_outcome_delta()
输出示例:
优化后的预算分配
您可以直观呈现各渠道的预算分配优化,以便获得有关如何分配预算的总体建议。
运行以下命令可查看各渠道优化后的预算分配:
optimization_results.plot_budget_allocation()
输出示例:
基于响应曲线的优化预算
响应曲线会显示增加预算后可能获得的收入。实线表示为优化设置的支出限制范围,图中会指明以下两点:当前支出水平和优化后新的支出水平。
运行以下命令可基于响应曲线绘制优化后的预算:
optimization_results.plot_response_curves()
输出示例:(点击图片可放大。)

如未另行说明,那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可,并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情,请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC):2025-08-04。
[null,null,["最后更新时间 (UTC):2025-08-04。"],[[["\u003cp\u003eThe \u003ccode\u003eOptimizationResults\u003c/code\u003e object provides built-in plotting methods for visualizing optimization outcomes.\u003c/p\u003e\n"],["\u003cp\u003eYou can visualize the change in spend per channel by comparing current budget to the optimized spend via \u003ccode\u003eoptimization_results.plot_spend_delta()\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eThe change in incremental revenue or KPI from historical to optimized data can be viewed with \u003ccode\u003eoptimization_results.plot_incremental_impact_delta()\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eVisualize the recommended budget allocation per channel using the command \u003ccode\u003eoptimization_results.plot_budget_allocation()\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eResponse curves are generated using \u003ccode\u003eoptimization_results.plot_response_curves()\u003c/code\u003e to display potential revenue gains with increasing budget, showing current and optimized spend levels.\u003c/p\u003e\n"]]],["The `OptimizationResults` object provides plotting methods for visualizing optimization data. Key actions include using `plot_spend_delta()` to compare current vs. optimized spend per channel, `plot_incremental_impact_delta()` to visualize changes in incremental revenue/KPI, and `plot_budget_allocation()` to see the optimized budget distribution across channels. `plot_response_curves()` visualizes potential revenue changes with budget increases, highlighting current and optimized spend levels within set constraints. Each function generates a visualization output.\n"],null,["# Plot optimization visualizations\n\nThis page describes how to customize your optimization visualizations. The\n`OptimizationResults` data object that is outputted by the optimizer also\ncontains plotting methods to visualize them.\n\nChange in optimized spend\n-------------------------\n\nYou can view an optimized spend change per channel visualization to compare your\ncurrent budget to the optimized spend. This gives you more granular insights per\nchannel.\n\nRun the following command to plot the optimized change in spend per channel: \n\n optimization_results.plot_spend_delta()\n\n**Example output:**\n\nOptimized incremental revenue or KPI\n------------------------------------\n\nYou can view the change in incremental revenue or KPI from the historical data\nto the optimized data. The visualization starts out with the current incremental\nrevenue or KPI and shows the differences per channel to reach the optimized\nincremental revenue or KPI.\n\nRun the following command to plot the optimized incremental revenue or KPI: \n\n optimization_results.plot_incremental_outcome_delta()\n\n**Example output:**\n\nOptimized budget allocation\n---------------------------\n\nYou can visualize the budget allocation optimization by channel for an overall\nrecommendation of how to allocate your budget.\n\nRun the following command to view the optimized budget allocation for each\nchannel: \n\n optimization_results.plot_budget_allocation()\n\n**Example output:**\n\nOptimized budget on response curves\n-----------------------------------\n\nResponse curves show how much revenue might be made as you increase your budget.\nThe solid line represents the spend constraint bounds that were set for the\noptimization and the plot indicates two points: the current spend level and the\nnew optimized spend level.\n\nRun the following command to plot optimized budget on response curves: \n\n optimization_results.plot_response_curves()\n\n**Example output:** (*Click the image to enlarge.*)"]]