For each metric, if you click the cog wheel, you can change the Metric Type (Standard/Total) and Attribution Model. Here, you’ll drag and drop dimensions (H), metrics (I) or segments (J) to create your calculated metric as well as the operators for the formula. This section is for display - as you build your calculated metric in section F, the formula will show here.į. If you’re using tags, which allow you to apply topics and quickly locate calculated metrics, add the tag(s) that apply here. Here, we’ll pick Currency for the Format, 0 for number of decimals, and ⬆ Good (Green) for polarity.ĭ. The metric format: Pick decimal, time, percent or currency, and add decimal places and polarity. For example, for Call Center AOV, we might add Calculates AOV for Call Center Assisted Orders.Ĭ. This description appears when users click the ‘ i’ beside the metric in the components list, so be sure it’s informative. This name is displayed in the metrics components list, so make it something that will be clear to yourself and others, like Call Center AOV.ī. Once the Calculated Metrics Builder opens, add and/or do the following:Ī. Or, you can click the + sign above Metrics in the Components panel. To open the Calculated Metrics Builder, use the top navigation to click → Components → Calculated Metrics → + Add. To build a calculated metric to answer this question, do the following: Imagine you want to understand if online self-serve users have a higher average order value (AOV) than call-assisted users. To get started with calculated metrics, let’s look at a simple example. The Calculated Metrics Builder can use a lot of different mathematical and statistical functions, so you can create metrics that answer even the most complex business questions. Today, I want to introduce you to calculated metrics, the next best tool in your analyst toolbox.Īs an advanced feature of Adobe Analytics, calculated metrics let you create new metrics without changing your implementation using the data you’ve already collected. Most new users of Adobe Analytics are familiar with Segments as a way to slice and dice their data.
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