![]() ![]() In this example, we’ll map your Facebook Ads cost data back to your customer performance data from Shopify. If you can identify what specific campaigns drive high-value customer acquisition over time, you’ve hit a gold mine. However, understanding the cost of acquiring a customer, and the lifetime value of that customer, is even better. Understanding the cost of each transaction is a good starting point. Why pivot cost and purchase metrics on the campaign dimension? In this case, we’re going to pivot data on the campaign dimension but note that the same principles apply to pivoting data on any other dimension. Pivot tables allow you to group data in a meaningful way and extrapolate a data-driven narrative that attributes performance back to specific campaigns, products, or other key dimensions over a given period of time. ![]() To answer these questions, pivot tables come in handy. Am I attributing conversions and/or revenue to the right campaigns?.What data do I need to look at to make informed decisions that will improve campaign performance?.This process will help when you’re asking questions, like: And that’s why having a clear process for analyzing your paid campaigns’ performance is critical. As digital marketers, we’re often experiencing data overload. ![]()
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