Chapter 12
What you can measure afterwards
 "Zoran Artmagic")
Table of contents
Better data is not an end in itself. It only pays off when it leads to better decisions. This chapter shows which goals and metrics become reliable with a clean data foundation and how to read them.
Macro goals and micro goals
A macro goal is a core business objective, such as more revenue from a product group or more new customers. Micro goals are the steps towards it: product view, cart, checkout started, newsletter sign-up. A good measurement plan captures both. The micro goals show where visitors are lost; the macro goal shows whether measures pay off in the end.
An example: winning back cart abandoners
According to a meta-analysis by the Baymard Institute, around seven out of ten visitors abandon a purchase they have started. Suppose a marketing team sets itself the goal of winning some of them back. That takes three things: measuring who abandons and at which point, reaching these visitors again through remarketing, email or push notifications, and measuring whether the win-back succeeds.
If measurement is missing for some visitors, for example Safari users after seven days, remarketing campaigns miss their target and their success is underestimated. With a clean data foundation, both the goal and its effect become verifiable.
Which metrics become more reliable?
Conversion rate per channel: When purchases are measured more completely and attributed correctly, it becomes clear which channels actually sell.
Cost per order and ROAS: The core metrics of ad steering only become meaningful with complete conversions.
Checkout drop-off rates: Measurable per step, so that optimizations can be targeted.
New versus returning customers: If you pass this information to Google Ads, you can steer new-customer acquisition specifically.
Longer purchase decisions: For high-priced products and in B2B, the decision often takes longer than seven days. Only with more stable cookies does it become visible which ad delivered the first contact.
How do you read engagement metrics in GA4?
Engagement rate and bounce rate: In GA4, a session counts as engaged if it lasts longer than ten seconds, includes a conversion event or has at least two page views. The bounce rate is the share of sessions that are not engaged.
Scroll depth: Shows whether content is being read. Low scroll depth on landing pages points to a message that misses the mark or to long loading times.
Exit pages: Exits on thank-you pages are normal; exits on intermediate pages in the purchase process are a warning sign.
And AI traffic?
More and more visitors reach stores via ChatGPT, Claude, Gemini or Perplexity. How to identify this traffic in GA4 and where the limits are is covered in the chapter Measuring AI traffic of our guide AI Commerce with Shopware (in German). A clean server-side setup is the foundation for this.
What you can define today
Write down your two or three most important macro goals and assign the micro goals that lead to each.
Check whether each of these goals is set up as an event in GA4 and as a conversion in your ad accounts.
Check whether your checkout measures every step as a separate event.
Frequently asked questions
Bounce rate measures sessions that are not engaged; exit rate refers to the last page of a session. A high exit rate on the thank-you page is normal; a high bounce rate on a landing page is a warning sign.