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This is a common problem. I can share how I go about it:
1. Categorize your metrics as primary north-star (e.g. Retention rate) vs. Secondary indicators usually used at a feature level (e.g. Click rate on alert emails).
2. The over-arching primary metric is what matters throughout while the secondary dials that you use to optimize it might change.
3. When you're shipping a new feature, there is an optimization time window (lasting a few sprints) where you're iterating on it to get to a certain benchmark you're happy with.
Note: There's a certain ROI you can get from a feature after which the law of diminishing returns kicks in.
4. Before you move to another feature, automate the tracking of the one you just worked on.
5. Create an alert on this to notify you when it oscillates anomalously below the benchmark. If say engagement on an email alert is constantly nosediving, it should come on your radar.
6. Understand the why. Then, decide whether if it's worth revisiting the feature or focusing on something else that will offset that deficit.
Moreover, as the product grows, so will your product team allowing you to delegate ownership.
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In an attempt to make this footer a bit interesting, here's a little PM joke:
A Product Manager tried walking into a bar...but couldn't when he realized the doorknob user story was still in the backlog.
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