How to Automate Conversion Fixes with GitHub Pull Requests

Automating conversion fixes means turning "analyse, decide, implement" into a pipeline that ends in a Pull Request, not a deploy. The steps are: read analytics to find the biggest leak, generate one scoped code change, open a PR that explains the data and the reasoning, run CI and a preview, and require a human merge. The automation does the work; you keep the decision.

The pipeline

A trustworthy automation has five stages, and the order matters:

1. Read the data. Pull funnel and behaviour data — where do people drop off, how far do they scroll, what do they click? The fix has to be grounded in what visitors actually do, not a guess about the layout.
2. Find the single biggest leak. Not a list of twenty ideas — the steepest drop, where a fix has the most leverage.
3. Generate one scoped change. A specific, reviewable edit addressing one hypothesis: move the CTA above the fold, shorten the form, fix the layout shift. One change, one hypothesis.
4. Open a Pull Request that explains itself. The PR body states the problem, the data behind it, and what the change does — so a reviewer can judge it in a minute.
5. Gate on CI, preview, and a human merge. Tests and types run on the PR; a preview deploy lets you click the change; you merge or close.

Why it ends in a PR, never a deploy

The temptation is to close the loop fully — analyse, change, and ship. Don't. Conversion changes touch live revenue surfaces and sometimes backfire (a "cleaner" form that quietly drops a trust signal, say). The Pull Request is what makes automation safe:

• CI catches breakage before it reaches anyone.
• A preview lets a human see the change in context.
• The merge is a human decision, so nothing ships silently.

Automating the analysis and implementation is the valuable part. Automating the merge throws away the safety that makes you willing to run it at all.

Scoped changes are the unit of work

The pipeline only works if each change is small and singular:

Good:  "Move the hero CTA above the fold (median scroll is 41%)."
Bad:   "Redesign the landing page."

A scoped change is reviewable, its impact is attributable (you know what moved the number), and it's trivial to revert if it backfires. A sprawling change mixes effects together so you can never tell what helped — which defeats the point of running this weekly.

Keep a record of what changed and why

Each PR is also documentation: a dated, reviewable record of a hypothesis and its result. Over time that history tells you what works on your site — which is far more valuable than generic best practices.

From pipeline to product

You can build this yourself — wire your analytics to a script that opens PRs — or use an agent that does it. Either way, the principles hold: ground fixes in data, keep changes scoped, and never remove the human merge. That's exactly the pipeline Velyr runs: each week it finds your biggest conversion leak, writes one scoped fix, and opens it as a Pull Request for your approval.