Get code diffs, not a dashboard screenshot
If you are the person who has to implement the change, a chart of what is wrong is only half a ticket. The other half is the diff.
- MCP access
- Reviewable diffs
- Theme-aware changes
Analytics hands you a finding. Someone still has to turn it into code.
The standard CRO workflow ends where engineering work begins. A tool surfaces an insight, the insight becomes a screenshot in a ticket, and a developer then has to reverse-engineer what was meant, find the relevant section of the theme, and guess at the intended change. Most of the cost of a CRO programme lives in that translation step, and none of it is visible in the tool that generated the finding. It is also where fixes go to die: a finding that takes three days to implement competes with everything else in the sprint, and usually loses.
Get code diffs and MCP access instead of a dashboard screenshot.
Findings that arrive without a change attached
An observation you have to interpret before you can act on it is a task you have not been given yet. The useful unit is the proposed change, in the file it belongs in.
Tickets that say 'improve the product page' with a heatmap image attached.
Context living outside your tooling
If store behaviour data only exists in a dashboard, every question about it is a context switch. Over MCP the same data is available to the assistant already in your editor.
Alt-tabbing to a dashboard to answer a question mid-implementation.
Changes that cannot be reviewed before they ship
Anything that edits a live storefront should be reviewable in the same way any other change is: see the diff, understand the blast radius, approve or reject.
A tool that applies changes without showing you what it changed.
No baseline attached to the change
Shipping a fix without a measurement plan means the next conversation about whether it worked is an opinion contest. The measurement should be part of the change, not a follow-up task.
Nobody can say whether last quarter's fixes did anything.
Three steps, no developer required
- Step 01
Connect over MCP
Point Claude, Cursor or ChatGPT at your store data through MCP Integration and query behaviour from the tool you already have open, instead of from a browser tab.
- Step 02
Take the diff, review the diff
Suggestions come with the concrete change attached and a preview before anything touches the live storefront. Approve what is right, reject what is not.
- Step 03
Let attribution close the loop
Each applied change gets measured against its own baseline, so the record of what worked builds itself rather than depending on anyone remembering.
The parts of DynoWeb this leans on
Shopify for Developers, answered
- Does it edit my theme without asking?
- No. Changes are proposed and previewed; applying one is an explicit approval. The agent does the drafting, you keep the merge button.
- Which MCP clients are supported?
- Claude, Cursor and ChatGPT. The integration exposes your store's behavioural data as tools those clients can call, so you can ask questions in context rather than exporting anything.
- Do I need to install a tracking snippet?
- No. DynoWeb installs as a Shopify app and collects on your existing theme — no snippet to paste, no tag manager, and nothing to keep in sync when the theme changes.
- Can I use this alongside our own analytics stack?
- Yes. Nothing here asks you to move off what you already run. The value is the behavioural layer and the proposed change, both of which sit alongside whatever reporting you already trust.
Most stores have more than one of these
- Increase Product Page ConversionsTurn product page attention into add-to-carts.
- Shopify Mobile OptimizationFix the mobile experience where most of your traffic actually is.
Or browse all four use cases.
Stop guessing. Fix it and see the money.
Install DynoWeb on your Shopify store and see your first findings within a day of normal traffic.
Questions first? Talk to us or read the merchant stories.