Your GA4 shows a mobile conversion gap. Your heatmaps show scroll drop-off. Your surveys show buyers leaving confused. But none of those tools tell you what to test first — or why. Conversion Research reads them together and hands you a prioritised list, with the source evidence attached to every finding.
Most DTC teams already run GA4, a heatmap tool, an on-site survey, and some form of A/B testing. The problem isn't a gap in the tooling. It's that those tools don't talk to each other.
Conversion Research reads them together. It connects to your GA4 property, your heatmap data, your survey responses, and your form analytics — then runs a structured analysis across all of them to find where buyers are stalling and why.
You already have the pieces. This is what ties them into a single ranked list of what to test next, with the source evidence attached to every finding. See the full Conversion Research platform, how click and scroll heatmaps and survey analysis feed into findings, and how they connect to A/B Testing.
Tools already in your stack
Conversion Research
Ranked list of what to test next, with evidence
Conversion Research surfaces findings across the full buyer path — not just the checkout funnel. For DTC stores, findings consistently cluster into four zones:
Mobile PDP friction
Where scroll depth, tap targets, image gallery behaviour, and add-to-cart visibility combine to explain the desktop-vs-mobile conversion gap.
Checkout and cart drop-off
Field-level form analytics surface exactly where buyers exit the cart — shipping estimate reveal, account-creation friction, payment method gaps.
Collection and filter UX
Search-and-exit patterns, mismatched filter labels, and intent gaps between how you categorise products and how buyers describe what they want.
Homepage and traffic-source mismatch
For paid traffic especially: what the ad promises versus what the landing page delivers. The scent-and-message-match lens catches promise-to-page gaps that bounce-rate metrics can't explain.
Mobile image gallery exits before add-to-cart
Scroll maps show most mobile visitors never reach the CTA. Heat pattern suggests they're looking for size/fit info the desktop page surfaces in a sticky sidebar.
Shipping cost field is the top form abandonment point
Field-level drop-off spikes at the shipping estimate step. Visitors who see a cost above a threshold don't proceed — the offer is fine, the reveal timing isn't.
Filter UX is breaking intent on mobile collections
Search → collection → immediate exit pattern. Survey responses cite 'couldn't find what I was looking for.' Filter labels may not match how buyers describe the product.
The most common reason a DTC team starts using Conversion Research isn't a slow quarter — it's a moment where they need to move fast and can't afford to guess.
When paid acquisition costs climb and the margin on new traffic shrinks, the only lever left is conversion. Research tells you where to pull it.
Replatforms reset conversion baselines. A structured research run immediately post-launch surfaces friction the new UX introduced — before it costs you a season.
Peak traffic exposes every friction point at scale. Teams who run research in September find their Q4 tests already prioritised before traffic surges.
When a CEO, a board, or a funding partner asks what you're testing and why, a ranked, evidence-backed finding list is the answer — not a heuristic audit PDF.
If that's your first reaction, it's probably the right one.
Most DTC growth stacks are already overbuilt: GA4, a heatmap tool, a session recording tool, a survey platform, an A/B testing tool, and a CRO agency invoice sitting somewhere in the accounts payable queue.
Conversion Research doesn't add to that stack — it reads it. You connect the tools you already pay for, and it surfaces the signal those tools are generating but not surfacing on their own. The analysis layer you're currently doing manually, in a spreadsheet, across six browser tabs, is what this replaces.
What most teams cancel after 90 days:
The standalone session recording tool they weren't reviewing, the heuristic audit subscription they forgot to cancel, and the freelance CRO analyst they hired to write a findings doc once a quarter. Conversion Research runs that analysis on a schedule, automatically.
Once you have a finding, the next step is a test. Conversion Research connects directly to A/B Testing — a finding becomes a running experiment in one click. The AI variant editor writes the JS/CSS change from a plain-English description, so your team doesn't need a developer in the loop to ship the first variant.