You have traffic. Where are the sales going?

Traffic with no sales is a diagnosis problem

The instinct when sales are flat is to buy more traffic. That is the expensive answer, and it is usually the wrong one — if a storefront converts at a fraction of what it should, more visitors means paying more to lose more. The cheaper question is which part of the visit is failing, and storefront visits fail in a small number of well-known places.

• The landing moment: the page does not answer why-this-product fast enough, and the visitor leaves in seconds
• The product page: price, shipping, sizing or trust questions go unanswered, and the answer exists further down than anyone scrolls
• The variant step: the option a shopper wants is out of stock, mislabelled, or takes too many taps on mobile
• The cart: shipping cost or a threshold appears late and reframes the whole decision
• The checkout entry: the shopper commits, hits friction, and does not come back

Why your analytics has not told you already

Your Shopify admin reports totals — sessions, conversion rate, revenue. Those are outcomes. They tell you the patient has a fever, not where the infection is. To locate the failure you need what happened inside the visit: where attention landed, how far people scrolled, what they clicked that was not clickable, and which step they were on when they gave up. That is behavioral data, and by default nobody is collecting it on your store.

• Totals tell you that something is wrong, never where
• Averages hide the segment that is actually failing — usually mobile
• A conversion rate is one number standing in for five different decisions
• The visit that left is the one carrying the answer, and it is gone unless it was recorded

How to find your leak this week

Work in this order. It is deliberately narrow — trying to look at everything at once is why most merchants abandon the exercise after two days.

• Split mobile from desktop before looking at anything. Most storefront traffic is mobile and most storefront problems are mobile-only.
• Take the funnel first: find the step with the steepest drop, and start there rather than at the page you personally dislike.
• Read the heatmap for that page. Look for what gets clicked that is not clickable, and what you built that nobody touches.
• Watch replays of sessions that reached that step and left, not a random sample. Ten targeted replays beat a hundred random ones.
• Compare converted against non-converted sessions on the same page. The difference between those two is your hypothesis.
• Change one thing, measure it against revenue, and only then move to the next.

How DynoWeb shortens that loop

Every step above is doable by hand, and merchants who do it get results. The problem is that it takes a week per cycle and the queue of found-but-unfixed problems grows faster than anyone ships. DynoWeb runs the diagnosis continuously, attaches a specific change to each finding so there is nothing to brief or schedule, and measures the revenue difference after the change goes live — so the loop closes instead of turning into a list.

• Heatmaps and replay scoped to your templates, split by device by default
• A funnel that shows which step loses the most visits, in order
• Each finding paired with a change you preview before shoppers see it
• Before-and-after revenue measurement on every applied change

When the problem is not your storefront

Sometimes traffic that does not convert is telling you something a CRO tool cannot fix. If your visitors arrive from a source that promised something the page does not sell, no amount of button-colour work will save the visit. The same is true when the price genuinely is not competitive, when stock is thin, or when the traffic is bot noise rather than people. We would rather you read that here than discover it after installing — the fastest way to check is to look at whether a specific segment converts fine while another is at zero. If every segment fails equally, look upstream.