Case studies — real stores, real numbers
See what DynoWeb finds in real Shopify stores
Every figure below is pulled straight from production — no rounding up, no invented lift. From 52,370 rage clicks on a high-volume wellness brand to live JavaScript errors silently breaking a furniture store, here's what DynoWeb surfaced and what each merchant did about it.
- Real production data
- Attributed to exact sessions
- AI-ranked fixes
- Updated June 2026
The Punarvasu
Ayurvedic wellness brand · India
How The Punarvasu caught 52,370 rage clicks across 3,132 orders with DynoWeb
The Punarvasu sells Ayurvedic formulations like Gandharva Haritaki and Madhumehari Churna to a high-volume, mobile-first Indian audience — over 34,000 page views and 837,250 tracked interactions all-time.
3,132
orders · ₹10.85L tracked sales
837K
interactions captured all-time
52,370
rage clicks caught
The challenge
Sales volume looked healthy — but underneath it, shoppers were fighting the storefront. DynoWeb counted 52,370 rage clicks and 15,288 error clicks across 837,250 interactions: classic high-effort, low-reward frustration.
The AI engine didn’t just total it up — it localized the pain, flagging “frustration cluster detected” and “users seem confused” on specific pages like the Gandharva Haritaki Tablet PDP, the Madhumehari Churna PDP, the homepage, and the cart.
How DynoWeb helped
- Frustration signals — surfaced 52,370 rage clicks + 15,288 error clicks and grouped them into named clusters.
- AI CRO suggestions — 52 ranked fixes (44 Quick Wins) — from a mobile sticky add-to-cart bug to missing Product JSON-LD.
- Revenue attribution — matched 1,154 orders worth ₹4.28L back to the exact tracked sessions that drove them.
Inside the data — what DynoWeb actually caught
The Gandharva Haritaki Tablet page was the epicentre
DynoWeb stacked three separate flags on that one PDP — a frustration cluster (score 89), a 'users seem confused' alert (83), and a mobile sticky add-to-cart bug (79).
It was a mobile problem first
88% of page views came from mobile (29,881 of 34,078). The rage clicks and the broken sticky add-to-cart hit the phone experience hardest.
Even the homepage and cart had clusters
Frustration clusters weren't only on product pages — DynoWeb flagged them on the homepage, the /cart page, and a Hindi blog post too.
At a ₹346 AOV, every drop-off compounds
With 3,132 orders at a ₹346.46 average, friction spread across 52,370 rage clicks quietly scales into real lost revenue.
The catalog was invisible to AI search
The top-scored fix (95) was missing Product structured data (JSON-LD) across all product pages — leaving the range unreadable to AI shopping assistants.
It also found what to amplify
Not just problems: DynoWeb flagged a high-performing element (#checkout2) on the Gandharva Haritaki page to lean into, backed by 14 CRO reports across 200 analysed pages.
The impact
1,154
orders attributed to a tracked session
₹4.28L
sales tied to exact sessions
44
Quick-Win fixes ready to ship
“We thought our volume meant the store was fine. DynoWeb showed us tens of thousands of rage clicks — and exactly which product pages were causing them.”
Illustrative — framed from the data DynoWeb surfaced
Sahasika
Men's ethnic wear · India · Facebook-driven D2C
How Sahasika turned 598 session replays into ₹97,767 of converting sessions with DynoWeb
Sahasika is a mobile-first men's ethnic-wear label (kurta sets and more) pouring paid social into acquisition — ₹9.8L of referral revenue, with Facebook alone driving 11,372 visits.
598
session replays captured
₹97,767
revenue in converting replayed sessions
₹3.97L
sales attributed to exact sessions
The challenge
Sahasika was spending hard on Facebook — ₹9.8L in referral revenue across 20,666 visits — but couldn’t see where that expensive traffic was getting stuck.
DynoWeb found the friction: 40,324 rage clicks, plus 1,067 JavaScript-error hits across 63 distinct issues — including “the string did not match the expected pattern” firing 285 times on the Mens Kurta Sets collection and repeated load failures on key product pages.
How DynoWeb helped
- Session replays — 598 recordings captured; 35 of them converted, worth ₹97,767 — the exact journeys that ended in a sale.
- Error tracking — caught 1,067 JS-error hits across 63 issues, pinned to the precise URLs they broke on.
- AI CRO suggestions — 64 fixes (5 already implemented) led by missing Product structured data and title tags.
- Revenue attribution — tied 162 orders worth ₹3.97L back to the sessions that produced them.
Inside the data — what DynoWeb actually caught
The Mens Kurta Sets collection was a bug magnet
The same 'string did not match the expected pattern' error fired 285 times on that collection — while AI separately flagged poor visibility of its search, sort, and 'open sidebar' controls.
Autofill and load failures on paid product pages
The Mens Off-White PDP alone logged Fetch-aborted (105), an autofill ReferenceError (84), and Load-failed (75) — friction on the exact pages Facebook ads pointed at.
Sessions were long and effortful
Replays averaged 311 seconds with an average frustration score of 32.7 — these were shoppers working hard, not browsing happily.
Returning shoppers were the most valuable
Returning customers posted the highest AOV (₹2,834 vs ₹2,778 for new) — a small, high-value segment worth protecting from the friction.
A custom checkout was hiding revenue
With Shopflo handling checkout, script-only tools miss orders — yet DynoWeb still tied 162 orders / ₹3.97L back to their originating sessions.
A structured-data and barcode backlog
Missing Product JSON-LD, missing title tags, and 50 products without barcodes all topped the fix list at score 95.
The impact
35
replayed sessions that converted
₹97,767
revenue in those sessions
1,067
JS-error hits caught
162
orders attributed (₹3.97L)
“DynoWeb let us watch the sessions that actually converted — and caught over a thousand JavaScript errors we never knew were firing on our paid traffic.”
Illustrative — framed from the data DynoWeb surfaced
Skyline Decor
Home & furniture retailer · USA
How DynoWeb caught 33 live errors breaking Skyline Decor's product pages
Skyline Decor sells dining tables, patio sets, and vanities to a US audience. The store looked fine on the surface — until DynoWeb started listening to the storefront itself.
297
error hits caught on the storefront
33
live errors (32 JS + 1 broken link)
14
visits already arriving from ChatGPT
The challenge
Skyline’s product pages were throwing real JavaScript errors — and nobody knew. DynoWeb logged 32 distinct JS errors over 297 hits, including “Uncaught SyntaxError: Unexpected token ‘=’” 42 times on a product page and “Importing a module script failed” 39 times on another.
At the same time, AI search engines were starting to send traffic — 14 visits from ChatGPT, plus Bing, DuckDuckGo and Brave — making it critical that product data be readable and error-free for the crawlers and assistants now shopping on customers’ behalf.
How DynoWeb helped
- Storefront error tracking — surfaced 32 JS errors across 297 hits with the exact message and the exact product URL each one broke on.
- AI-search (GEO) readiness — flagged the store as already drawing ChatGPT traffic — and what to fix so AI assistants can read and cite its products.
- Session replays — 19 recordings captured so the team could watch the broken experiences first-hand.
Inside the data — what DynoWeb actually caught
The Baxton Studio PDP was failing two ways at once
The same product page threw both 'Importing a module script failed' (39 hits) and 'undefined is not an object' (29 hits) — a broken script cascading into a broken page.
These were hard parse failures, not glitches
'Uncaught SyntaxError: Unexpected token =' (42 hits) and 'Unexpected end of input' (12) mean the JavaScript literally won't run — on live product pages.
Browsing broke before the product even loaded
Collection pages weren't spared — dining-tables and patio collections logged network and module-script failures of their own.
ChatGPT is already sending shoppers
14 visits came from chatgpt.com — more than Bing, DuckDuckGo and Brave combined — making error-free, readable product data a present-tense priority.
The breakage hit desktop and mobile alike
Page views split 293 desktop to 269 mobile, so the errors degraded the experience for both audiences equally.
Caught early, before launch-scale traffic
DynoWeb surfaced all of this at just 118 sessions this month — the cheapest possible moment to fix a broken storefront.
The impact
32
JS errors surfaced with exact pages
297
error hits logged
ChatGPT
now a tracked traffic source (14 visits)
“We had no idea our product pages were throwing syntax errors. DynoWeb handed us the exact message and the exact page — before it cost us the sale.”
Illustrative — framed from the data DynoWeb surfaced
Yetibeds
Online furniture retailer · beds, bunk beds & more
How one heatmap showed Yetibeds shoppers were clicking the wrong thing
Yetibeds sells beds, bunk beds, chairs and dining sets to a desktop-heavy audience. Traffic was climbing fast — page views ▲95.1% and sessions ▲81.4% month over month — but something on the homepage was quietly costing conversions.
Mouse Shake
the #1 behavioral signal store-wide
14%
scroll depth on the homepage
100%
of tracked sales attributed to the exact session
The challenge
The store’s most common signal wasn’t a click — it was Mouse Shake, the cursor-thrashing that means confusion, with Dead Clicks close behind. Pages were logging interaction rates over 1,000% (shoppers clicking many times per view) yet converting poorly.
The killer detail came from the homepage heatmap: clicks and mouse-shake were clustering on the decorative hero image, not the SHOP NOW button — and only 14% scroll depth meant most visitors never got past the hero. Meanwhile 74 returning visitors came back and didn’t buy.
How DynoWeb helped
- Heatmaps — the homepage click map exposed shoppers tapping the hero artwork instead of the CTA — a single screenshot that explained the drop-off.
- Behavioral signals — ranked Mouse Shake as the store's #1 signal and tied >1,000% interaction rates to real frustration clusters.
- AI CRO suggestions — matched 42 concrete fixes (40 Quick Wins) — from Product structured data and alt text to the confused-hero flags.
- Revenue attribution — attributed 100% of tracked sales to the exact session that drove them, on a fast-growing month.
Inside the data — what DynoWeb actually caught
The homepage hero is a trap
141 mouse-shakes and 26 dead clicks landed on the Home hero, where scroll depth was just 14% (13% above the fold) — visitors poked the decorative image and left before reaching the products.
1,457% interaction on /products_preview
The most-viewed page logged 1,501 clicks across 103 views — frantic, repeated clicking that's a textbook rage pattern, not engagement.
Search was carrying the load
/search saw 687 clicks across just 27 views (2,544% interaction) — shoppers couldn't find products by browsing, so they hammered the search bar.
One PDP proves the catalog can convert
The Barnstorm upholstered-bed page turned 1 of 2 buy-intent clicks into a $559 order — a 50% page conversion rate when the path was clear.
An unusual desktop-and-India profile
91% of sessions were desktop and 76.6% of visits came from India — a profile DynoWeb surfaces so the team optimises for the audience it actually has.
42 fixes on a store the owner thought was 'done'
Beyond the hero: missing Schema.org data, 50 products without barcodes, and missing alt text — invisible-to-AI-search gaps, 28 already surfaced as ready to review.
The impact
42
AI fixes found (40 Quick Wins)
▲95.1%
page views month over month
▲81.4%
unique sessions month over month
100%
tracked sales attributed
“One heatmap told us everything: our shoppers were clicking the pretty hero image, not the Shop Now button — and most never scrolled past it.”
Illustrative — framed from the data DynoWeb surfaced
All figures are real, pulled from DynoWeb production data on 6 June 2026. Story framing is ours; the numbers are not.
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