CRO & Analytics Case Study
CRO & Analytics · A/B Testing · Website Conversion Audit

CRO Case Study: Turning Increased Traffic into Actual Sales for a Skincare Brand

Skincare & personal care (D2C) · India · 3 months

Project Overview

Industry:

Skincare & personal care (D2C)

Service:

CRO & Analytics

Objective:

Identify and fix the specific points where visitors were dropping off before purchasing, so the brand's growing traffic (from its organic and influencer marketing phases) converted at a proportionally higher rate, not just a higher volume.

The brand had already solved its traffic problem through earlier branding, social and influencer work. This project addressed the next real bottleneck: what was happening — or not happening — once people actually landed on the site.

The Challenge

Traffic was growing, but revenue wasn't growing at the same rate:

Product pages had a high view count but a low add-to-cart rate, with no clear reason why from the traffic data alone

Checkout had a noticeable drop-off between "cart" and "order placed," but nobody knew at which specific step

The site had never been tested — every layout and copy decision was based on opinion, not visitor behavior

Mobile visitors, who made up the majority of traffic from the influencer phase, converted at a visibly lower rate than desktop visitors, with no investigation into why

No process existed to prioritize which page or step to fix first, so past changes were made reactively and without measurement

The challenge wasn't a lack of traffic anymore — it was that nobody had actually watched how real visitors were using the site, or tested whether a proposed fix would help before shipping it.

Research & Discovery

Before changing anything, we needed to see what was actually happening on the site, not guess from GA4 numbers alone:

  • • Heatmap and scroll-depth analysis (Hotjar) on the highest-traffic product pages, to see how far visitors actually scrolled and where they clicked or didn't
  • • Session recordings (Hotjar), reviewed specifically for mobile visitors, to watch real attempted interactions that failed — mis-taps, repeated scrolling, abandoned form fields
  • • GA4 funnel analysis, breaking the checkout process into individual steps to find the exact point with the steepest drop-off, rather than treating "checkout" as one stage
  • • Device and browser segmentation, to confirm whether the mobile conversion gap was a design issue, a performance issue, or both
  • • A review of existing product page copy and layout against what the session recordings showed visitors actually looking for and not finding

This stage turned a vague "conversion rate is low" problem into a specific, prioritized list of friction points — mostly concentrated in mobile product pages and one checkout step.

CRO & Measurement Setup

Before running any tests, we set a clean baseline so results could be attributed to specific changes, not general traffic growth:

  • ✓ GA4 goals and funnel steps configured to isolate add-to-cart rate, checkout step completion, and overall conversion rate as separate, trackable metrics
  • ✓ Hotjar heatmaps and recordings run for two full weeks pre-change, to establish a real behavioral baseline rather than a single snapshot
  • ✓ A/B testing set up in VWO, with traffic split evenly and tests run to statistical significance before any result was acted on, rather than ending tests early based on early trends
  • ✓ Segmented reporting by device (mobile vs. desktop), since the two were shown in research to behave differently and needed to be judged separately

This meant every result below is tied to a specific tested change, not a general "traffic grew so sales grew" effect.

Proven Case Study Impact
CRO & Analytics: +38% Add-to-Cart Rate

Turning the brand's growing traffic into a proportional increase in orders through data-driven, tested friction-point fixes.

CRO Strategy

1. Heatmap-Led Product Page Fixes

Used Hotjar data to identify that key product information (ingredients, usage instructions) sat below where most mobile visitors actually scrolled, and restructured the page to surface it earlier — then A/B tested the new layout against the original rather than assuming it would work.

2. Checkout Step Simplification

Used GA4's step-by-step funnel data to find the single checkout step with the steepest drop-off (an address-entry step with too many required fields) and tested a simplified version against the original.

3. Mobile-Specific Interaction Fixes

Addressed specific mobile friction points identified in session recordings — oversized tap targets that were hard to hit accurately, and a sticky add-to-cart button that wasn't visible on smaller screens — and tested each fix independently to confirm it actually helped before rolling it out.

4. Prioritized, Sequential Testing

Rather than testing everything at once, ran one test at a time on the highest-impact page first (based on traffic volume and drop-off severity), so each result could be clearly attributed to a specific change.

What We Did & When

Month 1 — Audit & Baseline
Set up Hotjar and GA4 funnel tracking, ran two weeks of heatmap and session recording data collection, and identified the prioritized list of friction points.
Month 1–2 — First Test: Product Page Restructure
Built and launched an A/B test on the product page layout, run to statistical significance in VWO.
Month 2 — Second Test: Checkout Simplification
Built and launched an A/B test on the identified checkout step, reducing required fields and simplifying the layout.
Month 2–3 — Third Test: Mobile Interaction Fixes
Tested the mobile-specific tap target and sticky add-to-cart changes identified from session recordings.
Month 3 — Results Review & Rollout
Reviewed all three tests for statistical significance, rolled out the winning variants permanently, and documented the process for future testing.
Before After
No heatmap or session data — decisions made on opinion Heatmap and session recording data driving every change
Checkout drop-off point unknown Specific step identified and tested
Mobile conversion gap unexplained Specific mobile friction points identified and fixed
Changes made without testing Every change A/B tested before permanent rollout
One blended "conversion rate" number Add-to-cart, checkout completion, and overall rate tracked separately
Results

Improvements came from fixing specific, data-identified friction points — not from a general site redesign or increased traffic.

Measured over 3 months. Source: Hotjar, GA4, VWO (A/B testing). Illustrative figures pending real campaign data.

+38%
Add-to-Cart Rate — winning product page variant vs. original, statistically significant in VWO.
+21%
Checkout Completion Rate — winning checkout variant vs. original.
+1.4 pp
Overall Site Conversion Rate — month 3 vs. pre-test baseline, via GA4.
3 Months
Measurement window — Hotjar, GA4, VWO, with each test run to statistical significance.
Business Impact
The brand's existing traffic growth finally translated into a proportional increase in orders, and the agency left behind a repeatable, tested process for future page changes — rather than a one-time fix that would need to be redone from scratch next time traffic grew again.
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