Returns intelligence · Built for fashion

Your returns dataalready contains fraudsters

Fashion brands refund 35–55% of what they sell. We show you what that really costs — live, per style, per customer.

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Why this matters

Returns are the largest unmanaged cost in fashion e-commerce.

Every refund erodes margin, distorts product performance, and hides your most — and least — valuable customers. Most brands still manage this with spreadsheets and gut feel. RETIQLY AI turns your live order data into a single source of truth that finance, buying, and CRM can act on from day one.

Capabilities

What finance, buying, and CRM
have been asking for.

01

True Net Revenue

Gross revenue is a vanity metric in fashion. RETIQLY subtracts every refund — per order line, per SKU, per market — and gives you one verified net figure your whole team works from. No reconciliation. No month-end spreadsheets. No gap between finance and commerce.

02

Ask Anything, In English

"Which styles have return rates above 50% this season?" "Forecast returns for the next 30 days by market." "Show me customers who keep less than half of what they order." The AI agent runs the analysis across your full history and answers in seconds — with the data sources attached.

03

Fraud, Named and Evidenced

Three patterns, detected continuously: wardrobing (worn once, returned), size bracketing (three sizes ordered, two refunded), and deadline gaming (returns timed to your policy window). You get a named customer list, the order history that proves it, and a recommended action — not a risk score.

AB
04

Your Loyal Segment, Surfaced

Most brands have never cleanly separated their high-value, low-return customers from habitual returners. We do. Ranked list, ready to export to your CRM, with lifetime spend, return rate, and tenure attached. The VIP programme you couldn't build before.

05

Product Performance, Net of Refunds

Which styles actually earn money once refunds are counted? Net margin by style, size, and variant — refreshed daily. Catch the 80%-return style before the reorder. Spot the chronically under-bought winner. Stop buying the mirage.

06

Return Volume Forecasts

7 to 90-day forecasts with confidence intervals, adjusted for day-of-week and seasonal patterns. Warehouse plans staffing. Finance models cash. Customer service knows when the post-sale surge hits. All from the same forecast.

How it works

Connected in one session.
Live the next day.

Your rollout, end to end
1Your rollout
2
3  Day 1  One session, 60 minutes
4   Store connection made by our team (no dev work from yours)
5   Catalogue structure and category tree mapped
6   Return policy windows set per market
7   Your isolated environment provisioned
8
9  Day 2  Live
10   Full order and returns history processed
11   Net revenue calculated per order line, per product, per market
12   Customer loyalty and risk baseline established
13   Fraud pattern detection running across all orders
14   Private platform URL delivered to your team
Typical timeline
Platform

Your own environment.
Run entirely by us.

Every brand gets a fully isolated environment, provisioned and monitored by our team 24/7. Your data never touches another brand's environment at any level of the stack. You get a private URL, a dedicated platform, and zero infrastructure to manage.

100%
Data isolation
24/7
Monitored
< 80ms
Dashboard load
What's inside your platformAll systems operational
Executive Dashboard
Return health KPIs, revenue strip, anomaly alerts, AI recommendations
:Live
Net Revenue Intelligence
Gross vs. net by product, market, category — verified per order line
:Live
AI Agent
Plain-English queries across your full data — sourced answers in seconds
:Instant
Fraud Intelligence
Wardrobing, bracketing, deadline-gaming — named customers with evidence
:Automated
Loyal Customer Engine
Ranked loyalty segments — ready for CRM, retention, VIP programmes
:Live
Product Intelligence
Net margin by style, size curve analysis, reorder signals
:Live
Return Forecasting
7–90 day volume and rate forecasts with confidence intervals
:Daily
Anomaly Monitor
Z-score spike detection across your catalogue, every 15 minutes
:< 15 min
The problem in numbers

Returns are the
hidden P&L line.

Industry data|11:07:33 AM
$0B
Lost to return fraud and abuse globally every year — Appriss Retail, 2024
up to0%
Return rate on online fashion — peaks reach 88% on promotional lines — NRF, 2024
up to0%
Of an item's original price consumed processing a single return — Optoro
0%
Of online shoppers admit to size bracketing — ordering multiples, keeping one — Narvar
Works with your stack

Plugs into
the tools you already run.

No rip-and-replace, no data migration. RETIQLY connects to your existing commerce, OMS, ERP and CRM — and starts delivering intelligence from your full historical data on day one.

Centra
Commerce Platform
Shopify
Commerce Platform
Order Management
OMS Integration
ERP Systems
Finance & Stock
CRM Platforms
Customer Data
Buying Tools
Merchandise Planning
Warehouse Systems
Returns Logistics
BI & Reporting
Data Export
Returns Portals
Customer-Facing Returns
Email & Marketing
Customer Communication
Finance Systems
P&L Reconciliation
Analytics Suites
Data Enrichment
Centra
Commerce Platform
Shopify
Commerce Platform
Order Management
OMS Integration
ERP Systems
Finance & Stock
CRM Platforms
Customer Data
Buying Tools
Merchandise Planning
Warehouse Systems
Returns Logistics
BI & Reporting
Data Export
Returns Portals
Customer-Facing Returns
Email & Marketing
Customer Communication
Finance Systems
P&L Reconciliation
Analytics Suites
Data Enrichment
Analytics Suites
Data Enrichment
Finance Systems
P&L Reconciliation
Email & Marketing
Customer Communication
Returns Portals
Customer-Facing Returns
BI & Reporting
Data Export
Warehouse Systems
Returns Logistics
Buying Tools
Merchandise Planning
CRM Platforms
Customer Data
ERP Systems
Finance & Stock
Order Management
OMS Integration
Shopify
Commerce Platform
Centra
Commerce Platform
Analytics Suites
Data Enrichment
Finance Systems
P&L Reconciliation
Email & Marketing
Customer Communication
Returns Portals
Customer-Facing Returns
BI & Reporting
Data Export
Warehouse Systems
Returns Logistics
Buying Tools
Merchandise Planning
CRM Platforms
Customer Data
ERP Systems
Finance & Stock
Order Management
OMS Integration
Shopify
Commerce Platform
Centra
Commerce Platform
Security & privacy

Your data
stays your data.

Single-tenant by default. Your orders, customer records and performance data are never shared, never commingled, and never used to train models that serve another brand. If your CISO has a question, we've already answered it.

SOC 2 AlignedSingle-TenantEncrypted at RestRole-Based AccessFull Audit Log

One brand per environment. No exceptions.

Your environment is provisioned exclusively for your brand. No shared databases, no shared compute — no path from your data to another customer's environment at any layer of the stack.

Role-based access, mapped to your org.

Finance, buying, merchandising, e-commerce and CRM each see what belongs to them. Granular permissions keep sensitive customer and margin data visible only to the people who should see it.

Your data trains your platform. Only yours.

Your return patterns, customer behaviour and performance data power your own intelligence — and nothing else. We don't aggregate, share, or cross-train across brands. Ever.

Every query and access event, logged.

Every AI query, alert trigger and data access event writes to an immutable audit log. Your compliance and security teams get full, permanent visibility.

Intelligence, by team

One platform.
Every team aligned.

RETIQLY isn't a tool for one analyst. For the first time, buying, merchandising, finance, e-commerce and CRM all work from the same live numbers — the same net revenue, the same fraud list, the same loyal segment. No reconciliation meetings required.

Net revenue verified per order line

Every refund subtracted, per SKU, per market — automatically. One number your whole finance team trusts.

Loyal customer ranking

Your best customers identified by real retention, real spend and real return behaviour. The segment your CRM has never reached.

Product performance net of refunds

Which styles actually earn money and which are margin illusions. Net margin per SKU, updated every sync.

Three-pattern fraud detection

Wardrobing, bracketing and deadline gaming — each with its own behavioural logic and evidence-backed suspect list.

Return volume forecasting

7 to 90-day forecasts with confidence intervals. Operations, warehouse and finance plan ahead instead of reacting.

Anomaly detection every 15 minutes

Z-score spike detection across your full catalogue. You know about a return surge before customer service does.

Net revenue intelligence  Finance team
"Net revenue after refunds for Q1,
  broken down by market?"
 Germany:  22.1M kr gross   8.4M kr net  (62% refunded)
  UK:       10.8M kr gross   4.9M kr net  (54% refunded)
  Sweden:    9.1M kr gross   4.2M kr net  (54% refunded)
  Full breakdown ready for board pack.
"Forecast returns for the next 30 days."
 14,20015,800 returns expected (90% CI)
  January post-sale spike factored in.
  Peak day: Tuesday, week 3.
What fashion teams are saying
01 / 04

"I asked for net revenue after refunds for last quarter, broken down by market. The answer came back in seconds — verified, sourced, ready for the board pack. Previously that was a week of work and three spreadsheets that never quite reconciled."

F

Finance Director

Finance Director, European Fashion Brand

Result

A week's work in seconds

Trusted by forward-thinking fashion brands

Meridian FashionFlux RetailBeacon BrandsPrism GroupNova CollectionsAtlas FashionVertex RetailOrbit Studios
Meridian FashionFlux RetailBeacon BrandsPrism GroupNova CollectionsAtlas FashionVertex RetailOrbit Studios

See what your
real numbers look like.

Most fashion brands manage returns with spreadsheets, gut feel, and data that's already weeks old. RETIQLY AI gives buying, merchandising, finance and e-commerce one live source of truth — from the first week, not the first quarter.

Dedicated environment · Onboarding included · Live within days