Pattern/Modules/Analytics
Module · Analytics

Know what's hot, what's not, and what to do about it.

Real-time intelligence on your trade, at item, location and attribute level. Every insight connects to a decision: Monday morning, your findings ready, synthesised, prioritised, actionable.

Daily location/SKU ingestion Fashion-specific retail analytics Actions attached to insights
Our philosophy

Analytics should drive action, not just reporting. Every insight should connect to a decision.

The Pattern approach

For trading and planning leadership

The Monday meeting starts at the decision, not the data pull. Findings arrive synthesised and ranked by value at stake, with the whole team reading the same numbers.

For planners and buyers

Smart Metrics tailored in the board for you: what's hot, what's not, and the recommended trade action for each. Item and attribute level, against your own sales curves.

For the whole merch organisation

Boards and cards are organised by your retail planning structure, so analysis lives where teams already work, and key analysis that took a planner all day is ready in minutes.

Capabilities

Fashion-specific analytics, built for action.

Not another BI tool: retail science applied to your trade, with the next step attached.

Smart Metrics

Identify what's hot and what's not, with recommended trade actions attached. Ranked by revenue and margin at stake.

Fashion Forecaster

In-season and post-season trend analysis with actionable insights, against your own categories and curves.

Boards & cards

Designed for apparel teams and organised by your retail planning structure, not a generic dashboard grid.

Daily ingestion

Location/SKU sales and stock data ingested daily, so every view reflects yesterday's trade, not last month's extract.

Cross-team collaboration

Shared boards, call-outs and KPI summaries keep planning, buying and locations aligned on one version of the trade.

Attribute-level analysis

Trends surfaced at item and attribute level, styling, fabric, price point, so the signal is specific enough to buy against.

Stock health intelligence

Ageing stock, markdown risk and sell-through deviations surfaced before they cost margin, across the whole network, every day.

Margin & markdown defence

Exit and clearance timing sized by rand impact, so action lands while there is still a profitable lever to pull.

Outcomes

From insight to action, same day.

Analytics is measured on decision speed and decision quality: how fast a signal becomes a trade action, and how often it is right.

01
Trade decisions made same-day

When the analysis is waiting at 07:30, the trade meeting acts on Monday instead of confirming on Thursday. Speed compounds: a week earlier on every call, every week.

How Pattern does it
  • Findings synthesised and prioritised overnight, every trading day
  • Recommended actions attached to every signal
  • Key analysis ready in minutes, not a planner's full day
What it drives
  • Earlier in-season actions on winners and losers
  • Planner hours returned to judgment work
02
One trade truth across teams

Planning, buying and locations stop debating whose extract is right. Shared boards on one data foundation mean the debate is about the action, which is where the value is.

How Pattern does it
  • Boards and cards shared across teams, on one source of truth
  • KPI summaries and call-outs aligned to your planning structure
  • Same numbers from the trade floor to the exec review
What it drives
  • Aligned cross-team trading decisions
  • No reconciliation tax on every meeting
03
Growth and margin from acting on signals

The value of analytics is the trades it changes: the replen expedited while the trend climbs, the markdown taken early, the attribute weighted into next season's buy.

How Pattern does it
  • Hot/not signals at item and attribute level, with rand impact
  • Trend reads feeding assortment and OTB decisions directly
  • Post-season analysis closing the loop into next season's plan
What it drives
  • Growth and margin improvement
  • Better planning accuracy season over season
The shared foundation

Built on the Pattern Engine.

Generic BI shows you data and wishes you luck. Pattern Analytics sits on the platform's science and data layers, so its signals are retail-aware and its actions are executable.

1

Daily location/SKU ingestion into the shared data foundation, one clean model across sales, stock, on-order and plan.

2

Retail science engines supply the sales curves and benchmarks that turn raw movement into meaningful signal.

3

Plan context from MFP and Assortment means every signal is read against intent: on plan, ahead, or at risk.

4

Signals feed the Agent Planner, which turns the week's priorities into a ranked brief and executes fixes on approval.

05

Configured Workflows

Tailored to how you trade

04

AI Intelligence

Forecasting & reasoning

03

Retail Science Engines

Optimisation engines & methodologies

02

Data Foundation

Single extendable model, built for high-volume SKU retail

01

Data Ingestion

Any source system

Connected modules

The intelligence across the whole lifecycle.

Each module maps to a stage in the merchandise planning lifecycle. All draw from the same single source of truth, so what is decided here is already understood everywhere else.

← What flows in
Every module

Live positions from MFP, Item Planning, Assortment, Critical Path and Allocations, on one foundation.

Data foundation

Daily location/SKU sales and stock, plus attributes, weather and events.

Retail science engines

Sales curves, benchmarks and fashion-specific analytical methods.

What flows out →
Agent Planner

Prioritised signals that become the Monday brief and in-line actions.

Trend reads and post-season learnings that shape the next plan and range.

Trade actions, expedites, rebalances and markdowns, into execution.

See it on your own data

Start every Monday at the decision.

See Pattern configured on your own data in weeks, not months.