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// For Footwear Brands

Footwear Planning Lives and Dies by the Size Run.
RetailNorthstar Plans It Natively.

Footwear merchandising planning software is planning software that models assortments, open-to-buy, and allocation at the size-run level — pairs by size and width, not just units by style. RetailNorthstar is an apparel-first platform: our flagship customers are apparel brands, and the same style-color-size data model that applies a size curve to a knit top applies a size run to a runner.

For mid-market and emerging footwear brands, that means curve-based buying, core vs seasonal logic, and prebook-plus-DTC planning without forcing footwear into an apparel-shaped workaround.

What makes footwear planning uniquely hard

Footwear concentrates risk differently than apparel: fewer styles, deeper pairs, longer tooling lead times, and a size dimension that decides whether a style sells at full price. Every buy is a curve decision — and generic planning tools do not model curves.

Size runs and width runs

A single style-color can carry 8–15 sizes, often with half sizes and widths on top. One style-color holds more SKUs than most apparel styles — which means a footwear buy is never really a quantity decision. It is a curve decision.

Broken size runs kill full-price selling

Once the core sizes of a run sell out, the remaining pairs drift toward markdown no matter how strong the style is. Size-level sell-through visibility — knowing which sizes are breaking, in season — is the difference between protecting full price and clearing broken runs.

Size-curve buying discipline

Curves differ by category — athletic, dress, boot — and again by gender and channel. Teams that buy on receipt history instead of sell-through history bake last season’s error into next season’s buy, and the error compounds season over season.

Core styles vs seasonal drops

A core runner or boot carries over for years while fashion styles rotate by drop. Drop calendars do not map cleanly onto seasonal resets, so planning both on one seasonal logic forces one of them into a workaround.

Depth-heavy buys, high MOQs

Footwear assortments run fewer styles at deep pairs-per-style-color. Lasts, molds, and tooling mean long lead times and near-zero in-season reorder except on core — so the initial curve and depth decision has to be right the first time.

Wholesale prebooks plus DTC drops

Key-account prebooks lock quantities months out while DTC needs launch-day depth on the same styles. Size-level fill rate on wholesale orders is an account scorecard metric — miss sizes on a prebook and it shows up in next season’s order.

Where generic planning tools force workarounds

General retail planning platforms treat size as an afterthought. In RetailNorthstar, size runs, curves, and drops are first-class objects in the data model — not configuration built on top of it.

Size-run modeling

Generic tool

A spreadsheet tab per size, maintained outside the planning tool

RetailNorthstar

Native size curves — enter the buy once, explode it to size-level pairs

Curve source

Generic tool

Receipt-based — curves copied from what was bought last season

RetailNorthstar

Sell-through-based — curves built from size-level selling by category, gender, and channel

Core vs seasonal styles

Generic tool

One planning logic forced onto both

RetailNorthstar

Carry-over and newness logic built in — core and drop styles plan on separate cadences

OTB by season and drop

Generic tool

Drops shoehorned into a monthly OTB via workarounds

RetailNorthstar

Native — open-to-buy tracked by season and by drop

Broken-run visibility

Generic tool

Manual pivot tables, usually after the run has already broken

RetailNorthstar

In-season size-level sell-through, surfaced before core sizes sell out

Buy depth per style-color

Generic tool

Manual recalculation every time a curve changes

RetailNorthstar

Curve-applied quantities tied to the assortment plan — change the curve, the buy updates

The footwear planning workflow in one connected system

From open-to-buy through size-level allocation — prebooks, drops, core replenishment, and curve-applied buys in one model, not a set of reconciled spreadsheets.

Where RetailNorthstar fits footwear — honestly

Apparel is our flagship vertical. RetailNorthstar's customer base today is apparel brands, and we do not have footwear customers or case studies to show you yet. We would rather say that plainly than invent proof.

What footwear teams evaluate is the data model. RetailNorthstar is style-color-size native — the hierarchy footwear planning actually runs on. Size curves, carry-over logic (see carry-forward), drop calendars, and channel-split buys are the same primitives whether the curve has five positions or fifteen. The honest question is whether that model fits your size-run reality — and the right way to answer it is a working session with your own size-level sell-through data, not a slide deck.

If you want to pressure-test the math first, start with the size-curve allocation formula and the sell-through rate formula, or browse every industry we plan for.

Live in weeks, not next season

Onboarding is run by your merchandising team — no IT project, no implementation partner. Your size-level history becomes the baseline for curves and forecasts during setup.

01
Access and initial setupDay 1

Planning hierarchy configured — categories, drop calendar, channels, and financial targets.

02
Size-level history importDays 3–7

Sales and inventory history imported in pairs by size, building sell-through-based curves per category, gender, and channel.

03
Team trainingDays 7–10

Planning and buying teams trained on OTB, assortment, and curve-applied buy workflows.

04
Parallel validationWeeks 2–3

Plan an upcoming drop or prebook window in RetailNorthstar alongside your current process and compare outputs.

05
Full cutoverWeeks 3–4

Retire the size-tab spreadsheets. Plan the next buy entirely in RetailNorthstar.

Footwear planning questions

Does RetailNorthstar handle footwear size runs and widths?

Yes. Size is a first-class dimension in the RetailNorthstar data model, not an attribute bolted onto a style record. A style-color can carry a full run of 8–15 sizes including half sizes and width variants, curves are stored by category, gender, and channel, and buys are planned and tracked in pairs at the size level. Changing a curve updates the size-level quantities across the buy without manual recalculation.

Can core styles and seasonal drops be planned differently?

Yes. Core styles that carry over for multiple years plan on carry-over logic — rolling forecasts and replenishment against a stable size curve. Seasonal styles plan by drop, with their own delivery windows, depth decisions, and open-to-buy. Both live in the same connected assortment plan, so total pairs, spend, and margin roll up across core and seasonal without maintaining two separate models.

Most RetailNorthstar customers are apparel brands — does it really fit footwear?

An honest answer: apparel is the flagship. RetailNorthstar’s customer base today is apparel brands, and we do not have footwear case studies to point to yet. What we do have is a data model that is style-color-size native — and footwear shares that structure. A size run is a size curve with more positions and higher stakes, and curve-based buying, drop calendars, and channel splits are the same planning primitives. We recommend evaluating fit in a working session with your own size-level data rather than taking claims on faith.

How are wholesale prebooks and DTC drops planned together?

Prebooks are treated as committed demand at the size level — key-account quantities lock months before delivery and flow into the buy as fixed pairs per size. DTC launch depth is planned separately from the sell-through forecast and the channel’s size curve. Both roll up into a single buy per style-color, so total pairs against MOQs are visible in one place, and size-level fill rate on wholesale orders is tracked as its own metric.

Explore More

Plan the size run natively. Live in weeks.

See how RetailNorthstar handles size curves, core vs seasonal styles, OTB by drop, and prebook-plus-DTC buys — with your own size-level data.

Connected merchandise planning — live in weeks, not quarters.