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Assortment planning and the Assortment Curator agent

Assortment planning decides which products a retailer carries, in which stores and channels, and in what breadth and depth. This guide covers how planners build an assortment today, the arithmetic that limits a range, and how the OODARIS Assortment Curator agent proposes the range for each store cluster.

By Fatih Nayebi, Founder and CEO of OODARIS. Updated .

What assortment planning is

Assortment planning is the process of choosing the mix of products a retailer will offer in a season or period, and where each product will be offered. It answers questions such as how many styles to carry in each category, which ones, in which colors and price points, in which stores and channels, and how deep to buy each one.

A few terms come up in every assortment conversation:

  • Option: a style in one color. A black leather loafer and a tan leather loafer are two options of the same style.
  • Breadth: how many different options a category carries.
  • Depth: how many units of each option are carried, including the spread across sizes.
  • Store cluster: a group of stores with similar sales volume, climate, space or customers that receive the same range.
  • Line review: the meeting where merchants and planners decide which options to keep, add and drop.

Assortment planning sits between the money and the units. Merchandise financial planning sets the sales and inventory budget for a category. The assortment plan decides which products fill that budget in each cluster. Allocation then decides how many units of each product go to each store, in which sizes.

How assortment planning is done today

Before a season, merchants and assortment planners review last season by style and by attribute: what sold through at full price, what needed markdowns, what ran out early. They combine that with trend input, vendor offers and the financial plan to draft a range. Stores are grouped into clusters, usually by sales volume and climate and sometimes by customer profile, and each cluster gets a range sized to its space.

The draft is then argued through line reviews. Each option is defended or cut, and the outcome is a range plan: which options go to which clusters, with planned units. Much of this lives in spreadsheets and slide decks, and the line review pack is often assembled by hand from several reports.

The common weak points are well known to anyone who has sat through a line review:

  • Ranges are localized only at a coarse level, so every store in a large cluster gets the same products.
  • Space is checked late, and allocation finds there is no room for the depth that was bought.
  • Decisions lean on last season’s top sellers, which may not repeat.
  • The reasons behind adds and drops are not written down, so next season the argument starts again from scratch.

Breadth, depth and space: a worked example

Space and depth together cap how many options a store can carry. Take a cluster whose stores have room for about 360 pairs of women’s boots, on the floor and in the stockroom. To present a full size run, each option needs at least one pair in each of six sizes and two pairs in the four core sizes: 10 pairs per option.

Maximum options = capacity ÷ minimum units per option = 360 ÷ 10 = 36

If the category plan calls for 30 options at that depth, the range fits with room to chase. If merchants want 45, something has to give: fewer options, shallower depth that risks broken size runs, or space taken from another category. Working this out at the assortment stage is cheaper than discovering it during allocation.

The cluster’s capacity in options: 360 pairs at 10 pairs per option, against a plan of 30 options and an ask of 45 (illustrative numbers)

The main performance measure in a line review is sell-through: units sold divided by units received, for a set period. An option that received 1,200 units and sold 840 at full price in its first eight weeks has a full-price sell-through of 70%. Comparing sell-through by cluster and by attribute (color family, heel height, price point) shows which products travel and which are local.

Eight-week full-price sell-through for three options in one cluster, and the line review outcome (illustrative numbers)
OptionUnits receivedUnits sold at full priceSell-throughOutcome
Chelsea boot, black1,20084070%Keep, buy deeper
Leather loafer, black90054060%Keep
Leather loafer, tan90027030%Drop in this cluster

Sell-through alone can mislead. A low number may mean the option was over-bought, sent to the wrong cluster, or broken in its core sizes early. Good line reviews read sell-through next to depth, size availability, margin and the markdown that would be needed to clear what is left.

Building an assortment plan, step by step

  1. Start from the money. Take the sales, margin and inventory budget for each category and cluster from the merchandise financial plan, so the range is sized to what the business can afford to hold.
  2. Review the last comparable season. Rank options and attributes by full-price sell-through, rate of sale and margin, cluster by cluster, and note which results were distorted by stockouts or late deliveries.
  3. Set the cluster structure. Decide which stores share a range, and check that each cluster’s space and depth limits are known before any option is chosen.
  4. Draft the range. For each cluster, decide which options to keep, which to add from new lines and trend input, and which to drop, with breadth and depth that fit the space.
  5. Review and approve. Take the draft through the line review with merchants, buyers and planners, and record the reason for each add and drop.
  6. Hand over to buying and allocation. The approved range by cluster sets what buyers order within open to buy and what allocation plans to send.

In season, the plan is not finished. Early sell-through on new options tells the team where to chase, where to stop reordering, and which clusters should swap options before the season ends.

Measures assortment planners use

  • Sell-through: units sold as a share of units received, at full price and overall.
  • Rate of sale: units sold per store per week, which compares options with different store counts.
  • Gross margin and GMROI: what an option earns for the inventory it ties up.
  • Weeks of supply: how long current stock lasts at the current rate of sale.
  • Attribute performance: sales and sell-through by color, fabric, fit or price point, across options.
  • Exit risk: how much of an option is likely to need a markdown to clear by the end of its life.

Short definitions of these measures are in the retail planning glossary.

How the OODARIS Assortment Curator agent works

In OODARIS, assortment is one of the ten capabilities the Agentic OS covers, and part of how OODARIS applies agentic AI to retail planning. The Assortment Curator is the specialist agent for it.

  1. WatchesSell-through, attribute performance and space, by store cluster.
  2. ProposesAdds, keeps and drops for each cluster, with the reason for each.
  3. Approved byAssortment planning, with the buyer.
  4. Writes backThe approved range by cluster, to your assortment plan.

It runs line reviews by store and by cluster, localizes ranges to regional demand, and exports the review for merchant and supplier meetings. It works with product information management, catalog and planogram tools, and market and trend data.

With OODARIS, each option is ranked by local demand, space, margin and exit risk for every store cluster before the range is committed. The approved range by cluster is what allocation plans from.

Two agents work alongside it. The Trend Intelligence Scout matches social, search and influencer signals to your product attributes and proposes early demand scores for new-to-market styles, by region; it writes nothing directly, and its scores feed the range and launch proposals. The New Product Catalyst watches early sales of new styles against their launch plan and proposes buy sizes for each launch wave, test groups, and when to chase or cut; the buyer approves its proposals.

By default, the person who owns the decision approves each change before anything is written back. Teams can also keep OODARIS read-only, or let it act on its own inside limits the decision’s owner sets; how it works describes the four levels. Assortment is one of the five capabilities available to new clients today.

Frequently asked questions

What is the difference between assortment planning and merchandise financial planning?

Merchandise financial planning sets the money: sales, margin, inventory and receipts by department and period. Assortment planning decides which products fill that money in each store cluster.

What is the difference between breadth and depth in an assortment?

Breadth is the number of different options a category carries. Depth is how many units of each option are carried, including the spread across sizes. With fixed space, more breadth means less depth per option.

What is store clustering in assortment planning?

Store clustering groups stores with similar sales volume, climate, space or customers so that each group can get a range suited to it. The cluster, not the single store, is usually the level at which ranges are set.

How is assortment planning different from allocation?

Assortment planning decides which products each cluster carries. Allocation decides how many units of each product, in which sizes, each store receives and when.

How does the Assortment Curator decide what to drop?

It ranks each option by local demand, space, margin and exit risk for every store cluster and proposes adds, keeps and drops for each cluster, with the reason for each. The assortment planner and the buyer approve before the range is written back to your assortment plan.

Start with one decision.

Pick the decision where margin leaks first. In a demo we walk through one like it in OODARIS; a pilot runs one live cycle on your data.

What happens next

  1. A reply within 24 hours

    A person on the OODARIS team reads your note and writes back to set up a first call.

  2. The first call

    We map the decision's data, handoffs and approvals, and show how OODARIS would work through it.

  3. A pilot, if it fits

    8–12 weeks to a first live cycle, run on your data with your approvals.