Inventory how-to

How to forecast demand for a new color or size

A brand new variant has no sales history, so you cannot forecast it the normal way.

Short answer: A brand new variant has no sales history, so you cannot forecast it the normal way. Instead, borrow data from a similar existing variant or the parent product, then switch to the variant's own sales as soon as you have a few weeks of real numbers.

Start with a proxy variant

Pick the closest existing variant as your stand-in. For a new color, use the best-selling color in that same style. For a new size, use the most common size of a similar product. Use that proxy's daily sales rate as your starting forecast, then adjust it up or down based on what you know about demand for the new option.

Adjust for known differences

If the new size is a less common one (like XS or XXL), scale the proxy down, maybe to half or a third of the core size's rate. If the new color is a trend color or matches a current pattern of strong colors selling well, you might keep it close to the proxy or even scale it up slightly. Write down your assumption so you can check it later against real sales.

Order small and conservative at first

Since this is a guess, order a smaller first batch than your formula suggests, or stick closer to the supplier's case pack minimum. This limits the downside if the new variant underperforms. Set a short review point, for example after 3 to 4 weeks of sales, rather than waiting for a full seasonal cycle.

Switch to real data as soon as you can

Once the new variant has a few weeks of its own sales, stop using the proxy and calculate its own daily sales rate. Compare that rate to what you assumed. If it is selling faster or slower than the proxy, update your reorder point and order quantities for that SKU going forward.

Step by step

  1. List the closest existing variant to use as a proxy, by style, material, or price point
  2. Pull that proxy variant's recent daily sales rate
  3. Apply a size or color adjustment factor based on your judgment of relative demand
  4. Calculate a conservative first order using that adjusted rate, rounded to the supplier's case pack and minimum
  5. Place the order and set a calendar reminder for a 3 to 4 week review
  6. Once real sales data exists, recalculate the daily sales rate from actual numbers
  7. Update your reorder point and future order quantities using the real rate instead of the proxy

Worked example

A store launches a new "Sage Green" color for a shirt that already sells in five colors. The best-selling color, "Navy," sells 6 units a day. The store manager expects Sage Green to be a mid-pack performer, so they estimate 3 units a day, half of Navy's rate. Lead time is 20 days and they want 10 days of safety stock, so order point = 3 x (20 + 10) = 90 units. They round down slightly for a first order of 72 units (two case packs of 36) rather than the full amount the formula suggests, to limit risk. After four weeks Sage Green is actually selling 4.5 units a day, so they update the daily rate used for its next reorder.

How SteadyShelf helps

SteadyShelf forecasts from a variant's own 28-day sales window, so a brand new variant with no sales history will not get a meaningful forecast on day one. You need to set the first order manually using a proxy variant as described above; once a few weeks of sales exist for the new SKU, SteadyShelf will pick up its own sales pattern and start suggesting reorders from real data.

$29/month flat, unlimited products and suppliers, 30-day free trial. Run the numbers now with the free reorder point calculator.

SteadyShelf is launching on the Shopify App Store. Join early access to get the install link first.

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FAQ

Should I set a reorder point for a new variant before it has any sales?

You can set a rough one based on the proxy variant's daily rate, but treat it as temporary. Recalculate as soon as the new variant has its own sales history, usually after 3 to 4 weeks.

What if the new variant sells out immediately and I have no data to judge against?

A fast sellout with no history is not reliable data either; it could mean the order was too small rather than demand being huge. Reorder a moderate increase over the first batch and keep watching the daily rate over the next few weeks before committing to a large order.

Let SteadyShelf do this math for every SKU

Order-by dates per supplier, seasonal forecasts and draft POs for your Shopify store. $29/month after a 30-day free trial.

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