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StorageLab Methodology

How we turn belongings into a size recommendation and market observations into a price range — including where the data is strong and where it is not.

Size methodology

The inventory method assigns planning-volume estimates to common household items, then converts total packed volume to required floor space using an assumed 8 ft unit height and a packing-efficiency factor.

Efficiency is reduced when you need more frequent access, because a usable aisle and less aggressive stacking consume space.

Limitation: item volumes are planning estimates, not manufacturer dimensions. Provider unit shapes and ceiling heights vary.

Home presets

Home presets use evidence-backed planning anchors: approximately 25 sq ft for a studio/bedsit, 50 sq ft for a 1-bedroom flat, 75 sq ft for a typical 2-bedroom home, 100 sq ft for a 2–3 bedroom home and 150 sq ft for a large 3–4 bedroom household.

3D spatial methodology

The visualizer is a second planning layer. It does not replace the core size recommendation; it checks whether representative packed dimensions can be arranged inside the selected unit while preserving an access allowance.

01

Packed dimensions + semantic models

Common items use approximate width, depth and height values intended for storage planning. The renderer interprets those bounds as recognisable low-poly sofas, mattresses, cabinets, appliances, bikes, chairs and box stacks rather than anonymous cuboids.

02

Storage-aware packing

Boxes can rotate and stack. Dining chairs may be nested in pairs, mattresses and bed parts are represented upright, and furniture/appliances remain broadly upright so the simulation does not gain unrealistic space by turning everything on its side.

03

Access allowance

Monthly and weekly access reserve more floor width for retrieval. Rare archive-style storage can use a tighter packing mode.

Technology: Three.js renders the semantic furniture silhouettes while binpackingjs evaluates conservative bounding boxes. The visual mesh and the fit box are deliberately separate: recognisability must not make the mathematical fit less conservative. Both versions are pinned; the normal size and price tools still work if 3D modules cannot load.

Open the 3D storage visualizer →

Price methodology

01

Keep raw observations

Each observation stores source, provider, location, unit size, billing period, rate class, date and confidence.

02

Normalise periods

Weekly prices are converted using weekly × 52 / 12. We do not assume four weeks equals one month.

03

Separate promotions

Introductory or promotional rates are not silently used as standard ongoing prices.

Current markets

UK baseline, London, Manchester and Birmingham. Exact-size benchmark bands cover 50, 75, 100 and 150 sq ft; intermediate sizes may be interpolated and are labelled estimated.

Not live pricing: StorageLab benchmark ranges are planning estimates. Always confirm current provider prices and mandatory extras before booking.

Research sources retained in the dataset

The current dataset contains 46 observations. Provider and industry sources are preferred over comparison/editorial summaries where available.

Download source observations CSV