Calculate what Pay & Store lockers could earn at your venue

The Pay & Store ROI calculator estimates annual locker revenue by multiplying annual visitors, expected usage rate, and average price per use. Use it as a smart rental locker ROI calculator, paid locker revenue calculator, or self-service luggage storage ROI tool for venues, hotels, transit sites, and public spaces.

If your venue already handles coats, bags, luggage, or prohibited items, your storage demand may already be measurable.

The calculator helps you test whether that demand can become a profitable Pay & Store model. Start with the traffic numbers your team already knows, then compare how revenue changes when you adjust price, usage rate, locker count, and business model.

This gives commercial, operations, and facilities teams a shared starting point for the same decision: whether paid guest storage is worth scoping for the site.

Use this calculator if you are reviewing:

• Venue locker revenue for arenas, stadiums, concert halls, theatres, museums, exhibitions, or event spaces
• Hotel luggage storage lockers for early arrivals, late departures, and peak front-desk periods
• Cloakroom locker ROI for venues replacing staffed coat check, keys, coins, or manual tickets
• Guest storage revenue for transit hubs, public spaces, leisure venues, nightlife, and hospitality sites
• Payback scenarios for purchase, lease, or revenue-share locker models

The calculator is useful for commercial, operations, facilities, guest-experience, and revenue teams that need a practical first estimate before a deeper site review.

The calculator uses a simple revenue model:

Annual Revenue = Annual Visitors x Expected Usage Rate x Average Price per Use

Start with four inputs:

• Annual visitors: total guests, attendees, travellers, or visitors passing through your site each year
• Expected usage rate: the share of visitors likely to use paid storage
• Average price per use: the price guests pay for one storage session
• Locker count: the number of lockers available for paid use
• Adjust each input to model conservative, expected, and high-demand scenarios.

A concert venue can compare weekday shows with sold-out events. A hotel group can test luggage storage around check-in and check-out. A transit or public-space operator can model demand around arrival and departure peaks.