Footfall, capture, conversion and basket chained into a shop's sales and the rent it can pay, with the gearing that makes a footfall fall hit rent harder than sales.
Footfall conversion rate is transactions divided by visitors: a shop with 400,000 entries a year and 92,000 transactions converts 23.0 per cent. Multiply conversion by entries and the average transaction value and you have the unit's sales, 4,140,000 here, which is what decides the rent it can pay: a 10 per cent fall in footfall cuts this unit's rent capacity by 13.5 per cent and takes it below its passing rent.
Worked in full in Retail Real Estate by Julian R. Sterling, with every figure reproduced in a free workbook.See the book on Amazon →
Landlords count footfall at the centre doors; retailers count it at their own. The two measures answer different questions, and the useful one for an owner is the chain that runs from people through the door to sales to rent. Because retail tenants report their sales, every link in that chain can be measured rather than guessed.
| Input | Value |
|---|---|
| Centre footfall, visits | 9,000,000 |
| Centre sales, ex VAT | 76,500,000 |
| Unit door count, entries | 400,000 |
| Unit transactions | 92,000 |
| Average transaction value | 45.00 |
| Occupancy cost ceiling for the trade | 12% |
| Service charge and rates | 130,000 |
| Passing rent | 340,000 |
Conversion rate = transactions / entries
92,000 / 400,000 = 23.0 per cent. In Excel: =B5/B4.
Sales = entries × conversion × average transaction value
400,000 × 23.0% × 45.00 = 4,140,000, or 10.35 per entry.
Capture rate = unit entries / centre footfall
400,000 / 9,000,000 = 4.44 per cent of centre visitors come into the shop. At centre level the equivalent measure is spend per visit: 76,500,000 / 9,000,000 = 8.50.
Conversion is only meaningful with a door counter at the unit, which most retailers have and few share. The centre-wide figure landlords can compute from their own data is spend per visit, and it moves for three reasons the landlord cannot separate without the tenant's numbers: fewer people coming in, fewer of them buying, or smaller baskets.
Rent capacity = ceiling × sales − service charge and rates
12% × 4,140,000 − 130,000 = 366,800, against a passing rent of 340,000. Headroom is 26,800 and the occupancy cost ratio is 11.4 per cent. The ratio itself is covered in how to calculate a retailer's occupancy cost ratio.
The rent the unit can sustain is geared to footfall. Service charge and rates do not fall when visitors do, so each 1 per cent of sales lost costs 1.35 per cent of rent capacity. Sales can fall only 5.4 per cent, to 3,916,667, before capacity drops below the rent.
| Footfall change | 21% conversion | 23% conversion | 25% conversion |
|---|---|---|---|
| −15% | 255,560 | 292,280 | 329,000 |
| −10% | 278,240 | 317,120 | 356,000 |
| −5% | 300,920 | 341,960 | 383,000 |
| 0% | 323,600 | 366,800 | 410,000 |
| +5% | 346,280 | 391,640 | 437,000 |
A 10 per cent fall in footfall at constant conversion leaves sales at 3,726,000 and capacity at 317,120, 22,880 below the rent. Two points of conversion are worth about as much as 10 per cent of footfall: a fall from 23 to 21 per cent, with footfall unchanged, cuts capacity by 11.8 per cent, to 323,600.
Run it backwards to see what a tenant must do to hold the rent after losing a tenth of its visitors. With 360,000 entries it needs 87,037 transactions, a conversion of 24.2 per cent; or, at an unchanged 23.0 per cent, an average transaction of 47.30, 5.1 per cent higher. Either is achievable for a good operator and neither is automatic, which is the conversation an asset manager should have before a lease event, not after.
Footfall is the landlord's number and conversion is the tenant's. A centre whose footfall is flat while tenants' sales fall is losing conversion, which usually means the wrong tenant mix or the wrong offer for the visitors it has, not a marketing problem.
The landlord has centre footfall from door counters and, under most modern leases, monthly or annual sales from each tenant. Unit entries and transactions belong to the retailer, but many will share them during a lease negotiation, especially when the alternative is a rent the landlord sets from sales alone. With sales and the centre count you can still compute sales per centre visit for each unit, 0.46 here, and track it month by month: a falling figure with stable footfall is a conversion or basket problem inside the shop.
Conversion is transactions over entries, 23.0 per cent on this unit; sales are entries times conversion times basket; rent capacity is the ceiling times sales less fixed occupancy costs. Follow the chain and a footfall report becomes a rent forecast. The free workbook for this case runs the same capacity test across the whole tape, with sales shocks built in, and the companion article on the sales growth a retailer needs to keep paying its rent runs it forward in time.
It depends on the trade: a grocer converts most visitors, a fashion or furniture store far fewer, so compare like with like and over time. The figure that matters for the landlord is whether conversion supports the rent. In this example the fashion unit converts 23.0 per cent and needs 24.2 per cent to hold its rent if footfall falls 10 per cent.
Footfall counts visits to the centre, capture rate is the share that enter a given shop, and conversion is the share of shop entries that buy. Here 9,000,000 visits, a 4.44 per cent capture rate and 23.0 per cent conversion give 92,000 transactions.
More than proportionally, because service charge and rates stay fixed while sales fall. On this unit a 10 per cent fall in footfall, at constant conversion and basket, cuts sales to 3,726,000 and rent capacity from 366,800 to 317,120, a fall of 13.5 per cent, leaving it 22,880 below the passing rent.
This article is one calculation from Retail Real Estate. The book takes the same case from first principles to the decision, chapter by chapter, and every figure it prints is a live formula in the free companion workbooks.
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