Picking KPIs for CRE leasing teams

Leasing teams were among the first to adopt foot-traffic analytics, and they are also the teams most likely to be using it badly. The usual failure mode is a single headline number (“our center sees 4 million visits a year”) deployed in every pitch, regardless of which tenant is across the table.

A big number is a fine opener. It is a poor argument. A prospective tenant’s real estate committee does not care how busy your center is in general; it cares whether its customers are there, whether the space will be productive, and whether the neighbors will help or hurt. That calls for a small, deliberate set of KPIs.

Here are the five we recommend to leasing and asset management teams, with how to pull each one in MapDove. Numbers in the examples are illustrative and drawn from the synthetic demo dataset.

1. Visits per square foot

Raw visits favor large units. A 40,000 sq ft grocer will always out-visit a 1,800 sq ft café, which tells you nothing about which space is more productive. Normalizing by area fixes that.

How to use it:

• Compare within a category, never across. Grocery and coffee have very different natural densities.
• Use it to support rent conversations. If the in-line spaces along one corridor of a center produce 40% more visits per sq ft than the other, that is a defensible basis for differential rents.
• Use it to spot under-performing boxes. A large-format tenant with low visits per sq ft relative to its category is a candidate for a downsize or a split.

Every place in MapDove carries a sqft field, so visits per sq ft is one division away in the app or an export. In Dubai, the same metric reads as visits per square meter.

2. Percentile in city (within category)

“Strong” is meaningless without a reference group. MapDove’s place view reports a percentile in city: where this location ranks among all places in the same category in the same city. A Taco Rojo unit at the 81st percentile out-visits four in five quick-service places in its market.

Why leasing teams should prefer it to raw counts:

• It is seasonally neutral. Everything in the reference group experiences the same season, so the percentile does not swing just because it is August in Phoenix.
• It travels well. “Top-decile coffee location” means the same thing to a tenant in Austin as in Miami.
• It frames renewals. A tenant who has slipped from the 70th to the 45th percentile over two years has a different conversation coming than one that has held steady.

3. Trade-area overlap

Prospective tenants want to know whether your center’s visitors look like their customers. The trade area view answers that: it maps the hexes that together account for the first 85% of modeled visitors, with population, income, age and lifestyle segment mix.

For leasing, the strongest version of this KPI is overlap: how much of the prospect’s existing trade area (from one of their stores elsewhere in the city) coincides with your center’s. High overlap with an existing store is a mixed signal; it confirms fit, but it also predicts cannibalization. Pair it with a Huff forecast with cannibalization enabled to show the prospect net new visits, not just gross.

4. Co-tenancy strength via cross-shopping

Co-tenancy clauses are written in legal terms, but they rest on a behavioral claim: that one tenant’s customers also shop at another. Cross-shopping measures exactly that. For any place, it lists the other places its visitors also visit, with two scores:

• Overlap: the share of visitors in common.
• Affinity: how much more likely that is than you would expect from the two places’ sizes and locations alone.

Affinity is the one to bring to a negotiation. Every tenant overlaps with the busy grocer next door; a high-affinity link (say, between IronPulse Fitness and a neighboring WellPoint Pharmacy) shows a genuine shared customer that a merchandising plan can build on. It also tells you which tenants matter most for co-tenancy: losing a high-affinity anchor hurts more than losing a merely large one.

5. Dwell time

Dwell is the KPI most often ignored and the one that best explains how a center earns its rent. Long dwell means more cross-shopping, more food and beverage, and more incidental spending.

Use it carefully:

• Benchmark by category. A cinema will always out-dwell a pharmacy. Compare a Starlight Cinemas to other cinemas, not to the center average.
• Track direction, not level. A falling center-wide dwell after an anchor departure is an early warning that the remaining tenants are losing cross-shopping traffic.
• Use it to place F&B. Units adjacent to long-dwell tenants are the natural home for cafés and casual dining.

Putting it together

A compact leasing scorecard for a prospect pitch:

KPI	Question it answers	Where in MapDove
Visits per sq ft	Is this space productive?	Place view, sqft
Percentile in city	How strong is it versus its peers?	Place view KPIs
Trade-area overlap	Are the prospect’s customers here?	Trade areas
Cross-shopping affinity	Will the neighbors help?	Cross-shopping
Dwell time	Does this center hold visitors?	Place view, visit series

Five numbers, each tied to a question a tenant’s committee will ask. For portfolio reviews, add compare sites to put up to five candidate units side by side on suitability, forecast and a 1-mile catchment.

Takeaway

Retire the single headline visit count. Build each pitch from visits per sq ft, percentile in city, trade-area overlap, cross-shopping affinity and dwell, all benchmarked within category and city. These KPIs are seasonally fair, comparable across markets and grounded in the questions tenants actually ask. See how the real estate solution packages them for leasing and asset teams.