How to Win Retail LOIs in 2026: 7 Questions Landlords Should Answer

A landlord playbook to reduce friction, speed decisions, and win more LOIs

Retailers didn’t suddenly change their minds in 2026. The environment changed.

With higher operating and build-out costs, retailers are leaning harder on analytics to reduce risk in site selection. At the same time, retail availability remains constrained and new supply is limited, which means fewer “perfect” spaces and more pressure to make the right call quickly.

For landlords, that shifts the competitive advantage. A strong center in a strong market still matters. What increasingly wins tours and LOIs is decision confidence: the ability to show—early—how a site will perform, how it will operate, and how fast it can open.

Removing decision friction

In 2026, expanding retailers tend to evaluate sites through a practical lens:
How many unknowns remain—and how costly are they?

Most “unknowns” fall into four buckets:

1. Market risk: Is demand real for this concept, and will it show up consistently?
2. Competition risk: Who already serves this demand, and what’s the share fight?
3. Ops risk: Can the site physically run the model (flow, loading, pickup, signage, stacking)?
4. Timeline risk: Can the store open on schedule, or will utilities/permitting derail the plan?

This is why “disciplined, data-led growth” keeps showing up in industry conversations: retailers are optimizing for quality and predictability.

The 7 questions retailers are asking in 2026 (and how landlords should answer)

These are the questions that surface repeatedly in deal cycles. The fastest path to “yes” is answering them proactively in a tight, decision-ready packet.

1) “Can this site win a specific trade area?”

Retailers are putting more weight on real-world movement patterns because routines are fluid, and a busy corridor doesn’t automatically translate into the right customer. Movement and mobility data increasingly shape how trade areas are defined and evaluated.

What to provide

• A trade area defined by observed origins (where visitors come from)
• A simple explanation of why those origins match the concept’s target customer
• A short list of top feeder neighborhoods/submarkets (and what that implies for positioning)

2) “What does visitation look like by daypart, weekend, and season?”

Retailers want patterns they can plan around: peak windows, repeat behavior, and seasonality that aligns with their category.

What to provide

• A visitation profile that highlights:
  • Daypart strength (e.g., lunch vs. dinner, weekday vs. weekend)
  • Seasonal swings (and whether they support the concept’s calendar)
  • Repeat/visit-frequency indicators where available
• Context versus comparable centers or corridors when possible

This fits the broader shift toward analytics-driven decisions as the cost of error rises.

3) “What’s the adjacency story—and why does it work for us?”

Adjacency is becoming more deliberate. Retailers want a clear explanation of how nearby uses drive complementary trips and cross-shopping.

Store roles are also diverging. Some formats are designed as experience destinations, while others win through speed and convenience. That difference changes what “good adjacency” looks like.

What to provide (a true 5-bullet adjacency thesis)

• Trip drivers: which tenants generate consistent traffic (and when)
• Trip missions: what shoppers are doing before/after (errand runs, dining, weekly stock-up)
• Complementary categories: which neighbors increase relevance for this concept type
• Customer overlap: which nearby uses share the same customer profile (not just the same parking lot)
• Placement logic: where this concept should sit in the center to maximize visibility and flow

4) “Where will sales come from: capture, switch, or new demand?”

Retailers want a credible demand story, not a generic “strong demo” claim.

What to provide

• A competitive set that reflects how shoppers actually behave (not only distance)
• A clear demand narrative:
  • Capture: conversion of existing trips already happening at/near the site
  • Switch: share that can be taken from competitors (and why this site has an edge)
  • New demand: incremental trips your mix and location can create (harder, but sometimes real)

Movement-data approaches help reduce guesswork and improve confidence in these trade-offs.

5) “Can the site physically operate our model?”

Operational fit is a gate. If the model can’t run cleanly, the deal stalls.

Physical stores increasingly function as part of broader omnichannel networks (pickup, returns, last-mile support), which increases the importance of back-of-house needs, access, and circulation.

What to provide

• An annotated site plan that addresses:
  • Ingress/egress realism
  • Loading access and constraints
  • Pickup/curbside feasibility
  • Stacking/queuing potential (where relevant)
  • Signage and visibility limitations
• A short “constraints + mitigations” note (surface issues early, show a path through them)

6) “What’s the speed-to-open path—and what could derail it?”

Retailers want a timeline that reflects reality: dependencies, risks, and who owns each step.

Across the site selection landscape, power constraints and infrastructure readiness are eliminating sites earlier, and scarcity is pushing decisions toward deliverability. Energy and utility constraints continue to influence development feasibility, and the consistent recommendation is to verify capacity and timelines early.

What to provide

• A basic critical path with responsibilities (tenant vs. landlord vs. municipality vs. utility)
• Utility readiness evidence (or a defined plan to confirm quickly)
• Permitting precedent and known friction points
• A schedule range that’s credible, with risk flags clearly stated

7) “What does success look like versus comparable locations and why?”

Retailers want a defensible “why this works” story tied to:

• lookalike trade areas,
• comparable co-tenancy patterns,
• trip missions and visit behavior that match the prototype.

What to provide

• A short “comp logic” section:
  • which comparable environments this resembles (and why)
  • what that implies for performance expectations and ramp
• A direct recommendation: “This site fits X concept profile because…”

Disciplined, insight-driven growth strategies are increasingly positioned as standard practice for retailers managing risk.

What to hand a retailer: the Decision-Ready Packet

Retailers move faster when you reduce diligence friction. The goal of this packet is simple: make the decision easy to validate.

Decision-Ready Packet

1. 1-page executive summary
   • Site thesis (2–3 sentences)
   • Top 3 risks + mitigations
   • Best-fit categories / use cases
2. Trade area behavior
   • Top origin areas
   • Movement-informed trade area definition
   • What’s distinctive about this draw
3. Visitation profile
   • Daypart / weekend / seasonal highlights
   • Repeat/frequency indicators where available
   • “What this suggests” for the category
4. Competitive reality
   • Competitive set + implications
   • Leakage/capture narrative
   • Cannibalization notes (if relevant)
5. Operational feasibility
   • Annotated plan: flow, loading, access, pickup/stacking
   • Constraints + solutions
6. Speed-to-open
   • Timeline range + dependencies
   • Utility status / next steps
   • Permitting path and precedent

As costs rise and the downside of a miss gets bigger, retailers increasingly favor partners who shorten the path to confidence.

The bottom line: package certainty, win faster

In a constrained supply environment—limited availability and low new construction—retailers prioritize sites that can be evaluated and executed with fewer surprises.

Landlords who consistently win in this climate do three things well:

• They define the trade area with real behavior
• They make operational fit obvious
• They surface timeline risks early and credibly

That’s the opportunity for retailer-side intelligence: turning what expanding retailers prioritize into a clear, evidence-backed site story that leasing teams can use to move deals forward.