A retail site shortlist starts with a particular store in mind. A convenience store depends on different shopping trips than a destination store, and those differences affect what the property needs to offer. You're choosing space where that format can operate and reach the customers it is meant to serve.
The people approving the shortlist need to understand why the store's needs point toward one property over another. They also need to know which questions about a site still need answers before the team seeks a lease.
| Criterion | Treatment | Geographic evidence | Additional check |
|---|---|---|---|
| Permitted use and required access | Pass/fail requirement | Site and approach locations | Property documents and site review |
| Relevant demand | Weighted preference | Customers, supplied traffic, demographics | Data definition and period |
| Existing-store overlap | Review against the network plan | Existing sites and comparable catchments | Customer and sales evidence |
| Occupancy cost | Budget requirement or preference | Candidate location | Comparable lease and operating costs |
Set criteria for this store format
Separate failed requirements from preferences
Write down what the proposed store needs before you look at the map. The requirements should come from the actual format and operating plan. The space you can use and the allowed use may each rule out a property. How people can reach it and the budget for using the space may do the same.
Give each requirement a pass, fail, or unresolved status in the source worksheet. Keep unresolved sites separate from sites that passed. A broker's assurance or an attractive map position doesn't complete a building or permitted-use check.
Next, decide which preferences matter most to the concept. A destination store, a convenience store, and a store that relies on people buying on impulse may value the same location features differently. Judge foot traffic and ease of parking with that store type in mind. Do the same for how well people can see the store and which businesses are nearby.
Ask the operating team how customers reach successful stores and what they buy there. Use that evidence to choose what to compare on the map. Avoid giving every criterion equal weight simply because each one is easy to put in a table.
Document the score calculation
Calculate the site score in your team's spreadsheet, then import the result as a numeric column. Maptive will display and filter the supplied score. Keep the scoring rules in the worksheet so another planner can work out the same ranking.
Define the unit, direction, and weight of each input. More demand may help a site, while higher costs for using the space may count against it. Put unlike measures on the same scoring scale before you add them. Adding raw rent dollars to a pedestrian count produces a total that tells you nothing useful.
For a simple example of the math, suppose your team has already rated demand at 80 and access at 60 on a 0-to-100 scale. If it assigns 60% weight to demand and 40% to access, the combined score is 72. Those inputs and weights are examples. They are not a suggested retail formula or the result for a real site.
Write down what to do when an input is missing. You might wait to score the site until the evidence arrives, or mark its score as pending review. Don't treat a missing value as a measured zero. If you change how you treat missing data or spread the weights differently for one site, record that change before you compare its score with sites that have all their data.
Make sure costs for using the space can be compared before you score them. Confirm whether each figure covers a month or a year, and whether it is a total for the unit or a rate per unit of floor area. Keep the usable area beside it. Ask the property team to identify the costs included in each quote, since a favorable base rent may leave other costs unresolved. Once you have checked that you can compare the figure, record it in the worksheet. Keep the original quote for review.
Keep the raw criteria as separate columns. Include the score version and calculation date too. A small difference in combined scores may depend on a weight your team is still debating. Recalculate that alternative in the worksheet and check whether the shortlist changes.
Map the candidate locations
Prepare a candidate table with a stable Site ID, full address or verified coordinates, store format, review status, usable area, occupancy cost, access checks, dated demand evidence, and the calculated score. Keep pass/fail requirements separate from the numeric preferences.
Add existing stores as distinctly labeled records when you'll review network overlap. Use a record-type field so you can separate existing units from candidates during grouping and filtering. Give an existing store a candidate score only if you scored it with the same method.
Select Create New Map in Maptive, name the workfile, and click Continue. Upload the headered spreadsheet or paste its data under Your Data. Click Map Now and check the location-column matching if prompted.
Open Categorize Data when you need to correct a match. It is available from the Data tab or a marker's gears. Put address fields in Section 1 and title or contact fields in Section 2, then click Done. Keep the score and review status out of the address matches.
Inspect the candidate locations before adding catchments. A property address and the actual storefront entrance may be some distance apart in a large development. Verify the origin you intend to use and retain the Site ID through any correction.
Compare the geographic evidence consistently
Use comparable modeled catchments
Choose the reach measure that fits how customers travel to this store format. A distance radius supplies a simple way to check the area. A drive-time polygon follows modeled road access. Neither tells you who will shop at the store.
For a radius, open Map Tools and Distance Radius Circles. Enter the candidate's origin, set the distance and units, and select Add Proximity Radius. Repeat with the same distance for the other candidates. Keep the origins and the distance convention consistent.
For driving reach, open Map Tools and Drive Time Polygon Tool. Enter the candidate address, set hours and minutes, and click Add Drive Time Polygon. Apply the same threshold to the comparison set.
Drive-time polygons assume perfect driving conditions and exclude historical and current traffic. Use them as a consistent modeled comparison, then check busy roads or hard-to-reach entrances on their own. A property near the polygon edge needs more attention if the operating plan depends on customers reaching it during peak traffic.
Using the same time or distance limit keeps one part of the comparison consistent. It doesn't make traffic observations, rent evidence, or access quality equivalent. Keep those checks in their own source columns.
Add the relevant demographics
Open Map Tools and Boundary Tool. Choose the Boundary Set, select Demographic Census Data, choose the Demographic Group and Fill Data, and click Load Boundaries. Use the geography and measure that fit the demand question, such as surrounding population or area income.
Record the displayed data period and geographic unit. Confirm the actual metric's period rather than assigning it a presumed current year. Demographic data is available for the U.S. and Canada, so check the choices for the market you're looking at.
Population tells you how many people live in an area. It doesn't measure store visits. Area income describes the people who live nearby. It does not tell you the income of each person who will shop at the proposed store. Use those measures to judge whether the store suits those customers, along with what you know about how they shop.
You can keep another demographic option through Fill Settings and Add More Fills. Only one fill appears at a time. Change the displayed fill when the question changes, and label the view clearly so an income map doesn't get read as a population map.
Display the supplied scores in Maptive
Open Map Tools and Grouping Tool / Colored Pins Tool. Select Numeric for the imported score column. Choose the group count, percentage or number ranges, and marker style, then click Group Now.
Read the range limits alongside the site values. Several candidates may share a color even when their scores differ. The color helps you see where the stronger candidates are; the numeric score and raw criteria support the order in your ranking worksheet.
When two candidates have similar scores, inspect the inputs rather than inventing a precise distinction from their colors. One may have complete observations and the other a provisional estimate. Tell the team about that difference. A score can organize the work queue without resolving every uncertainty, and a tied shortlist may simply need another visit or a missing lease figure before the order is useful.
Use Filter Tool to restrict the map to the appropriate format and review status. Choose Create Filters on first use, or the gear if filters already exist. Select Group for categorical status or format fields, Number for numeric score or cost limits, and Date when you need a particular evidence period.
Check the records that survive. A high-score filter can conceal a failed requirement unless the status filter is also set correctly. Keep a separate view or worklist for unresolved candidates so they don't disappear from the research queue.
If a source value changes, update the calculation in the scorecard and bring the revised data into the map. Check that the score on the map uses the same version as the raw evidence. The marker range displays your calculation. It doesn't add a separate recommendation to invest.
Inspect overlap and site-level conditions
Review the candidate's catchment alongside existing stores. Where the areas overlap, check the sites more closely. They don't establish how much business a new unit would take from an existing one. Check where real customers come from and any sales evidence you have before you reduce a site’s score for overlap.
Look at whether the candidate serves a different approach, customer group, or shopping trip. Two nearby units can share modeled reach while operating under different conditions. Keep that explanation in the review notes. Do not use the area where the polygons cross to estimate lost sales.
When supplied foot traffic contributes to the score, confirm the measure, source, observation period, and duration. Pedestrians passing a count point differ from store entries. A longer observation will usually contribute more raw passages, so prepare measures you can fairly compare. Do not let counts taken over different lengths of time affect the ranking.
Send the shortlisted properties for field and document checks. Verify parking, entrances, storefront visibility, usable space, building conditions, and the proposed lease terms. Add findings against the Site ID and change a criterion only when the evidence supports it.
Export a shortlist people can audit
Use the Export Data icon, choose Export Filtered Data, select .xlsx, .tsv, .csv, or Clipboard, and click Export Now. Confirm the exported Site IDs against the intended shortlist; Export Data Visible on Map can omit a candidate outside the current view. Keep the raw criteria, evidence dates, catchment assumptions, supplied score, score version, and failed or unresolved requirements in the review packet. Where a ranking depends on uncertain weights or missing evidence, show the recalculated alternative from the source worksheet. Assign the next property or data check to each shortlisted site before the team decides which lease to seek.
