Hoodie Analytics · Retail Site Selection · September 2026

Presenting a new-site or acquisition recommendation to a real estate committee is a different exercise than exploring the opportunity yourself. You already believe in the location. Now the job is to give a group of people who weren’t in the field with you enough to trust the recommendation on its own merits. That comes down to what you show them, in what order, and how honestly you frame the numbers.

Start with the relationship between the site and its market, not the price tag

Committees that see a revenue number first tend to interrogate the revenue number first, before they’ve had a chance to understand the market it’s coming from. It’s worth walking through the site’s context before the financials: who’s already operating nearby, what the trade area looks like demographically, and whether the zoning actually supports the plan. Once the committee understands the ground the recommendation is standing on, the financial estimate lands as a natural conclusion rather than a number to be defended in isolation.

The figures a committee will ask about first

In practice, four questions tend to come up before anything else, all core outputs of Hoodie’s cannabis dispensary site selection:

  • Competitive density. How many dispensaries are already serving this trade area, and how close is the nearest one. A committee wants to know whether this site is entering open ground or fighting for share on day one.
  • Zoning risk. Whether the location is cleared to operate as planned, or whether there’s a permitting or land-use hurdle that could stall or kill the timeline. This is usually the fastest way a promising site gets tabled, so it’s worth addressing before anyone else raises it.
  • Projected revenue range. What the site is likely to do in its first year or two, and what that estimate is built from.
  • Demographic fit. Whether the population within a realistic trade area actually matches the profile of an active cannabis customer, not just whether there are enough people nearby.

Having each of these ready, with the reasoning behind them, does more for credibility than any single standout number.

A Hoodie Analytics site selection report for a sample location, showing the trade area map, nearby points of interest, and a monthly revenue prediction.

A sample Hoodie site selection report: trade area, nearby points of interest, and a monthly revenue prediction, compiled side by side.

Present the estimate as a range, honestly

A revenue estimate is a projection built from comparable conditions: trade-area demographics, competitive density, nearby points of interest, and the specifics of the planned store. It is not a guarantee, and presenting it as one invites the wrong kind of scrutiny the moment actual results land anywhere outside a single point figure. A range, framed around the assumptions that drive it, holds up better under committee questioning and better reflects what the data can actually tell you. If a committee member asks what could push results outside that range, having an answer ready (a major competitor opening nearby, a zoning shift, a shift in the local market) shows the estimate was built with those risks in mind, not despite them.

Why one document beats four dashboards

Real estate committees are usually reviewing several opportunities in a single sitting, often against a deadline. Asking them to cross-reference a zoning map, a demographic report, a competitor list, and a spreadsheet of revenue assumptions slows the meeting down and gives every skeptic a separate document to pick apart. A single compiled report that puts competitive density, zoning context, demographic fit, and the revenue range side by side lets the committee evaluate the whole case at once, in the order that makes the strongest argument, rather than reconstructing it themselves from four different sources.

Hoodie’s cannabis dispensary site selection report is built for exactly this moment: everything the committee will ask for, compiled into one PDF, presented in the order that builds the case rather than the order the data happened to be pulled.

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Where insights meet relationships.

When you’re ready to see this in your own data, Retail Site Selection is where to start.

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