Compare proposed markets using demographic, economic, density, accessibility, and competitive characteristics.
Comparing candidate territories usually turns into an argument about which factor matters most. This tool makes that argument explicit: you set the benchmark for each measure and how much weight it carries, then every market is scored against the same standard.
Two measures are treated as ceilings rather than floors. Fewer competitors and a shorter drive time both score better when they come in under the benchmark, so you can mix “more is better” and “less is better” factors in one comparison.
Each market is scored against your benchmark on every measure. For the four “more is better” measures the score is the value as a percentage of the benchmark; for competitors and drive time it inverts, so coming in under the benchmark scores above 100. Individual measures can reach 110, which lets a genuinely strong showing on one factor offset a weaker one, but the weighted total is capped at 100 so no market can run away on a single measure.
Weights are relative, not percentages — they are summed and each measure's score is divided by that total. Setting a weight to zero removes the measure from the comparison entirely, which is a quick way to test how much a contested factor is actually driving your ranking.
The score reflects the numbers and weights you entered, nothing more. Larger geographic areas naturally produce larger population and household totals, so comparing territories of very different sizes will flatter the big ones unless you normalise first. And a ranking is not a recommendation: existing commitments, franchisee capability, real estate availability, and the sequence in which you want to develop a market all matter and none of them appear here.
Use a consistent set of criteria tied to the concept's customer profile, market capacity, accessibility, competitive environment, and operating model. Apply the same definitions, sources, and data years across all proposed territories.
Not by itself. The score reflects the assumptions and data entered. It can help prioritize analysis, but it does not account for every geographic, contractual, operational, or market factor and does not predict financial performance.
Yes, but larger geographic areas often produce larger population and household totals. Consider whether customer density, drive time, serviceability, boundary shape, and qualified customer distribution make the areas meaningfully comparable.
Validate the leading markets using complete geographic boundaries, current demographic layers, competitive and point-of-interest data, existing territory commitments, and operating constraints. Zors brings these elements together on an interactive franchise territory map.
Create, analyze, present, and manage franchise territories with demographic intelligence and franchise workflows built into Zors.
