Most location decisions in small business are made on impressions: the street felt busy, the rent was reasonable, the neighborhood seems to be improving. Baltimore publishes enough neighborhood-level data to replace all three impressions with figures.
What is published
Indicators are compiled at community statistical area level: groupings of neighborhoods small enough to be meaningful for a decision about a specific site, which is exactly what citywide statistics cannot do.
The categories relevant to a business decision:
Population and age profile. How many people, and of what ages, within the catchment.
Household income. What the local market can spend.
Housing and vacancy. Occupancy, ownership, and the vacancy rate, which is among the best single indicators of a commercial street’s trajectory.
Vehicle access. Decisive for some retail models and irrelevant to others, and rarely considered at all.
Commercial activity. Business counts and employment in the area.
Trend. All of it published over time, so direction is visible.
Using it for a location decision
Three questions the data answers directly.
How many potential customers are within the realistic catchment? For most small retail and service businesses the catchment is smaller than owners assume: walking distance, or a short drive. Population within that radius, filtered by the relevant age or income characteristic, is the market.
Can they afford what you charge? Household income against your price point. A business whose economics require a spend the neighborhood does not have is in difficulty before it opens, and this is the check that most often changes a plan.
Which way is it going? Trend data over several years. A neighborhood improving from a low base frequently makes a better site than a stable comfortable one, because the rent reflects the past and the trade reflects the future.
What it cannot tell you
It cannot tell you about footfall on a specific block, which varies enormously within an area, and it cannot tell you about competition. Both require going and looking: counting people at different times of day, and visiting the businesses already doing something close to what you intend.
The combination is what works: data for the catchment, observation for the block. Either alone produces a confident wrong answer.
Alongside the library
Neighborhood demographics answer who is nearby. Industry benchmarks answer what a business like yours should look like financially, and consumer spending data answers what people like that actually buy. The second and third sit in the subscription databases at the Enoch Pratt Free Library, free with a card.
Put together, these two free sources produce most of a feasibility study, and a set of projections built on them is substantially more credible to a lender than one built on estimates, as the financing fundamentals page explains.
Reading the indicators carefully
Two habits prevent the most common misreadings.
Check the geography. Community statistical areas do not always match how people describe neighborhoods, and a commercial street can sit on a boundary with very different populations on either side. Confirm which area actually contains the site.
Check the year. Indicators come from sources with different collection dates, and some update annually while others follow a longer cycle. A figure that is four years old may be fine for a slow-moving measure and misleading for a fast-moving one.
Neither of these is difficult and both are routinely skipped, which is how confident wrong conclusions get built on real data.
Combining data with observation
The data answers who is nearby. It cannot answer what happens on one block, and the two together are what produce a good decision.
Go at different times: a weekday morning, a weekday evening, a Saturday afternoon, and count people passing. Note which direction they are moving and whether they stop. Look at what is occupied, what is empty, and how long the empty units have been empty. Visit the businesses doing something adjacent to your idea and see how busy they are.
An afternoon of this, set against the demographics, is a better feasibility assessment than most paid reports, and it costs a bus fare.
Using it in a funding application
Lenders and grant funders read applications that assert demand and rarely read ones that evidence it.
A paragraph naming the population within the catchment, the relevant income or age characteristic, and the source, changes how the rest of the application is read, because it demonstrates the applicant checked rather than assumed.
The financing fundamentals page covers what else lenders assess, and the project-based funding page covers grant applications. In both, specific sourced figures do disproportionate work.
The wider open data picture
City open data portals publish permits issued, licenses granted, code violations and service requests, alongside the neighborhood indicators.
For someone assessing a commercial street this is unusually informative: permits issued nearby indicate investment, and the pattern of violations and service requests describes conditions that a single visit would not reveal.
What the data cannot settle
It gives the catchment and the trend. It does not give footfall on one block, competitive intensity, or whether a specific unit has a problem that has defeated three previous tenants.
Those come from visiting at different hours and talking to neighboring businesses, which is why the data is half of a site decision instead of all of it.