The resemblance map & neighborhood detail

The national resemblance map

When you select a brand, LookAlike displays a national census-tract choropleth — a map where neighborhoods are colored by how closely they resemble the brand’s archetype.

What the colors mean

The map uses a diverging color ramp. Only neighborhoods in the top similarity range are colored:

• 50–68th percentile: nearly transparent (dark background shows through). These neighborhoods exist but do not visually draw attention.
• 68–80th: gold/tan; starting to light up.
• 80–88th: orange; increasingly high similarity.
• 88–95th: red-orange; strong resemblance.
• 95–100th: deep red; very high resemblance to the brand’s store neighborhoods.

Why this design: The map intentionally leaves the median tract dark. It highlights where to look, not the entire country. By color, neighborhoods at the 50th percentile are transparent; only the top tier of matches become visible.

Reading similarity percentiles

Every colored tract shows a within-brand percentile rank (0–100). This number means:

• 0–49th percentile: Below the national median for this brand. Uncolored on the map.
• 50–79th percentile: Around or slightly above median. Visible but dim.
• 80th percentile: High similarity; strong signal.
• 90th+ percentile: Exceptional match to the brand’s archetype; the most promising discovery.

Critical: Not comparable across brands

A Trader Joe’s neighborhood at the 85th percentile is not comparable to a Starbucks neighborhood at the 85th percentile. Each brand gets its own percentile distribution. Trader Joe’s tracts cluster tightly on brand characteristics (distinctive chain), so an 85th percentile Trader Joe’s represents a more selective match. Starbucks occupies far more diverse neighborhoods (ubiquitous), so its percentiles are more spread. Always compare within a single brand.

Store overlay

If you toggle Show stores in the map controls, the brand’s actual store locations appear as white circles with a colored ring (the color matches the brand). This lets you:

• See where the brand already operates (which tracts have stores).
• Visually cross-reference store locations with the resemblance ranking.
• Spot geographic gaps: high-similarity regions with no stores yet.

Stores are placed on the map via OpenStreetMap and represent the store locations used to build the brand’s archetype.

The neighborhood detail panel

Click any tract on the map to open the detail panel on the right. It contains nine sections, top to bottom:

1. Header: tract name, percentile, and status

At the top you see:

• Tract label (a Census-named area, e.g., “Greenville-Spartanburg, SC”).
• Similarity percentile in the brand’s color (e.g., “82nd percentile”). At or above the 99th percentile it is shown to one decimal place, so the top of the list does not collapse into a wall of identical “100th” readouts.
• An absolute-fit band chip — Strong, Moderate, or Weak — next to the percentile. Unlike the percentile (a within-brand rank), the band measures the tract’s raw distance to the archetype against the brand’s own store neighborhoods, so it is comparable across brands and does not inflate every brand’s best tract to the top. See how it works.
• A small ⓘ glyph next to the percentile. Hovering it shows a one-line caveat: the number is resemblance to the brand’s store neighborhoods on open Census features, not a prediction of sales, foot traffic, or success, and it points to the Method & data page for the full explanation.
• “Resemblance to [Brand]‘s store neighborhoods” — a reminder of what the score measures.
• Status tags:
  • “Already has a [Brand]” (if the selected tract contains an existing store).
  • “No [Brand] in this tract” (if open for potential expansion).
  • Distance to the nearest brand store (e.g., “nearest: 2.4 km”).
  • A low ACS reliability badge when the tract has a small population, a missing income estimate, or a large income margin of error — a signal to treat its feature values as noisy.
• A “Not a fit?” control to flag a lookalike that is wrong on the ground; flagging hides it from the ranked list, and once you have flagged a few, the tool surfaces the features your rejected tracts most share.
• A star to save the neighborhood to your shortlist.

Note

The nearest-store distance is measured from the tract centroid to the closest store location. It helps you gauge expansion distance if you want incremental growth.

2. Winners vs. failures (custom upload only)

If you’ve uploaded your own store data with a performance or status column, this section appears. It shows two bars:

• Resembles your winners (green bar): the percentile of how closely this tract matches the archetype of your high-performing stores.
• Resembles your failures (red bar): the percentile of how closely it matches stores you flagged as failed or low-performing.

A neighborhood with a high “winners” score and low “failures” score is a strong prospect under your own ground truth.

Note

This section only appears when you use the custom upload feature with performance data.

3. Neighborhood fingerprint vs. brand archetype

A radar (spider) chart compares the tract against the brand’s average across all 21 features:

• Blue/colored area = the brand’s archetype (the average of all neighborhoods where the brand has stores).
• Light gray area = this specific tract’s feature values.

The 21 features are displayed as axes: Income, Education, Density, Age, Ethnicity, and Retail Context (grocery, restaurants, cafés, shopping). Where the two polygons overlap closely, the tract matches the brand. Where they diverge, you see the differences.

The radar is most useful for visual pattern matching: you can see at a glance whether the tract is denser/older/wealthier than the brand average, or matches it across the board.

4. Robustness badge

A small colored chip labeled:

• Robust (green): This neighborhood’s high rank is stable across different weighting scenarios. It matches the brand on fundamental characteristics.
• Fairly robust (yellow): The match holds up under most weighting adjustments, but is somewhat sensitive to theme priorities.
• Weighting-sensitive (orange/red): This neighborhood’s high rank depends heavily on how certain themes (e.g., Affluence, Urbanism) are weighted. It may drop if priorities change.

The robustness test re-scores the tract under equal weighting of themes and with each theme removed one at a time. If it stays in the high percentiles across all variations, it is robust.

Tip

Use this to distinguish true archetype matches from neighborhoods that rank high only because your filter weights favor a particular characteristic.

5. Nearby chains (within 6 km)

Shows which of the tracked brands — Trader Joe’s, Whole Foods Market, Sprouts Farmers Market, Chipotle Mexican Grill, Starbucks, Costco Wholesale, Dollar General, Tractor Supply Co., Sweetgreen, H Mart, Cracker Barrel — have a store within 6 kilometers of this tract’s center.

Each entry shows the brand, the distance, and a colored dot. This is a competitive-density snapshot: useful to see if this area already has dense retail presence from tracked competitors, or if it is relatively uncontested.

If the list is empty, the tract is an uncontested pocket among the tracked brands.

6. Why it matches (or closest features if the overall match is modest)

A list of the top 3–4 features where this tract is closest to the brand’s archetype:

• If the overall similarity is 82nd percentile or higher, the heading reads “Why it matches” — these are the strongest drivers of resemblance.
• If the overall similarity is below 82nd percentile, the heading reads “Closest features (overall resemblance is modest)” — acknowledging that the match is weaker overall.

For each feature, you see:

• The feature name (e.g., “Median Household Income”).
• The tract’s value (e.g., “$67,400”).
• A visual bar showing how close this feature is to the brand’s archetype.
• A plain-English comparison: “Close to [Brand]‘s typical $65,000” or “Higher than [Brand]‘s typical.”

Resemblance, not prediction

High similarity on income and education does not mean sales will be high. It means the neighborhood looks like where the brand already operates. Use this to narrow your search, not as a revenue forecast.

7. Where it differs — check these

The top 3 features where this tract diverges most from the brand’s archetype:

• Feature name and the tract’s actual value.
• A visual bar showing the gap.
• A comparison: e.g., “Lower than Chipotle’s typical 22% renters” or “Higher than Trader Joe’s typical median age.”

Use this section to spot potential friction. If a brand typically operates in dense, walkable neighborhoods and this tract has a very low transit-commute percentage, that is a material difference worth investigating further.

8. Full feature comparison (by theme group)

A table organized by the 6 thematic feature groups:

1. Income, wealth & housing cost: median household income, per-capita income, median home value, median gross rent, poverty rate.
2. Education: bachelor’s degree or higher percentage.
3. Density & transportation: population density, households without a vehicle, walk/bike/transit commute, renter-occupied housing.
4. Age & household type: median age, average household size, households with children.
5. Race & ethnicity: White non-Hispanic, Hispanic/Latino, Asian non-Hispanic percentages.
6. Retail & dining context: all POI density, grocery stores, restaurants, cafés, shopping/apparel (per km²).

Each row shows:

• Feature name.
• This tract value with an inline bar (gray) showing where it falls on the national 1st–99th percentile.
• [Brand] avg value with an inline bar (brand color) showing the archetype’s position.

This table is the most detailed comparison; use it when you need to audit a neighborhood thoroughly or explain results to a team.

Note

Some context fields (total population, Black non-Hispanic %, unemployment rate) are displayed in the full data but not scored. They give you additional context.

9. Plain-English assessment

A short paragraph summarizing the neighborhood:

• For a strong match (82nd+ percentile): “On observable Census features, this neighborhood closely resembles [Brand]‘s store neighborhoods, especially on [top 3 features]. It diverges most on [biggest gap]; if you are considering this tract for other reasons, that is the first thing to check.”
• For a modest match (below 82nd percentile): “This neighborhood is only a moderate resemblance overall ([X]th percentile). Its closest features to [Brand]‘s are [top 3]. It diverges most on [biggest gap].”

The assessment always concludes with: “This is a description of resemblance, not a prediction that a store would perform here.”

Where the honesty caveat lives

The detail panel no longer repeats a paragraph-long disclaimer at the bottom. Instead the same caveat is attached to the ⓘ glyph on the score line (section 1) as a hover tooltip, and the full explanation lives one click away on the Method & data page, opened from the link at the bottom of the left rail. The message is unchanged: a high percentile means the neighborhood looks like places the brand already operates; it does not predict sales, foot traffic, or that a store would succeed here. Observable neighborhood resemblance is a weak predictor of revenue, so the tool is for discovery and triage, not site selection alone.

How the map updates with filters and weights

If you adjust the factor weight sliders (Balanced, Affluence-led, Urbanism-led, Community-led), the map re-scores live:

• Colors shift as themes are prioritized differently.
• Percentile ranks change for each tract.
• The detail panel updates to reflect new drivers and gaps.

This is a scenario analysis tool, not a claim about causal importance. Dragging the Urbanism slider up to 2× does not mean urbanism is twice as important in reality; it means “let me see what neighborhoods would rank highest if I cared more about density and transit.”

Similarly, if you compare two brands, the map becomes a diverging map where:

• Hue indicates which brand a tract leans toward, using a fixed, colorblind-safe blue-and-orange pair (blue for brand A, orange for brand B) rather than the brands’ own colors, so a red-versus-green pairing can’t hide the lean direction.
• Brightness shows how strongly the tract resembles either brand.

A neighborhood that is very bright and strongly blue is an excellent archetype match for brand A. A dimly colored neighborhood is a weak match for both.

Key limitations to remember

• Similarity percentiles are not comparable across brands. Trader Joe’s 85th percentile is not equivalent to Starbucks’ 85th percentile; each brand has its own distribution.
• The scoring is observable resemblance only. The tool does not account for foot traffic, local business conditions, permitting, labor costs, or anything not captured in Census and POI data.
• ACS Census data carries a 5-year lag and sampling error. Smaller tracts have wider confidence intervals. Always pair results with current local knowledge.
• OSM store coverage is good for large chains but imperfect. A few stores may be missing or mislocated, which can shift the archetype slightly.
• High similarity does not predict sales. See the honesty rule in what it is.

Next steps

Once you have identified promising neighborhoods on the map:

• Star them into your shortlist (use the star icon in the detail panel) for later review.
• Export a PDF report with per-tract statistics, drivers, and your notes.
• Upload your own stores if you have performance or failure data; LookAlike will re-score based on your ground truth.
• Filter by metro area to focus on a specific region and see a ranked list of that metro’s neighborhoods.

See uploading custom data and the method for more detail.