# Demographics Demographics reveal who lives within your trade area—the population characteristics that determine whether local residents match your target customer profile. GrowthFactor provides detailed demographic breakdowns with national benchmarks and store average comparisons, helping you quickly assess customer fit for any site. *** ### Accessing Demographics {% columns %} {% column valign="middle" %} Demographics display in the results panel when you search a site. The data reflects the population within your currently selected trade area—if you change your trade area settings, demographic figures update automatically. Expand the demographics section to see distribution charts for each category. {% endcolumn %} {% column %}
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*** ### Viewing Options #### Chart View and Table View Toggle between chart and table views using the view toggle in the demographics modal. **Chart View** displays demographic data as visual bar charts comparing local population to national averages and store averages (when available). This view is ideal for quickly spotting demographic patterns and over/under-indexing. **Table View** displays the same data in a table format showing exact population counts and percentages. This view is useful for precise comparisons and when you need specific numerical values. Both views display: * **Local:** Population characteristics for your selected trade area * **National Average:** U.S. benchmark for comparison * **Store Average:** Average demographics across all your existing store locations (when available) *** ### Demographic Categories #### Age Distribution Shows the population breakdown by age group within the trade area. **Age Brackets:** * Under 10 * 10–19 * 20–29 * 30–44 * 45–59 * 60–69 * 70–79 * 80+ These brackets are designed to provide balanced, actionable segments—distinguishing younger families, working-age adults, and retirees in a way that aligns with typical retail customer profiles. **Key Metrics:** * **Largest Group:** The age bracket with the highest population count * **Biggest Difference:** The bracket that deviates most from the national average (over- or under-indexed) * **Median Age:** The midpoint age for the trade area population, compared to the national median and store average median (when available) #### Income Distribution Shows household income distribution within the trade area. **Income Brackets:** * Under $15,000 * $15,000–$24,999 * $25,000–$34,999 * $35,000–$49,999 * $50,000–$74,999 * $75,000–$99,999 * $100,000–$149,999 * $150,000–$199,999 * $200,000 and over The brackets provide granularity at both ends of the spectrum—distinguishing lower-income households that may be price-sensitive and higher-income households that support premium concepts. **Key Metrics:** * **Largest Group:** The income bracket with the most households * **Biggest Difference:** The bracket most over- or under-represented compared to national averages * **Median Income:** The midpoint household income for the trade area, compared to the national median and store average median (when available) #### Race Distribution Shows the racial composition of the trade area population, using U.S. Census categories. #### Education Distribution Shows educational attainment levels for the adult population within the trade area—from less than high school through graduate degrees. #### Gender Distribution Shows the male/female population split within the trade area. #### Presets Tab The Presets tab displays custom demographic variables configured by your organization in Organization Settings. These are organization-specific metrics that matter most to your business, such as household composition, lifestyle indicators, or industry-specific demographic markers. **What's displayed:** * Variable names as configured in your Organization Settings * Local values for the searched trade area * Store average values across your existing locations (when available) *** ### Store Average Demographics Store average demographics show the aggregated demographic profile across all your existing store locations. This comparison helps you understand whether a potential site's demographics match the profile of your successful stores. #### How It Works GrowthFactor calculates store averages by: 1. Generating trade zones around each of your existing stores 2. Retrieving demographic data for each store's trade area 3. Averaging the demographic values across all stores #### When Store Averages Are Shown Store average data appears when: * Your organization has multiple existing stores in the system * Demographic data is available for your store locations * The feature is enabled for your organization If store averages are not displayed, only local and national comparisons will appear. #### Using Store Averages Store average comparisons help you: * **Validate site fit:** Sites with demographics similar to your store average are more likely to perform well * **Identify outliers:** Sites with demographics significantly different from your average may present higher risk or require different strategies * **Refine target customer profile:** Understanding the demographic commonalities across your successful stores helps clarify your ideal customer *** ### Key Demographic Insights Below each chart, GrowthFactor highlights three summary metrics to surface the most important takeaways. #### Largest Group The bracket containing the most people (or households, for income). This tells you the dominant segment in the trade area. **How to use it:** If the largest age group is 30–44, the area skews toward young families. If the largest income group is $50K–$75K, you're looking at a solidly middle-income market. #### Biggest Difference The bracket where the trade area deviates most from national averages—expressed as a percentage difference and whether it's above or below average. **How to use it:** This flags what makes the trade area distinctive. A trade area that's 25% above average in the 20–29 age bracket has a notably young population. One that's 30% below average in the Under $15K bracket has fewer low-income households than typical. #### Median Value The midpoint value (age or income) for the trade area, shown alongside the national median and store average median (when available) for comparison. **How to use it:** Medians cut through distribution complexity to give you a single benchmark. A median income of $85,000 vs. a national median of $75,000 tells you the area is more affluent than average at a glance. If your store average median income is $82,000, this site aligns closely with your existing customer base. *** ### Trade Area Impact Demographics are calculated for the population within your selected trade area boundary. This makes trade area selection critical to demographic analysis. #### Smaller Trade Areas Tighter boundaries (e.g., 5-minute drive, 50% foot traffic zone) show the demographics of your immediate, core customer base. Numbers will be smaller in absolute terms but may be more representative of who actually visits. #### Larger Trade Areas Wider boundaries (e.g., 20-minute drive, 80% foot traffic zone) capture a broader population. This provides larger sample sizes and may smooth out hyperlocal anomalies, but could dilute signals if the outer ring differs significantly from the core. #### Foot Traffic Trade Zones When using Foot Traffic Trade Zones, demographics reflect the areas where visitors actually originate—not just who happens to live nearby. This can produce different (and often more accurate) demographic profiles than radius-based approaches. **Note:** Foot Traffic Trade Zones may show lower absolute population numbers since they're scoped to visitor origins rather than arbitrary boundaries. The data is more precise but covers a more targeted geography. *** ### Data Sources GrowthFactor demographic data is sourced from ESRI and updated regularly. **Age Data:** Based on ESRI demographic data including population estimates by age groups. **Income Data:** Based on ESRI household income data including income distribution across standard brackets. National average benchmarks and store average calculations are derived from these ESRI sources, ensuring consistent and authoritative comparisons. *** ### Using Demographics in Site Selection #### Customer Match The primary question: does the local population match your target customer? If your concept targets young professionals with disposable income, look for: * Over-indexed 25–44 age brackets * Above-average median income * Strong representation in $75K+ income brackets If you serve families with children, look for: * Strong Under 10 and 30–44 age representation (parents and kids) * Median income aligned with your price point #### Comparing to Your Store Base When store average data is available, compare the searched site to your existing successful locations: * **Demographics closely match store average:** The site serves a population similar to your proven customer base—lower risk * **Demographics differ from store average:** The site may attract a different customer segment—assess whether this is an opportunity or a concern * **Some categories match, others differ:** Identify which demographic factors are most critical for your concept's success #### Identifying Mismatches Demographics can disqualify sites quickly. A luxury concept in a trade area with median income 30% below national average faces an uphill battle—regardless of how strong the traffic or visibility metrics look. Conversely, a value-oriented concept in an ultra-affluent area may struggle with perception or format fit, even if raw population numbers seem adequate. #### Contextualizing Other Metrics Demographics add context to other analyses: * **High foot traffic + mismatched demographics** → The traffic may not convert to *your* customers * **Strong competitor performance + aligned demographics** → Validates that your customer base is present and spending * **Weak sales projection + strong demographics** → Other factors (competition, access) may be limiting potential #### Comparing Sites When evaluating multiple opportunities, demographics provide an apples-to-apples comparison lens. Two sites with similar sales projections might have very different demographic profiles—and therefore different risk profiles for your concept. *** ### Best Practices **Start with your customer profile.** Before analyzing a site, know what demographic markers correlate with your brand's success. Which income brackets drive your sales? What age groups over-index in your customer base? **Focus on differences, not just absolutes.** The Biggest Difference metric often reveals more than raw numbers. An area perfectly matching national averages is unremarkable; an area dramatically over-indexed in your target segment is noteworthy. **Use store averages as a benchmark.** When available, store average comparisons provide a brand-specific benchmark more relevant than national averages alone. Sites matching your store average demographics are more likely to perform consistently with your existing portfolio. **Compare multiple trade area configurations.** If demographics look marginal at a 15-minute drive time, check what happens at 10 minutes. You may find a strong core customer base that gets diluted by a weaker outer ring. **Triangulate with foot traffic demographics.** If available, compare radius-based demographics to Foot Traffic Trade Zone demographics. Differences may reveal that your actual customer base differs from the resident population (e.g., daytime workers vs. residents). **Don't disqualify on a single metric.** Demographic mismatches are yellow flags, not automatic disqualifications. A below-average median income might be offset by unusually high population density or lack of competition. **Review preset variables.** If your organization has configured demographic presets in Organization Settings, these are the metrics your team has identified as most important for your concept. Pay close attention to how the site performs on these custom indicators. For related analysis, see Trade Area Analysis, Sales Projections, and Foot Traffic and Brand Rankings.