Single-detached homes
85.0%Home maintenance, outdoor, renovation, utilities, and property-related campaigns may deserve a larger test.
Ontario postal region
K0C demographics and market profile
See what distinguishes this audience, how it compares with other markets, and which local characteristics can shape campaign decisions in Stormont, Dundas and Glengarry United Counties.
AudienceScoutK0C · Stormont, Dundas and Glengarry United CountiesLoading the K0C boundary…
Selected postal region
Market profile
A market of 52,838 people
Size the opportunity, understand its household composition, and identify the local patterns that make K0C different from the typical Canadian postal region.
Population52,838
Households21,675
Median income$84,000
Average age45.1
K0C market summary
What distinguishes this postal-region audience
K0C represents 52,838 residents and 21,675 households in Stormont, Dundas and Glengarry United Counties. Its average household contains 2.4 people, creating a local market that can be evaluated by both total reach and household composition.
The clearest difference from the Canadian postal-region benchmark is detached housing: 85.0%, or 32.4 percentage points above the benchmark. Immigrant population is 5.7%, 17.2 percentage points below the benchmark.
For campaign planning, these patterns give K0C a clear audience profile. They provide concrete criteria for deciding whether the region fits an offer, which audience characteristics should shape creative, and how it should be compared with other parts of Stormont, Dundas and Glengarry United Counties.
Audience matching
Find more regions that resemble K0C
To find regions with a profile similar to K0C, begin with home ownership near 81.9% and university education near 13.6%. Adjust each minimum to make the audience broader or more selective.
Match This AudienceDistinctive market signals
The characteristics with the largest local differences
These four characteristics show the largest available differences between K0C and the Canadian postal-region benchmark.
Immigrant population
5.7%Use the wider demographic and household profile to determine whether localized or broad-market creative is the stronger starting point.
Owner households
81.9%Prioritize home, property, renovation, financial, and longer-term service propositions where relevant.
Bachelor's degree or higher
13.6%Use direct, practical language that demonstrates the everyday value of the offer.
Detailed comparison
How K0C compares with the Canadian benchmark
Use the difference column to identify which measures are most useful for creative, offer, channel, and geographic targeting decisions.
| Measure | K0C | Canada FSA benchmark | Difference |
|---|---|---|---|
| Median household income | $84,000 | $85,788 | 2.1% below |
| Average household size | 2.4 people | 2.4 people | 1.2% below |
| Owner households | 81.9% | 66.5% | 15.4 percentage points above |
| One-person households | 25.1% | 29.4% | 4.3 percentage points below |
| Families with children | 31.9% | 34.0% | 2.1 percentage points below |
| Bachelor's degree or higher | 13.6% | 26.5% | 12.9 percentage points below |
| Immigrant population | 5.7% | 22.9% | 17.2 percentage points below |
| Worked from home | 19.7% | 23.8% | 4.1 percentage points below |
Local market context
Community activity around the audience
AudienceScout connects 92 local facility records with K0C. Recreation is the largest represented category with 34 records, adding another signal for local media, partnership, service-area, and campaign planning.
Education33
Health care20
Culture and art5
Recreation34
Platform audience potential
Match channel planning to the local age mix
Facebook has the largest modeled audience among the displayed channels at 34,569 people. Compare that opportunity with the other estimates before setting the regional channel mix and budget.
26,238YouTube estimate · 61.0%
34,569Facebook estimate · 80.4%
20,700Instagram estimate · 48.1%
9,993TikTok estimate · 23.2%
Practical campaign implications
Turn the strongest K0C signals into campaign tests
Use these as evidence-based starting hypotheses, then validate them against campaign performance and your own customer results.
- Single-detached homes: 85.0%32.4 percentage points above the Canadian benchmark
Home maintenance, outdoor, renovation, utilities, and property-related campaigns may deserve a larger test.
- Immigrant population: 5.7%17.2 percentage points below the Canadian benchmark
Use the wider demographic and household profile to determine whether localized or broad-market creative is the stronger starting point.
- Owner households: 81.9%15.4 percentage points above the Canadian benchmark
Prioritize home, property, renovation, financial, and longer-term service propositions where relevant.
Related market context
Compare similar-sized Ontario postal regions
This directory represents Stormont, Dundas and Glengarry United Counties with one postal region. These Ontario markets are selected by population similarity for a useful market comparison.
K0C audience questions
Using this postal-region profile
How large is the audience in K0C?
K0C represents 52,838 residents and 21,675 households in Stormont, Dundas and Glengarry United Counties. The average household size is 2.4 people.
What demographic characteristics stand out in K0C?
Single-detached homes is 85.0%, 32.4 percentage points above the Canadian postal-region benchmark; Immigrant population is 5.7%, 17.2 percentage points below the Canadian postal-region benchmark; Owner households is 81.9%, 15.4 percentage points above the Canadian postal-region benchmark.
How does K0C compare with another postal region?
K0M is one useful Ontario market comparison because its population is similar to K0C. It has 4.8% lower median income · 5.3 years older on average.
How can I find other regions that match the K0C audience?
To find regions with a profile similar to K0C, begin with home ownership near 81.9% and university education near 13.6%. Adjust each minimum to make the audience broader or more selective.
How can customer postal codes be analyzed in K0C?
Import postal codes to measure customer concentration in K0C, compare the count with the region's population and households, and use its strongest demographic characteristics to decide whether similar regions belong in the campaign.