Single-detached homes
78.1%Home maintenance, outdoor, renovation, utilities, and property-related campaigns may deserve a larger test.
Quebec postal region
G3N demographics and market profile
See what distinguishes this audience, how it compares with other markets, and which local characteristics can shape campaign decisions in Sainte-Catherine-de-la-Jacques-Cartier.
AudienceScoutG3N · Sainte-Catherine-de-la-Jacques-CartierLoading the G3N boundary…
Selected postal region
Market profile
A market of 11,114 people
Size the opportunity, understand its household composition, and identify the local patterns that make G3N different from the typical Canadian postal region.
Population11,114
Households4,475
Median income$100,000
Average age37.6
G3N market summary
What distinguishes this postal-region audience
G3N represents 11,114 residents and 4,475 households in Sainte-Catherine-de-la-Jacques-Cartier. Its average household contains 2.5 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: 78.1%, or 25.5 percentage points above the benchmark. Immigrant population is 1.7%, 21.2 percentage points below the benchmark.
For campaign planning, these patterns give G3N 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 Sainte-Catherine-de-la-Jacques-Cartier.
Audience matching
Find more regions that resemble G3N
To find regions with a profile similar to G3N, begin with home ownership near 86.8% and household income near $100,000. 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 G3N and the Canadian postal-region benchmark.
Immigrant population
1.7%Use the wider demographic and household profile to determine whether localized or broad-market creative is the stronger starting point.
Owner households
86.8%Prioritize home, property, renovation, financial, and longer-term service propositions where relevant.
Median household income
$100,000Test premium, higher-consideration, or value-led offers grounded in a clear customer benefit.
Detailed comparison
How G3N 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 | G3N | Canada FSA benchmark | Difference |
|---|---|---|---|
| Median household income | $100,000 | $85,788 | 16.6% above |
| Average household size | 2.5 people | 2.4 people | 2.9% above |
| Owner households | 86.8% | 66.5% | 20.3 percentage points above |
| One-person households | 23.5% | 29.4% | 5.9 percentage points below |
| Families with children | 39.9% | 34.0% | 5.9 percentage points above |
| Bachelor's degree or higher | 19.5% | 26.5% | 7.0 percentage points below |
| Immigrant population | 1.7% | 22.9% | 21.2 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 8 local facility records with G3N. Education is the largest represented category with 6 records, adding another signal for local media, partnership, service-area, and campaign planning.
Education6
Health care1
Culture and art0
Recreation1
Platform audience potential
Match channel planning to the local age mix
Facebook has the largest modeled audience among the displayed channels at 6,780 people. Compare that opportunity with the other estimates before setting the regional channel mix and budget.
5,456YouTube estimate · 66.1%
6,780Facebook estimate · 82.1%
4,361Instagram estimate · 52.8%
2,170TikTok estimate · 26.3%
Practical campaign implications
Turn the strongest G3N 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: 78.1%25.5 percentage points above the Canadian benchmark
Home maintenance, outdoor, renovation, utilities, and property-related campaigns may deserve a larger test.
- Immigrant population: 1.7%21.2 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: 86.8%20.3 percentage points above the Canadian benchmark
Prioritize home, property, renovation, financial, and longer-term service propositions where relevant.
Related market context
Compare similar-sized Quebec postal regions
This directory represents Sainte-Catherine-de-la-Jacques-Cartier with one postal region. These Quebec markets are selected by population similarity for a useful market comparison.
G3N audience questions
Using this postal-region profile
How large is the audience in G3N?
G3N represents 11,114 residents and 4,475 households in Sainte-Catherine-de-la-Jacques-Cartier. The average household size is 2.5 people.
What demographic characteristics stand out in G3N?
Single-detached homes is 78.1%, 25.5 percentage points above the Canadian postal-region benchmark; Immigrant population is 1.7%, 21.2 percentage points below the Canadian postal-region benchmark; Owner households is 86.8%, 20.3 percentage points above the Canadian postal-region benchmark.
How does G3N compare with another postal region?
G3L is one useful Quebec market comparison because its population is similar to G3N. It has 28.5% lower median income · 7.1 years older on average.
How can I find other regions that match the G3N audience?
To find regions with a profile similar to G3N, begin with home ownership near 86.8% and household income near $100,000. Adjust each minimum to make the audience broader or more selective.
How can customer postal codes be analyzed in G3N?
Import postal codes to measure customer concentration in G3N, 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.