chevron_left Back to Candidates @if (data) {
{{ data.candidateName?.charAt(0) }}
{{ data.postName }} Voter Influence Analysis

{{ data.candidateName }}

@if (hasCriteria(data)) {
Target Criteria: @if (data.postGenderType && data.postGenderType !== 'ANY') { Gender: {{ data.postGenderType }} } @if (data.postMinAge && data.postMaxAge) { Age: {{ data.postMinAge }}–{{ data.postMaxAge }} yrs } @else if (data.postMinAge) { Min Age: {{ data.postMinAge }} yrs } @else if (data.postMaxAge) { Max Age: {{ data.postMaxAge }} yrs } @if (data.postMinShareHolding) { Min Shares: {{ data.postMinShareHolding }} }
}
}
@if (loading) {

Building voter analysis...

} @else if (error || !data) {
error_outline

{{ errorMessage || 'Analysis not available.' }}

Return to Candidates
} @else {
how_to_vote
{{ data.actualEligibleVoters }}
Post-Eligible Voters
{{ eligiblePct(data) }}% of shareholders
group
{{ data.totalActiveShareholders }}
Total Shareholders
Active members
cake
{{ data.eligibleByAge }}
@if (!data.postMinAge && !data.postMaxAge) { Age-Eligible } @else { Age-Eligible ({{ data.postMinAge }}–{{ data.postMaxAge }}) }
Fits age threshold
diversity_3
{{ data.casteMatchCount }}
Same Social Category
Matches candidate
account_balance
{{ data.activeLoanHolders }}
Active Loan Holders
With active accounts
family_restroom
{{ data.shareholdersWithFamily }}
With Family Records
Household influence
people_outline

Demographic & Professional Profile

6 Analysis Dimensions
people
Gender Distribution @if (data.candidateGender) { Candidate: {{ data.candidateGender }} }
{{ data.totalActiveShareholders }} total
@for (item of data.genderBreakdown; track item.label; let i = $index) {
{{ item.label }} @if (item.match) { ★ Match } {{ item.percent }}%
}
cake
Age Group Distribution @if (data.candidateAge) { Age: {{ data.candidateAge }} yrs }
{{ data.totalActiveShareholders }} total
@for (item of data.ageBreakdown; track item.label; let i = $index) {
{{ item.label }} Group @if (item.match) { ★ Match } {{ item.percent }}%
}
temple_hindu
Religion Profile
@if (data.religionBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.religionBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
} @else {

No religion data recorded yet.

}
work
Occupation Profile
@if (data.occupationBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.occupationBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
} @else {

No occupation data recorded yet.

}
school
Education Level
@if (data.educationBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.educationBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
} @else {

No education data recorded yet.

}
favorite
Marital Status Profile
@if (data.maritalBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.maritalBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
} @else {

No marital status data recorded yet.

}
public

Social & Geographic Influence

3 Analysis Dimensions
location_on
Area / City Distribution @if (data.candidateArea) { Candidate: {{ data.candidateArea }} }
{{ data.totalActiveShareholders }} total
@for (item of data.areaBreakdown; track item.label; let i = $index) {
{{ item.label }} @if (item.match) { ★ Match } {{ item.percent }}%
}
diversity_3
Social Category (Caste) @if (data.candidateCaste) { Candidate: {{ data.candidateCaste }} }
{{ data.casteMatchCount }} match
@for (item of data.casteBreakdown; track item.label; let i = $index) {
{{ item.label }} @if (item.match) { ★ Match } {{ item.percent }}%
}
account_tree
Sub-Caste Breakdown @if (data.candidateSubCaste) { Candidate: {{ data.candidateSubCaste }} }
@if (data.subCasteBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.subCasteBreakdown; track item.label; let i = $index) {
{{ item.label }} @if (item.match) { ★ Match }
{{ item.count }} members {{ item.percent }}%
}
} @else {

No sub-caste data recorded for shareholders yet.

}
savings

Financial & Family Engagement

5 Analysis Dimensions
account_balance_wallet
Share Holding Distribution
{{ data.totalActiveShareholders }} total
@for (item of data.shareHoldingBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
history
Member Tenure
{{ data.totalActiveShareholders }} total
@for (item of data.tenureBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
currency_rupee
Monthly Income Distribution
@if (data.monthlyIncomeBreakdown?.length > 0) {
{{ data.totalActiveShareholders }} total
@for (item of data.monthlyIncomeBreakdown; track item.label; let i = $index) {
{{ item.label }} {{ item.percent }}%
}
} @else {

No monthly income data recorded yet.

}
savings
Savings Account Depth {{ activeSavingsPct(data) }}% Penetration
@if (data.savingsBreakdown?.length > 0) {
{{ data.activeSavingsHolders }} active savings
@for (item of data.savingsBreakdown; track item.label) {
{{ item.label }} {{ item.percent }}%
}
{{ data.activeSavingsHolders }}
Active Savings
{{ data.totalActiveShareholders - data.activeSavingsHolders }}
No Savings
{{ activeSavingsPct(data) }}%
Penetration Rate
info_outline High savings penetration means members are financially active and have stronger ties to the institution — a positive signal for candidate support.
} @else {

No savings data available.

}
account_balance
Financial Engagement — Active Loans
{{ activeLoanPct(data) }}% active
@for (item of data.loanHolderBreakdown; track item.label) {
{{ item.label }}
{{ item.count }}
{{ item.percent }}% of shareholders
}
info_outline Members with active loans have an ongoing financial relationship, indicating higher engagement and interest in institutional decisions.
auto_graph

Voter Influence Insights

Multi-Dimension Analysis
hub
Multi-Dimension Voter Alignment Candidate's core voter base overlap
hub
{{ data.crossMatchCount }}
{{ crossMatchPct(data) }}%
Core Base — Same Caste & Same Area
diversity_3
{{ data.casteMatchCount }}
{{ casteMatchPct(data) }}%
Same Social Category (Caste Alignment)
location_on
{{ data.areaMatchCount }}
{{ areaMatchPct(data) }}%
Same Area / City (Geographic Proximity)
savings
{{ data.activeSavingsHolders }}
{{ activeSavingsPct(data) }}%
Active Savings Holders (Financially Engaged)
lightbulb The Core Base — voters matching both the candidate's social category AND geographic area — represents the strongest aligned voter segment. Caste, area, and financial engagement are the three strongest predictors of voter support in cooperative elections.
}