Allergen Filter Analytics

Understand what dietary needs your diners have by analyzing allergen filter usage.

Why This Matters

Allergen filter data tells you:

• What allergies your diners have
• Where your menu may have gaps
• How to better serve dietary needs
• What items to develop next

Filter Usage Overview

Filter Adoption

Percentage of visitors who use allergen filters:

Total Visitors: 1,000
Used Filters: 320 (32%)

Benchmarks:

• 20-30% = Typical
• 30-40% = Health-conscious area
• 40%+ = Strong dietary focus

Trend Over Time

Track filter usage trends:

• Growing = more dietary awareness
• Declining = audience shift?
• Seasonal patterns

Most Filtered Allergens

See which allergens diners avoid most:

Filter Combinations

Common allergen combinations:

Most Common:
1. Gluten only (45%)
2. Milk + Gluten (18%)
3. Peanuts + Tree Nuts (12%)
4. Milk only (10%)
5. Multiple (3+) allergens (15%)

Insights:

• Design combos safe for common pairings
• Highlight items safe for multiple allergens

Safe Option Analysis

Options Per Allergen

How many safe items exist for each allergen:

Gap Analysis

Identify opportunities:

• Low % + High filtering = Major gap
• High % + Low filtering = Well-served audience
• Low % + Low filtering = Lower priority

Filter-to-Order Correlation

Do Filtered Visits Convert?

Track whether filter users:

• Stay on menu longer
• View more items
• Return more often

Comparison

Non-filter users:
- Avg. session: 2:30
- Items viewed: 4.2

Filter users:
- Avg. session: 3:45
- Items viewed: 6.8

Filter users often more engaged because they’re actively searching.

Time-Based Patterns

Filter Usage by Day

Monday:    ████████ 35%
Tuesday:   ███████ 32%
Wednesday: ███████ 30%
Thursday:  ███████ 31%
Friday:    █████ 25%
Saturday:  █████ 24%
Sunday:    ██████ 28%

Filter Usage by Meal

Breakfast: ██████████ 38%
Lunch:     ████████ 34%
Dinner:    █████ 26%

Health-conscious diners often more prevalent at certain times.

Location Patterns

If multi-location:

By Location

Downtown:   ██████████ 42%
Suburbs:    ███████ 28%
Mall:       █████ 22%
Airport:    ████████ 35%

Location-Specific Insights

• Different locations may serve different demographics
• Consider location-specific menu tweaks
• Staff training may vary by location

Using This Data

Menu Development

Based on filter data:

1. Identify most-filtered allergens
2. Check safe options availability
3. Develop new items to fill gaps
4. Highlight safe options in descriptions

Marketing

Target dietary communities:

• “Extensive gluten-free options”
• “Nut-free friendly kitchen”
• Feature safe options in ads

Staff Training

Focus training on common needs:

• “32% of visitors filter for gluten”
• “Top 3 allergens to know: Gluten, Milk, Peanuts”

Reports

Generate Reports

1. Navigate to Analytics > Allergen Filters
2. Select date range
3. Click Export
4. Choose format

Report Contents

• Filter usage over time
• Per-allergen breakdown
• Combination analysis
• Safe option coverage
• Recommendations

Best Practices

1. Check monthly - Patterns may shift
2. Compare to menu - Match filter demand with safe options
3. Share with kitchen - Inform menu development
4. Track after changes - Did new items impact filters?