Reading Your Retention Data: Cohorts, Frequency, and Churn Signals

Why Retention Data Is Your Most Valuable Signal

Most venue operators focus on acquisition — more footfall, more covers, more first-time visitors. But the economics of hospitality are built on repeat business. A guest who visits 4 times per year is worth 4x a one-time visitor. WiFi analytics give you the clearest picture available of who is coming back, how often, and — critically — who is about to stop coming back.

Step 1: Understand the 7-Day, 30-Day, 90-Day Cohort View

Go to Analytics → Retention Cohorts. The cohort table shows groups of guests who first connected in a given week, and tracks what percentage returned in subsequent weeks. Read it left to right: the first column is the cohort size (new guests that week), and each subsequent column shows the retention rate at week 1, week 2, week 4, week 8, and week 12. A healthy retention curve typically drops sharply after week 1 (first-time visitors who don't return quickly) then flattens — indicating a core of regulars. If your curve keeps dropping without flattening, you have a churn problem worth investigating.

Step 2: Benchmark Your Return Rate by Venue Type

Retention benchmarks vary significantly by venue type. Use these as your reference points: Cafes and coffee shops: 35-55% 30-day return rate (guests return frequently by habit). Bars and pubs: 20-35% 30-day return rate (less habitual, more occasion-driven). Hotels: 5-15% 90-day return rate (repeat stays are inherently infrequent). Restaurants: 18-30% 30-day return rate (depends heavily on cuisine type and price point). Retail: 25-40% 30-day return rate. If you're significantly below your benchmark, your retention campaigns, post-visit email sequences, or in-venue experience needs attention. If you're above it, identify what's working and protect it.

Step 3: Read the Peak Hours Heatmap

Navigate to Analytics → Visit Patterns → Heatmap. The heatmap shows visit density by hour of day (y-axis) and day of week (x-axis). Darker cells = more WiFi connections. Use this to: identify your true peak times (vs. anecdotal assumptions), spot underperforming periods you could target with campaigns ("quiet Tuesday lunches"), and plan staffing more accurately. If you run campaigns, you can overlay campaign send dates on the heatmap to see whether a specific send drove an uplift in visits on a given day.

Step 4: Identify At-Risk Guests

Go to Analytics → Guest Segments → At Risk. VoqadoWiFi automatically flags guests whose visit gap exceeds 2x their average inter-visit interval. For example, if a guest typically visits every 7 days and hasn't visited in 14+ days, they're flagged as at-risk. This is a dynamic segment — it updates daily. You can click Create Campaign from Segment directly from this view to launch a win-back email to exactly this group. This is one of the highest-ROI campaigns available because you're targeting guests whose lapse is anomalous, not just occasional visitors.

Step 5: Export Data for Mailchimp Segmentation

If you use Mailchimp for email campaigns, VoqadoWiFi can sync segments automatically (via the Mailchimp integration in Settings → Integrations), or you can export manually. Go to Analytics → Guests → Export CSV. Filter by the criteria you need — e.g., "Visited 3+ times in last 90 days" for your VIP segment, or "Last visit 21-60 days ago" for win-back. The CSV includes: email, first name, last visit date, total visits, and visit frequency score. Upload directly to Mailchimp as a new segment and tag accordingly.

Step 6: Using the Retention Insight Card

On your main Analytics dashboard, the Retention Insight Card gives you a weekly summary: your 30-day retention rate, the change vs previous period, your top returning guest count, and one automated recommendation (e.g., "15 guests are overdue for a visit — consider a re-engagement campaign"). This card is designed to be your weekly check-in point. Spend 3 minutes every Monday reviewing it before making any marketing decisions for the week.

Step 7: What "Good" Looks Like Over Time

In the first 30 days of using VoqadoWiFi, your list will be small and your cohort data thin. By month 3, you'll have enough data to see meaningful patterns. By month 6, you should be able to: predict your busiest days 2-3 weeks out, identify your top 20% of guests by frequency, and run retention campaigns with confidence. The guests who drive 80% of your repeat business will be visible in your data — and once visible, they become targetable, retainable, and protectable.