Understand who your customers are, what they are worth, and how they buy, so you can target the right audiences and tune your offer.
Quick overview
This dashboard profiles your customer base: age, gender and language mix, where they come from, when and how far in advance they book, basket size, add-on spend, value per visitor, lifetime value, and value tiers (VIP, Regular, Occasional). Use it to segment audiences, localise your content, target loyalty actions, and tune pricing and timing.
Who this is for
Primary audience: Marketing and growth managers
When to use it
Decision it helps you make: identify your highest-value and highest-potential customer segments, and decide where to focus loyalty, localisation, and pricing or timing actions.
Why use this dashboard
Use it to know your audience before you act. You can see which age groups and regions drive your business, which languages to communicate in, how far ahead people book, and which customers are worth the most over their lifetime. That makes it easier to decide who to reward, who to win back, and how to position your offer.
Access and default filters
📌 How to access: app.smeetz.com > Analytics > Dashboards > Customer intelligence
Default date range: a recent sales window (adjust with the Transaction date filter).
Data currency: the dashboard shows the time of its last data refresh in the header. Check that tile to see how up to date the figures are.
Filter guide
Filter | What it does | Typical values |
Transaction currency | Limits the dashboard to one currency. | CHF, EUR |
Transaction date | Sets the time window for sales. | Last 30 days, this season |
Product name | Focuses on one or more products. | Any of your products |
Channel | Focuses on one or more acquisition or sales channels. | Online, point of sale |
Customer country | Filters by the customer's country of origin. | Switzerland, France |
Customer canton code | Filters by Swiss canton. | VD, GE, ZH |
Customer age | Filters by customer age. | Any age range |
Customer gender | Filters by customer gender. | Female, Male |
Visuals explained
Header band
Dashboard purpose: a one-line reminder of what the dashboard is for.
Last data refresh: the date and time the figures were last updated (Swiss time).
Headline figures
Revenue per visitor (RPV): the average revenue earned per customer.
Average order value (AOV): the typical revenue per order.
Avg tickets per order: the average number of items per order (tickets, add-ons, and standalone items), after cancellations.
Avg booking lead time: how many days in advance, on average, customers book.
Avg ancillary spend per visitor: the average add-on spend per customer.
Avg customer lifetime value: the average total spend per customer, across all of their paid bookings with you.
Who are my customers?
Gender split: the gender mix of your customer base.
Age group mix: how customers are distributed across age groups, with percentages.
Language preference: the language of each customer's most recent booking, with counts and percentages.
Customers by value tier: your active customers split by lifetime spend into VIP (top 10%), Regular (the next 40%), and Occasional (the bottom 50%).
Where do they come from?
Top regions by customers: canton and municipality ranked by number of customers, with their share and associated revenue.
Customer origins: a map of customers by country.
Customer density by zip / canton: a bubble map showing where your customers are concentrated.
When do they book?
Booking hour distribution: bookings by hour of the day.
Bookings by age group and hour: a heatmap of booking volume by age group and hour of the day.
Booking lead time: bookings grouped by how far in advance they were made.
Example scenarios
Localise your communication: use Language preference and Customer origins to decide which languages and regions to prioritise.
Reward your best customers: use Customers by value tier and Avg customer lifetime value to build a VIP loyalty action.
Time a campaign: use Booking hour distribution and Booking lead time to choose when to send offers and how far ahead to promote.
Data freshness
How current is the data: the dashboard header shows the time of the last data refresh. Check that tile to see how up to date the figures are.
Known limitations
Gender is often blank. It comes from an optional field that is rarely filled in, so the Gender split skews heavily to Unknown.
Age needs a birth date. Age, the age group mix, and the age-by-hour heatmap only include customers who have a birth date on file.
Maps need an address. Customer origins, the density map, and Top regions only include customers with a complete address.
Demographic filters reduce totals. Filtering by country, canton, age, or gender drops customers who are missing that detail, so totals shrink.
Lifetime value counts paid orders only. Guest, unpaid, fully refunded, and gift-card-only orders are excluded from lifetime value and value tiers.
Value tiers are per currency. A customer who booked in two currencies is ranked separately in each. With no currency selected, lifetime value mixes currencies, the same as every other revenue figure on the dashboard.
Links
Related dashboards: Marketing performance, Automated email campaigns