Post-launch intelligence
Mission Control
Sales, purchase reliability and customer feedback at a glance.
Sales and reviews: supplied reports · Operational metrics: simulated scenario · No live feeds
Needs attention
Investigate affected orders and prepare a briefing.
SIMULATED OPERATIONS| Order / client | Payment method | Current state | Time in state | Amount | |
|---|
Demo rule: pending over 10 minutes, or captured payment without a ticket. Ten minutes is an illustrative threshold, not an agreed SLA.
Sales momentum
Tickets sold · 21 September – 5 October
Tickets sold Limited coverage**Sales records missing: 29 Sep 14:19 – 30 Sep 04:07.
5 Oct includes sales only up to 17:32. All times are Swiss time.
Sales are growing.
The audience is coming back more often.
Week 2 visits rose 34%, while unique visitors stayed almost flat. The pattern suggests deeper use within a stable tracked audience.
Launch ramp-up and incomplete tracking affect this comparison.
How customers buy
18,071 completed orders · all available exports
Ticket shop80% · 14,500 orders
From a trip search20% · 3,571 orders
Opportunity to explore
Make ticket purchase from a connection easier to discover. A search without a purchase is not necessarily a failed purchase.
Where to focus next
Suggested actions from the post-launch analysis
3 priorities01Close the sales export gap
29–30 Sep is incomplete. Around 630 orders are estimated missing.
02Understand the checkout journey
Align iOS and Android events before interpreting drop-off.
03Build on SwissPass adoption
44% of orders are still guest purchases.
Customer voice deserves its own signal
October written reviews · snapshot collected 6 Oct, 09:44 Zurich
1.38 / 5 ★29 reviews · 28 Android, 1 iOS
Access to departures, navigation and readability remain prominent complaints. Ticket-purchase friction also appears.
Sales growth and review sentiment can coexist. This small, self-selected sample does not measure satisfaction across all users.
REVIEW SNAPSHOTSWritten-review sample, not the overall store rating. No new store fetch.
Every star counts
Rating distribution in the selected sample
Daily rating breakdown
| Date | Reviews | 1 ★ | 2 ★ | 3 ★ | 4 ★ | 5 ★ | Average / 5 | 1–2 ★ share |
|---|
What reviewers are reporting
Explore related metrics
Review themes can guide investigation; they do not establish causes.
01“Buying a ticket is difficult”
Inspect checkout activity and payment visibility.
02“Too many steps to see departures”
Compare the reported task with app usage.
03Sales can grow while feedback stays negative
View commercial performance alongside customer feedback.
Historical data
Data coverage
Historical report data and simulated operations
Demo coverage| Source | Available through | Includes | Note |
|---|
Purchase operations Simulated | Illustrative 24-hour cohort | Purchase outcomes and fictional DEMO orders | Requires complete order/payment histories and matching timestamps. No live feed. |
| Backoffice | 5 Oct, 17:32 | Orders, tickets and revenue | Missing hours on 29–30 Sep |
| Matomo | 5 Oct, partial day | Visits, screens and shop events | Consented users only |
| HAFAS / Grafana | 25 Sep, 17:00 | Trip searches and new-app share | Earlier reporting window |
| App reviews | 6 Oct collection | Ratings and complaint themes | Written-review sample; limited iOS coverage |
Metric details
Select a metric for its calculation and source