A customer's insights
Read a customer's lifetime value, health score, behaviours, predictions and equipment outlook.
Open any customer and scroll to Insights. It's worked out from that customer's own records and appears once they have a completed job or a membership.
Figures
| Figure | What it means |
|---|---|
| Lifetime value | Everything they've paid you, net of refunds (tips aren't counted) |
| Last 12 months | What they paid in the last year |
| Average ticket | Their average invoice, not counting membership fees |
| Jobs | Completed jobs out of all their jobs |
| Last visit / Next visit | Their most recent and next booked visit |
| Membership | Their plan and when it ends |
| Open balance | What they owe now, and how many days they usually take to pay |
Health score
A score out of 100, where 70 is a typical customer. Under What moved it you see each thing that raised or lowered the score, with its points: for example being on their usual rhythm, having a visit booked, being a member, paying late or leaving a bad review. The score falls in a band: Good (70 and up), Watch (45 to 69) or At risk (below 45).
Behaviours
Tags such as Books online, Prefers text, Pays on time, Approves quotes quickly, Price-sensitive, Seasonal, Promoter or High value. Open Why we think so to see the evidence behind each one.
Predictions
Each prediction shows how likely it is, how confident ServFlo is, when it's expected, and Why? with the reasons and the data used:
- Service due: when they'll next need a visit.
- Equipment replacement: for each unit, how likely it needs replacing soon.
- Lapse risk: how likely they are to stop using you.
- Late payment risk: how likely they are to pay late.
- Quote acceptance: for each open quote, how likely they are to approve it.
Equipment outlook
A table of the equipment at their current properties: type, install date, age against its expected lifespan, refrigerant, condition, repairs in the last 24 months and an Outlook: Replace now, Plan replacement, Healthy or Age unknown.
Predictions get better with better data. Record the install year, equipment type and condition on equipment, and set a usual repeat interval on your service types.
Technicians only see insights for customers on their own jobs, and never see money figures or payment predictions.