After sales
Detect customer churn early
Sales and after sales see the same customer for the first time — in the same model.
In the product
Which customers on a charging contract had support cases on the same topic last quarter — and whose contract expires within 90 days?
412 customers on an active charging contract had at least one support case on authentication at charge points last quarter.
The context:
- For 118 of them the contract expires within 90 days
- 74 of those cases were solved at the first support level, 44 escalated
- The escalated cases cluster on 2 vehicle series sharing one option variant
Recommendation: Approach the 118 expiring contracts before renewal, starting with the 44 escalated cases: that is where churn is most likely.
QuellenContractsCharging sessionsSupport casesVehicle master dataCustomer
What changes
Before
- Customer, vehicle, contract, charging session and support case in separate systems, contracts sometimes in several.
- No linkage that reflects the actual process landscape.
- Merging, cleaning and analysis by hand; one dashboard per silo.
With d.AP
- Questions that were unanswerable before are answered in minutes.
- One agreed understanding of the KPIs, across departments instead of per dashboard.
- New perspectives on the data without a new data project.
What it delivers
−90%
per further analysis
Less effort: the model stands instead of being rebuilt per question.
−70%
versus the alternative build
Lower cost for the same analytical capability.
0analysts
Business teams query their own data in natural language.
Connected data sources
CRMContract systemsCharging infrastructureTicket systemVehicle master data
Reference · Automotive OEM
Use Cases
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