Conversational Analytics
Executives type questions as if talking to an analyst and get numbers and charts instantly.
AI turns questions into data queries and explains where every number comes from.See details ›Customer Scoring
Score each customer from available data to decide on approvals, credit limits or special care.
B84Score Good
Scoring factors
Go ahead and try it. This screen simulates the system with sample data.
Highlights
Use it for credit approval, finding quality customers and spotting customers likely to churn
Adjust the criteria to match your own policies
Trace every score back to the data behind it
What Customer Scoring is and how it helps your organisation
Credit and sales teams decide every day which customers to approve, whose credit limit to raise, and who is starting to pay late and needs watching. Those decisions often rest on individual experience, purchase and payment history is scattered across ERP, accounting and Excel, and when someone asks why one customer was approved and another declined, the answer is hard to give.
Customer Scoring scores each customer from the data your organisation already has, including purchase history, payment behaviour and other supporting information. The AI gives a score with explainable reasons showing which factors pushed it up or down. Use it for credit approval, identifying quality customers for special care, and spotting customers likely to churn, with criteria and weights adjusted to your own policies.
After go-live, approvals follow one standard across the organisation, the credit team can show auditors the data behind every score, and sales knows which customers to spend time on first. Khaojai IT designs the scoring model around your customer base and policies and connects it to your existing ERP, accounting system and CRM.
Questions buyers ask before starting
How long does implementation take
It depends on how ready your historical data is, typically 2 to 4 months, including a parallel run alongside your current approval method to compare results before going live.
How much data do we need to start
You can start with the purchase and payment history already in your ERP or accounting system. One to two years of history is usually enough, and other data sources can be added later.
Does the AI approve on its own or does a person still review
The system provides the score and reasons as supporting information. Approval stays with your staff, or you can allow automatic approval only within a score range your organisation defines. Every score can be traced to its data.
Is customer data secure and PDPA compliant
The system uses only data your organisation is entitled to use for the stated purposes, with per-user access rights and full usage logs. It can run on your own servers or on cloud infrastructure in Thailand.
AI in this system
AI scores customers with explainable reasons.
- 01Scores each customerCalculates a score from purchase history, payments and usage.
- 02Explains every scoreStates the main factors behind a high or low score in plain language.
- 03Predicts churnSpots customers showing signs of drifting away before they actually leave.
- 04Suggests credit limitsProposes a starting credit limit based on the score and your risk policy.
Works with the systems you already use
LINEMicrosoft 365Google WorkspaceSAPExcelExisting systems through APIs
Questions about Customer Scoring?
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