Sales & Wholesale
Trade account churn risk prediction
Predict which trade accounts are at risk of lapsing in the next two quarters using order frequency, category breadth, payment behaviour, service failures, and engagement signals.
10–20%
reduction in trade account attrition
Opportunity assessment
Moderate impact. Meaningful cost or revenue improvement, likely noticeable at function level but modest relative to total business scale.
Moderate effort. Requires configuration, prompt engineering, and testing. A capable team can get there but expect several months.
Demanding data requirements. Relies on clean, integrated data across multiple systems. Significant data preparation work typically needed.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
A churn score without a defined intervention is a report. Decide before you build what the account manager will actually do differently for a high-risk account, and resource it.
Service failure history is usually the strongest single predictor and the one most often left out because it lives in a different system from sales data.
Beware self-fulfilling attention. If high-risk accounts get more contact and they retain, you cannot tell whether the model was right — hold out a control group for the first two cycles.
Experiment starter: Train on three years of account history and score the current base. Hold back 20% of high-risk accounts as an untouched control and run the retention play on the rest. The difference in lapse rate after two quarters is your answer.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — RAG and Knowledge Systems: Unlocking Proprietary DataThis is an decision support opportunity — see the relevant playbook section for how to approach it.More in Sales & Wholesale
Wholesale account performance briefing
Generate a pre-meeting briefing for each trade account: sell-through by line, order pattern versus last year, open orders, credit position, and the three things worth raising in the meeting.
Trade order pattern anomaly detection
Monitor trade customer ordering behaviour and flag material deviations — a dropped category, a halved reorder, a shift to a competitor's specification — early enough for the account manager to intervene.
RFP and tender response drafting
Draft responses to tender and RFP questions by retrieving from a library of previously approved answers, accreditations, and policy documents, then tailoring the wording to the specific question asked.
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