Intelligence at every
stage of the sale.
A practical guide to where AI can support a commercial team, and what people need to keep in view.
Discover the right accounts
Combine approved CRM records, public company information and business signals to prioritise research.
Inputs: account criteria, source dates, permission to use data.
Measure: accepted account rate, research minutes, duplicate records.
A useful first pilot: research 50 known accounts and compare the result against a human-reviewed baseline.
Prepare relevant engagement
Create first-draft messages grounded in a real customer context. Keep a person responsible for claims and sending decisions.
Inputs: verified account evidence, messaging policy, suppression lists.
Measure: factual error rate, approval rate, positive replies.
A useful first pilot: compare two approaches using the same account sample, with all messages reviewed.
Keep opportunities moving
Summarise meetings, suggest follow-up actions and identify missing opportunity context. Review before updating important commercial records.
Inputs: permitted meeting notes, opportunity stage definitions, action owners.
Measure: record completeness, missed next steps, review time.
A useful first pilot: generate draft summaries for ten meetings, then review omissions and inaccuracies.
Learn from a controlled pilot
Set a baseline and a fixed scope. Track the combined time for automation, checking, correction and ongoing administration.
Inputs: owner, evaluation sample, incident process, stop criteria.
Measure: net time saved, quality, data access and operating cost.
Expand only when the evidence supports it. Product capabilities and availability vary by provider, geography and plan.