Sales teams often have more possible actions than they can realistically complete. They may need to follow up with warm leads, re-engage inactive accounts, progress open opportunities, prepare renewal conversations, respond to buying signals, or escalate at-risk deals. Without clear prioritisation, valuable actions can be delayed or missed.
This project focused on creating a next-best-action system for sales operations. The system analysed CRM records, pipeline stage, engagement history, account attributes, customer signals, and recent activity to recommend the most useful next step for each account or opportunity.
The recommendation framework included actions such as follow up now, send relevant content, schedule a check-in, escalate to a senior seller, update missing CRM data, re-engage a dormant lead, prepare a proposal, review an at-risk opportunity, or move an account into nurture. Each recommendation included reasoning so sales users could understand why the action was being suggested.
A combination of rules, scoring, and AI-generated context was used to make the recommendations practical. Sales operations teams could monitor which actions were recommended, accepted, completed, or ignored. This created a feedback loop for improving the system over time.
The result was a more focused sales workflow. Instead of relying entirely on manual judgement or generic task lists, sales teams received prioritised guidance based on current account and pipeline context. This helped improve consistency, speed, and commercial follow-through.