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Events and media group · international sales team

An AI assistant that knows each salesperson's plan.

Inside an events group's sales cockpit, an assistant connected to the person's own data: their plan, targets, portfolio, and what they have already signed.

The flow
  1. QuestionThe salesperson types in their plan's panel.
  2. ContextPlan, targets, portfolio and signed deals, injected with every question.
  3. AnswerBased on that data only, with its limits stated.
  4. Adjusted planThe salesperson edits the block and reruns the projection.
What the assistant sees, and what it does not.

The context

The project first aimed at a broad assistant: follow-ups, meeting preparation, voice entry of activity, a shared knowledge base. The CEO refocused the first step on the salespeople's season plan. The assistant followed that refocus: it serves the plan, not the whole activity.

What was built

  • A chat panel inside the cockpit, private to the salesperson, with one thread per season.
  • Context injected with every question: the current plan, targets by brand, the account portfolio and what is already signed. The model is not trained on the client's data; it receives it at the moment it answers.
  • Typical questions: "is this plan realistic given last season?", "which brand am I furthest from?".
  • Stated limits: the assistant reads neither quotes, nor emails, nor meeting notes.
  • The same logic in each plan block's projection: a structured output with a confidence level, a rationale and a point to watch.
Assistant · season planFictional example
Is this plan realistic given last season?
On Brand A, you have already signed 72% of the target: the rest holds with two blocks. On Brand C, your plan aims at 3 times last season's signed amount with half as many meetings: that is the gap to look at.
Which brand am I furthest from?
Brand C: 31% signed. I cannot see your quotes or emails, only your plan and portfolio.
Fictional exchange.

What was hardened in testing

A first version compared the target with the planned amount without counting what was already signed, and announced a gap to someone who had already passed their target. The calculation was fixed before go-live: the assistant always starts from the signed figures coming up from the ERP.

What changed

The salespeople named the AI comments as the most useful part of the tool. Another piece of feedback sets the current limit: as long as the assistant does not know the full customer history and event feedback, its recommendations stay at common-sense level. That is the natural next step: connecting emails and history, with the client's agreement on how that data is processed.

Further reading