Commerce · Recommendation
Offer Recommendation Agent
Proposes offers with margin context, pending manager approval.
Offers are built inconsistently, without margin context at the moment of decision.
- Function
- Sales
- Industry
- Automotive
- Capability
- Recommendation
Business problem
Sales teams assemble offers from spreadsheets, price guides and memory. Margin, inventory position and customer history are rarely in front of the person making the offer.
What the agent does
Input → Intelligence → Decision → Action
- 01 · Input
Lead context, pricing recommendation and margin targets
- 02 · Intelligence
Offer construction against margin and policy
- 03 · Decision
Proposed offer with margin context
- 04 · Action
Submit for manager approval, then send
Agent workflow
How the Offer Recommendation Agent runs.
01
Signal
A qualified opportunity is ready for an offer.
02
Context
Pricing, margin targets and customer history are gathered.
03
Reasoning
The agent builds an offer within approved bounds.
04
Recommendation
The proposed offer is presented with its margin impact.
05
Manager approval
A manager approves before anything reaches the customer.
06
Action
The approved offer is sent and tracked.
Capabilities
- 01
Margin-aware offers
Every proposal shows its effect on margin.
- 02
Policy bounds
Offers stay within approved discount and pricing rules.
- 03
Approval queue
Managers review and approve proposals in one place.
- 04
Offer history
Keeps a record of what was proposed, approved and accepted.
Human oversight
Offers are pending manager approval by design — the agent proposes, people decide.
- Bounded automation
- Approved guardrails
- Human oversight
- Escalation when judgment is required
Business impact
- More consistent offers
- Margin visibility at the point of decision
- Reduced manual coordination
- Faster approval cycles
Related
Related agents, solutions and industries.
Solutions
Industries
Case studies
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