Sales & lead management
The right offer at the right time: lead scoring, campaign and price recommendations.
Sales & lead management is an Aginies solution package for the Retail & E-commerce sector in the “customer interaction & experience” area. What the agents do: Lead AI combines web, form and CRM signals; each lead is prioritised with an intent and fit score; the campaign agent produces personalised offers and gift suggestions from segment and past behaviour. Expected outcomes: sales focuses on the leads most likely to convert; personalised campaigns lift conversion and basket size; contact before the lead cools: every scored lead is called the same day. The package uses the Lead scoring, Recommendation engine, CRM tools (MCP), Multi-source RAG capabilities of the Aginies platform and can be watched live through the Sales lead qualification, Plan upgrade advisor, Review response and quality escalation, Product Q&A assistant scenarios in the agent library.
Leads pile up in the CRM, yet sales cannot tell which are warm; campaigns go to everyone alike. Price and gift suggestions rely on gut feel, and opportunities go cold.
- 01Lead AI combines web, form and CRM signals; each lead is prioritised with an intent and fit score.
- 02The campaign agent produces personalised offers and gift suggestions from segment and past behaviour.
- 03The price-analysis agent reads competitor and stock data and proposes prices within margin rules.
- 04Warm leads are handed to a rep with a conversation summary; offers above the discount threshold go to approval.
- Scoring and enrichment of leads from web, e-mail and WhatsApp
- CRM record, representative assignment and first-contact draft
- Offer and plan suggestion from the product knowledge base
- Follow-up reminders and lost-opportunity analysis
- API access to the CRM (Salesforce, HubSpot, Dynamics)
- Scoring criteria and territory/representative assignment rules
- Current product, price and campaign information
Derived from the linked scenarios: the supervisors, specialist agents, models and systems that run this package.
Summed from the simulation definitions of the linked scenarios; recalculated for your scale in the discovery session.
- Sales focuses on the leads most likely to convert
- Personalised campaigns lift conversion and basket size
- Contact before the lead cools: every scored lead is called the same day
| Time to first contact | From hours to minutes |
| Qualified-lead conversion | +10–20 points |
| CRM data completeness | 95% and above |
Target ranges from comparable deployments; baseline and target are fixed together in the first week of the pilot.
Scenario-level approval rules plus the package’s general controls.
- Sales lead qualificationEnterprise (> 1,000 employees) or suspected competitor → SDR lead acceptance
- Plan upgrade advisorCommitment-based or discounted bespoke offer → campaign manager approval
- Review response and quality escalation1-star review replies and defect escalations → community manager approval
- packagePrice and discount offers follow the authority matrix; out-of-band offers to a person
- packageNo marketing contact without consent; the consent record checked on every contact
- 1 · Discovery and design · 2–3 weeksThe 20 most frequent intents and transactions are chosen, identity and approval thresholds written with information security, channel and system integrations listed.
- 2 · Pilot · 4–6 weeksOne channel, a limited customer group; the test corpus runs, a human representative shadows, thresholds tuned on real traffic.
- 3 · Scale-outRemaining channels and transactions added; dashboards, SIEM forwarding and kill-switch handed over; monthly model and rule review begins.
This package’s scenarios in the agent library
Sales lead qualification
Inbound leads enriched, scored and in the CRM within seconds; the SDR starts the call with a context brief.
Plan upgrade advisor
Usage analysed, the right plan offered with a comparison; on acceptance the change provisions instantly.
Review response and quality escalation
Reviews classified and answered in brand tone; recurring defects joined with return data and escalated to QA.
Product Q&A assistant
Size, compatibility and spec questions answered from catalogue and return data; stock and price verified.
Time to move from experimenting with AI to transforming with it.
In a 30-minute discovery session we take your 2–3 priority business problems, show a live demo of a similar scenario, and draft a roadmap that starts with the Value layer.
- Your 2–3 priority problems
- Live demo of a similar scenario
- Roadmap starting with value analysis