AI Lead Scoring
Rank leads by likelihood to buy, and say why.
We build lead scoring and nurturing for B2B teams: scores from CRM history, firmographics and engagement, plain-language reasons per lead, routing rules and nurture sequences, validated against past wins and losses before rollout.
- Explainable scores
- Routing rules
- Nurture sequences
Free 30-minute call with a senior specialist. Reply within one business day. Based in Jaipur, working with businesses across India.
- Discovery callFree 30 minutes with a senior specialist
- Scoped first phaseWritten scope, timeline and fixed price
- Build with weekly demosWorking software you can see every week
- Launch and supportGo-live with your team ready, then ongoing support
What is AI lead scoring?
AI lead scoring ranks leads by their likelihood to convert using CRM history, company details and engagement, and explains the main reasons. Stack18 builds it for B2B teams, validates it against past outcomes before use, and connects it to routing and nurturing so sales focuses on the best leads.
Last reviewed 31 October 2026 by the Stack18 delivery team in Jaipur. Security and AI governance · Pricing · About Stack18
| What it covers | Data and scoring; Validation; Routing and alerts; Nurturing; Reporting. |
|---|---|
| Typical first step | Discovery Sprint: 2 weeks; fixed price. |
| Custom build | Fixed-scope first release: agreed in discovery; fixed price after discovery. |
| Long-term option | Transformation Pod: 12–36 months; annual contract. |
| Measured by | Win rate of top-scored leads; Speed to lead; Sales hours on poor-fit leads; Lead-to-opportunity rate. Each against an agreed baseline. |
| Governance | Human approval at 5 governance gates, every AI agent action logged, NDA available on request. |
| Delivery team | Based in Jaipur, India. A senior specialist replies within one business day. |
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AI Lead Scoring, end to end.
Each capability is delivered by the same team on the Agentic SDLC, with your approval at every critical step.
Data and scoring
Scores combine CRM history, company details and engagement, with plain-language reasons for each lead.
- CRM and engagement data
- Fit and intent signals
- Reasons per score
Validation
Scoring is back-tested on past wins and losses, with score bands compared to actual win rates and drift monitored.
- Back-testing on past leads
- Score bands versus win rate
- Bias and drift checks
Routing and alerts
Leads route to owners by score and territory, with hot-lead alerts and response-time targets.
- Owner assignment
- Hot-lead alerts
- SLA timers
Nurturing
Approved email and WhatsApp sequences nurture warm leads and hand over to sales on intent signals.
- Email and WhatsApp sequences
- Trigger-based follow-up
- Handover to sales
Reporting
Score-to-win analysis, source quality and funnel dashboards show which leads and channels pay back.
- Score-to-win analysis
- Source quality
- Funnel dashboards
A typical engagement, step by step.
Senior people lead every phase. Specialised AI agents on the Agentic SDLC handle the repetitive work, and nothing ships without your approval.
Discovery
We map today's process, systems and data for data and scoring; validation; and routing and alerts, talk to the people who run it and agree the baseline for win rate of top-scored leads and speed to lead so progress is measured from week one.
Design
We design the flows, roles, approvals and integrations for data and scoring; and validation, and review a clickable prototype with the people who will use it before anything is built.
Build in weekly demos
We build in weekly demos, starting with data and scoring, then validation and routing and alerts. Each release is tested on your own data and passes a human approval gate before the next begins.
Launch and support
We migrate data, train your team and support go-live. After 30 days we review win rate of top-scored leads, speed to lead and sales hours on poor-fit leads against the baseline and agree what to extend next.
Start small. Scale when it works.
Every engagement begins with a short, fixed-price step so you can judge the fit before committing further. See pricing.
Discovery Sprint
Teams deciding which of data and scoring; validation; and routing and alerts to build first, and what it should cost.
- Duration
- 2 weeks
- Pricing
- Fixed price
- Scoped plan and timeline
- Team and fixed price
- Process map or prototype
Fixed-scope first release
Teams that know the outcome they need from AI lead scoring and want a fixed-scope first release.
- Duration
- Agreed in discovery
- Pricing
- Fixed price after discovery
- Written scope and acceptance criteria
- Weekly demos
- Handover with documentation
Transformation Pod
Organisations running AI lead scoring across several teams, sites or systems over years.
- Duration
- 12–36 months
- Pricing
- Annual contract
- Dedicated cross-functional team
- Quarterly business reviews
- One accountable partner
What we have shipped, and what a typical engagement looks like.
Delivered projects link to the full case study. Illustrative scenarios describe typical engagements and are not named client results.
B2B software seller
- Challenge
- All leads treated alike; hot leads slow to get a response.
- What we do
- Explainable scores and routing alerts validated on past deals.
- We would measure
- win rate of top-scored leads, speed to lead and sales hours on poor-fit leads, against a baseline agreed in week one.
Pilot in weeks
Free lead prioritisation review
Tell us where lead prioritisation hurts most. We map what to fix first, whether ready-made or custom fits, and a realistic first step.
- Where to start and why
- Ready-made vs custom view
- Indicative timeline
We agree targets before we start.
Every engagement has a baseline and a target on the measures that matter to you, reported at every read-out.
AI Lead Scoring questions.
How much data do we need?
Enough closed won and lost leads to learn from. We check your data in discovery and say honestly if rules-based scoring suits you better.
Will reps trust a score?
Each score shows reasons, and reps can give feedback so the model improves.
Which CRMs does it work with?
HubSpot, Salesforce, Zoho and others with APIs. We confirm versions, plans and API limits during discovery, so there are no surprises on integration day.
Does it contact leads automatically?
Only with approved sequences and consent rules you set.
How do we measure success?
By win rate in top score bands, speed to lead and sales time saved versus your baseline. We agree the baseline in week one and report against it at each weekly demo and at a 30-day review.
What should we prepare before the first call?
Bring a short description of how AI lead scoring works today, examples of the documents or screens your team uses, and the three numbers that matter most to you. A senior specialist will use them to outline a first step and a fixed price.
Guides, comparisons and proof.
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Read →Let's scope your AI Lead Scoring project.
Tell us where you are and where you want to be. A senior specialist will reply within one business day with next steps.
- Free 30-minute consultation
- Indicative estimate after the call
- NDA available on request