Abandons the one-sequence-fits-all nurture model. Instead, adapts every lead's content journey in real time based on their engagement signals, intent data, and CRM history — delivering the right content at the right moment, and handing off to sales at the precise point of readiness.
3×
MQL-to-SQL conversion
vs static sequences
45%
faster sales readiness
engagement-driven pacing
Individual
journey per lead
not segment averages
Zero
premature handoffs
intent-gated handoff
Typical build: 3-week sprint · Fixed price · Production-grade
Journey model
Individual
MQL-to-SQL
3× lift
Handoff
Intent-gated
This is the actual Agentforce configuration Kovil AI builds and deploys — not a diagram. Here is what runs inside every node.
Every new lead entering the nurture pool receives an immediate profile assembly: ICP fit score from Einstein Lead Scoring (title, company size, industry against your ideal customer profile), initial intent signals from Data Cloud (which pages visited, which content downloaded, how long spent on pricing page), CRM history (if an existing contact, their previous engagement and any prior sales conversations), and source quality (leads from specific sources have different readiness patterns configured during implementation). This baseline profile determines the lead's starting position in the nurture sequence — high-fit, high-intent leads skip early educational content and start at consideration-stage content.
At each nurture step, Atlas Reasoning Engine evaluates the lead's current signal state — what they've engaged with, what they've ignored, what their intent trajectory is — and selects the most appropriate next content piece from your content library. Content selection considers: the lead's funnel stage (awareness, consideration, decision), their specific pain point signals (which problem-focused content they engaged with), their vertical (industry-specific case studies and data), and the gap since last engagement (cooling-off periods trigger re-engagement content before continuing the sequence). The agent never sends the next piece in a static sequence — it selects based on where the lead actually is.
Prompt Builder generates personalised email copy for each nurture touchpoint — not variable substitution in a template, but contextually relevant messaging grounded in the lead's engagement history. The email references the specific content they've engaged with, speaks to the pain point signals they've shown, and includes a CTA calibrated to their funnel stage (educational content for awareness leads, demo invitation for decision-stage leads). Subject lines are generated with send-time optimisation baked in. The Einstein Trust Layer ensures lead PII stays within Salesforce during generation.
After each nurture send, the agent processes the engagement response: Did they open? Click? Which link? Download the content? Visit additional pages after clicking? Each response event updates the lead's intent score and triggers a journey decision — accelerate (high engagement: move faster toward decision content), continue (normal engagement: proceed at standard pace), pause (no engagement: wait before sending again), or divert (unsubscribe signal: remove from sequence and flag for ops review). Journey decisions are made at the individual level — not batch decisions applied to segments — so every lead's pace is determined by their own behaviour.
The handoff gate is the most important guardrail in the nurture system. A lead is handed to sales only when a configured combination of signals is met: intent score above threshold, engagement with decision-stage content (pricing page, case study, demo content), recency (activity within the last X days), and fit score meeting the minimum ICP threshold. Premature handoffs — the primary complaint from sales teams about marketing-qualified leads — are eliminated because the gate requires evidence of intent, not just time-in-nurture. When the gate opens, the agent creates a Salesforce Lead record with full engagement history attached, alerts the assigned rep via Chatter, and converts the Marketing Cloud contact to a Sales Cloud lead.
Leads that have not engaged in a configured window (typically 21–30 days) are diverted from the primary nurture sequence into a re-engagement flow — a shorter, higher-frequency sequence designed to reactivate interest. Re-engagement content is differentiated from the primary sequence: it typically includes a direct value proposition (free audit, comparison guide, live demo invitation) rather than educational content. Leads that re-engage from this flow re-enter the primary sequence at the appropriate stage. Leads that do not re-engage after the full re-engagement sequence are moved to a long-term low-frequency drip or archived, preventing deliverability degradation from cold contacts.
Content selection
Selects the next content piece for each lead at every nurture step — based on their current funnel stage, engagement history, pain point signals, and vertical.
ICP + intent
Scores every lead on ICP fit and intent level — determining their starting position in the nurture sequence and gating the sales handoff.
Email personalisation
Generates personalised email copy grounded in each lead's engagement history — not variable substitution but contextually relevant messaging per send.
Intent signal feed
Feeds real-time web engagement, content download, and intent signals into the lead profile — enabling individual-level journey adaptation.
Journey execution
The platform where personalised nurture sequences are executed, engagement is tracked, and contacts are managed across the full funnel.
Handoff automation
Automates the sales handoff — creating the Lead record in Sales Cloud, attaching engagement history, and alerting the assigned rep via Chatter.
Data security
Keeps all lead PII within Salesforce during AI processing. No contact data leaves the platform during personalisation generation.
Kovil AI scopes, builds, tests and deploys this Agentforce configuration end-to-end. You do not touch Agent Builder until it is live and nurturing leads.
Journey Builder runs a fixed sequence — every contact goes through the same steps in the same order, with branches only at pre-defined decision points. The Lead Nurture Agent adapts the journey for each individual based on their real-time behaviour. It selects which content to send next based on what the lead engaged with last. It accelerates leads who are showing high intent. It pauses leads who are going cold. It personalises the email copy for each send. Journey Builder is a fixed script. The agent is a responsive system.
The gate requires a configured combination of signals: intent score above your threshold (based on Einstein Lead Scoring), engagement with at least one decision-stage content piece (pricing page, demo request, case study), activity within the last X days (recency signal), and ICP fit meeting minimum threshold. When all conditions are met simultaneously, the handoff triggers automatically. You set the thresholds during implementation. Most clients find that reducing premature handoffs significantly improves their sales team's trust in marketing-qualified leads.
Yes. The content selection logic and personalisation templates are configured per vertical and product line. A lead interested in Product A in the financial services vertical receives different content than a lead interested in Product B in healthcare. The agent identifies the relevant track from the lead's engagement signals and firmographic data, and runs the appropriate content selection logic for that track.
Leads that complete the full nurture sequence without reaching the readiness gate are moved to a long-term low-frequency drip — typically 1 touchpoint per month with relevant thought leadership content. This keeps them warm without driving deliverability cost. Leads that show no engagement over an extended period are moved to archived status and excluded from all sends. This is better for deliverability than keeping cold contacts in active sequences.
Book a 30-minute discovery call. We'll audit your current nurture sequences, identify where leads are dropping off prematurely, and scope a 3-week Agentforce implementation that adapts to every lead individually.
3-week sprint · Fixed-price · Production-grade · Post-launch support included