Automatically rank every lead by close probability — so reps always work the hottest opportunities first.
The fundamental problem with most Indian sales teams is that they treat all leads equally — they work them in the order they arrived rather than the order they're likely to close. In a world where a rep has 80 leads in their queue and can meaningfully call 25 in a day, the 55 they don't call that day matter enormously. If the 55 skipped leads include 12 that were about to make a decision, those deals are lost. AI lead scoring solves this prioritisation problem by ranking every lead based on 40+ signals — so the rep's 25 calls are always the 25 most valuable ones.
The 'next best action' suggestion makes the scoring actionable rather than just informational. A score of 87 is useful, but 'This lead just visited your pricing page for the third time and their company matches your ICP — call now' is actionable. The AI doesn't just tell you who to prioritise; it tells you what to do and why, reducing the rep's cognitive load and increasing the chance that the right action happens at the right time.
40+ Signal Analysis
Company size, industry, engagement history, website behaviour, lead source, deal stage velocity, and custom field signals — combined into a 0–100 score.
Next Best Action Suggestions
For each top-scored lead, the AI suggests the next action: 'Schedule a demo', 'Send the pricing deck', 'Call now — they just visited the pricing page'.
Score Decay
Scores decrease automatically when a contact goes quiet — preventing stale leads from occupying the top of the queue indefinitely.
Product-Fit Analysis
High / Medium / Low product-fit scoring based on industry, company size, and use-case match — separate from engagement score.
Objection Prep
For each high-scored lead, the AI generates likely objections and suggested responses based on the contact's industry profile.
Insurance aggregator prioritising leads by intent signals
A Bangalore-based insurance aggregator was calling leads in arrival order — a 100% random approach to a 500-lead daily queue. After enabling AI scoring, reps called score-ranked leads first. Leads scoring above 70 converted at 18% vs the team average of 6%. By spending 70% of call time on the top 30% of the queue, overall conversions per rep improved 40% with zero change in call volume.
Real estate developer identifying site-visit-ready buyers
A Pune developer used AI scoring to surface leads that had engaged with multiple WhatsApp brochures, revisited the project microsite 3+ times, and matched the buyer profile for a specific configuration. These leads were called with a targeted site-visit offer — at a 31% conversion rate to site visit vs 8% for the cold list.
AI Lead Scoring tells you how valuable a lead is. Smart Lead Routing decides who should receive it. Use scoring to prioritise; use routing to assign.