AI Lead Scoring & Routing
A lead scoring and routing agent evaluates every inbound lead on fit and intent, then sends it to the right person immediately based on territory, product line or deal size. The effect is that your strongest leads reach your strongest closer within minutes instead of tomorrow.
Who it's for
Teams with more than a couple of salespeople.
What changes
Your best leads reach your best closer within a minute.
- Starting at
- ₹75,000
- Timeline
- 3–5 weeks
- Category
- AI Sales Agents
- Built from
- Vashi, Navi Mumbai
Key takeaways
- Fit and intent are separate axes and collapsing them into one score loses the useful information.
- Routing speed matters more than routing accuracy for most teams.
- Scores must be explainable — an unexplained number gets ignored by salespeople.
- Builds in 3–4 weeks from ₹75,000; needs at least a few hundred historic leads to calibrate.
- Pointless below roughly three salespeople — there is nothing to route.
Two axes, not one
Most scoring models produce a single number, which throws away the distinction that actually drives what you should do.
Fit is whether this company is the kind you serve well: size, industry, geography, systems they run. It is stable and knowable from data. Intent is whether they are trying to buy right now: pages visited, form completed, pricing page viewed, urgency language in the enquiry. It is volatile and behavioural.
A high-fit, low-intent lead needs nurture. A low-fit, high-intent lead needs a fast honest conversation about whether you can help. Collapsing both into "score: 62" tells your salesperson nothing about which situation they are in.
The quadrant that drives the routing
| High intent | Low intent | |
|---|---|---|
| High fit | Route now, best closer, call within minutes | Nurture with real content; check back monthly |
| Low fit | Fast honest call — refer out if you cannot help | Automated reply, no human time |
The bottom-right quadrant is where most sales time is wasted, and the top-right is where most revenue is lost through slow response. Getting only those two right pays for the system.
Routing speed beats routing precision
Teams tend to over-engineer the scoring and under-engineer the handoff. In practice, a rough score that routes in ninety seconds outperforms a sophisticated one that routes at 10am the next morning.
The routing rules also need a fallback that actually fires. If the assigned rep does not act within your SLA, it reassigns rather than sitting in a queue with their name on it — which is where good leads quietly die in most CRMs.
Calibrating against outcomes, not opinions
The initial model comes from your closed-won and closed-lost history, not from a workshop. We need a few hundred historic leads with outcomes attached; below that the model is guessing and we will say so.
The interesting part is what the data disagrees with. Businesses routinely believe company size predicts success and find that the real predictor is whether the enquiry mentioned a specific deadline. Those discoveries change more than the routing — they change marketing.
Scores are recalibrated quarterly against actual outcomes, because a model fitted once and never revisited drifts as your market and offer change.
What routing rules usually include
- Territory — by state, city or pin code, with a defined owner for anything unmatched.
- Product or service line, where different people sell different things.
- Deal size band, so large opportunities reach senior people directly.
- Language, so the caller gets someone who speaks theirs.
- Existing relationship — if this company is already an account, it goes to the account owner, not into new business.
- Load balancing among equally suitable reps, with an SLA-based reassignment if nobody acts.
What the routing layer ends up doing
Separate fit and intent scoring calibrated on your own history, explainable factors on every lead, routing rules you can edit, SLA timers with automatic reassignment, CRM integration, notifications on the channel your reps actually watch, and a monthly report on score-to-conversion accuracy.
FAQ
Lead Scoring & Routing Agent — your questions
How much historic data do you need?
A few hundred leads with known outcomes is a workable minimum. Below that we start with rules you define from experience and switch to a calibrated model once enough outcomes accumulate. We would rather do that than fit a model to fifty rows and present it as science.
Can we override the score?
Always, and the overrides are valuable data. When a rep consistently overrides on a particular signal, either the model is missing something or the rep is. Reviewing those disagreements monthly is usually the fastest way to improve both.
What about leads that fit nothing?
They route to a defined catch-all owner rather than disappearing. Unrouted leads sitting in a queue nobody owns is the single most common failure in routing systems and it is entirely avoidable.
Does this work with our existing forms and portals?
Yes — anything that can fire a webhook or write to your CRM. Website forms, Meta and Google lead ads, IndiaMART, JustDial, property portals and phone enquiries logged by a voice agent all feed the same scoring layer.
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Next step
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