AI Lead Scoring

Lead scoring that learns — no rules required

Most lead scoring asks you to define the rules. Optifai learns your ideal customer profile from your CRM data, detects buying signals across your market, and scores every account based on real fit and real timing.

Why rule-based scoring breaks

Rule-based lead scoring works until it doesn't. You set up the rules once — company size over 50, industry is SaaS, has a VP title — and the system scores leads accordingly. For the first few months, it feels fine.

Then your market shifts. A new segment starts converting. Your best deals come from a profile your rules never anticipated. But the scores don't change, because the rules don't change — not until someone notices, schedules a meeting, debates the new thresholds, and manually updates the system.

Meanwhile, your reps chase leads with high scores that no longer mean anything, while real opportunities sit unnoticed at the bottom of the list.

The problem with rules is that they encode yesterday's assumptions. Markets move. Rules don't.

How Optifai scores differently

Optifai doesn't ask you to write rules. Instead, it learns what your ideal customer looks like from three sources:

1. Your CRM history

Optifai analyzes your closed-won deals — the firmographics, the deal timeline, the engagement patterns — to build a baseline model of who buys from you and why.

2. Buying signals

The system monitors six categories of real-time signals: funding rounds, hiring surges, website visits, role changes, technology adoption, and geographic expansion. An account that just raised a Series B and is hiring three SDRs is scored differently than one that's been quiet for six months.

3. Prospect responses

Every interaction teaches the system. When a prospect opens an email, clicks a link, books a meeting, or goes silent — each response refines the model. The scoring gets sharper with every conversation your team has.

The result is a score that reflects actual buying likelihood based on fit and timing — not a static checklist that someone wrote six months ago.

Rule-based scoring vs. Optifai

Rule-basedOptifai
SetupDefine rules, assign point values, maintain thresholdsConnect CRM. Learning starts automatically.
Data sourcesCRM fields onlyCRM + buying signals + prospect responses
MaintenanceQuarterly rule reviews, manual recalibrationContinuous — adapts as your market shifts
Cold startNeeds months of historical data to calibrateLearns from your first closed-won deals within days
Signal decayScores stay stale until rules are updatedScores refresh as new signals arrive
OutputA number in your CRMScore + context + recommended next step, written to your CRM

Every deal your team closes, every signal the system detects, every response a prospect gives — the scoring compounds. It doesn't just score leads. It gets better at scoring them.

Frequently asked questions

What signals does Optifai use for scoring?+

Optifai monitors funding rounds, hiring surges, website visits, role changes, technology adoption, and geographic expansion. These real-time signals are combined with your CRM history and prospect responses to produce a score that reflects actual buying likelihood — not static rules.

How long does it take to start learning?+

Optifai begins learning the moment you connect your CRM. Within the first week, the system identifies patterns in your closed-won deals and starts surfacing accounts that match. Scoring accuracy improves continuously as it learns from your team's decisions and prospect responses.

Does it work with HubSpot and Salesforce?+

Yes. Optifai connects to both HubSpot and Salesforce. Scores, context, and recommended next steps are written directly into your CRM as tasks and notes. No CSV exports, no switching tabs.

How much does it cost?+

Optifai starts with a 7-day free trial, no credit card required. Paid plans begin at $150/month (Starter, 3 seats). See the pricing page for Growth and Enterprise options.

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