AI
Most sales teams lose deals not because they lack leads, but because they can't tell which ones are worth chasing.
Schedule a Technical Scoping Call
AI
Most sales teams lose deals not because they lack leads, but because they can't tell which ones are worth chasing.
Schedule a Technical Scoping Call
Traditional lead scoring relies on static point systems built around gut instinct: job title gets 10 points, form fill gets 5, whitepaper download gets 3. The problem? These rules treat all CFOs at Series B companies the same - regardless of intent signals, buying stage, or actual fit.
The result is a sales team spending 70% of their time on contacts who will never convert, while genuinely high-intent leads sit unworked in the CRM. Reps burn out chasing the wrong names. Pipeline forecasts drift. And marketing keeps funding campaigns that generate volume, not revenue.
We engineer custom, automated scoring systems that sit directly inside your CRM and score every contact in real time - without manual tagging or static rules.
Behavioral, firmographic, and intent data pulled from every source in your stack.
ML models identify patterns across conversion history and engagement signals.
Dynamic, weighted scores assigned continuously - not just at the point of form fill.
This requires robust AI Integration to connect scoring logic across your CRM, marketing automation, and intent platforms - often augmented with Agentic AI to autonomously enrich lead records before a rep opens the contact. Explore our AI Services.
A custom model is trained to score leads across the full signal spectrum:
Page visits, session depth, return frequency, pricing page engagement.
Company size, industry, revenue range, tech stack alignment.
Third-party buying signals from Bombora, G2, or 6sense layers.
Email open patterns, webinar attendance, demo requests.
Score trial sign-ups, free users, and inbound leads against ICP fit in real time.
Prioritize ABM target accounts showing active buying-committee signals.
Qualify high-value advisory leads before SDR assignment.
Score inbound client leads by placement potential and contract value.
To build an accurate scoring layer, we require:
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12+ months of CRM records with closed/won and closed/lost outcomes labeled.
All data is encrypted at rest and in transit. Your model is siloed - your pipeline data is never used to train scoring for other clients.
API access to your CRM (HubSpot, Salesforce, or equivalent) and marketing automation platform.
Off-the-shelf SaaS tools force your data into generic models with escalating per-transaction pricing. BNXT.ai offers
You own the model
and IP.
Trained exclusively on your transaction data, not global averages.
Sits natively inside your existing CRM and LOS - no clunky third-party dashboards.
The model ingests hundreds of signals - behavioral, firmographic, and intent - and weights them against your own historical conversion data. Every lead gets a real-time score that updates as new activity is recorded, not just when a form is submitted.
Point-based systems assign fixed weights based on assumptions. AI models find the actual statistical relationships in your data - including non-obvious combinations of signals that your team would never manually identify.
A custom scoring model typically takes 6 to 10 weeks from data ingestion to live CRM integration, depending on data quality, CRM complexity, and the number of scoring segments required.
Yes. By suppressing low-fit and low-intent contacts from active rep queues, the model ensures your sales team spends time on leads that have a statistically meaningful chance of converting - based on your actual data, not assumptions.
Yes. We engineer API middleware that connects the scoring engine natively to Salesforce, HubSpot, Pipedrive, and most enterprise CRMs - without replacing your existing workflows or requiring reps to change tools.
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