AI Sales Intelligence
Sell Smarter. Close Faster.
What We Do
Your sales team does not have a leads problem. They have a prioritization problem. Too many contacts, not enough signal about which ones are worth calling today.
AI sales intelligence changes the economics of prospecting. Instead of working the list sequentially, your reps work the list intelligently: calling the leads that behavioral data says are ready to buy, skipping the ones that are still months away, and getting into the right conversation with the right message at the right moment. We build predictive scoring systems trained on your win/loss history, integrated with your CRM, and surfaced as actionable priority signals in the tools your team already uses.
How We Work
We start with your historical CRM data: closed-won deals, closed-lost deals, deal age, contact engagement, and firmographic attributes of the accounts that converted. That data trains the scoring model that identifies which attributes and behaviors predict purchase likelihood. Once the baseline model is built, we connect it to your live CRM and marketing data feeds so scores update in real time as prospects engage with your website, open emails, and attend events.
Scores and recommended next actions are surfaced directly in your CRM as custom fields and activity notifications. Reps see a prioritized view of their pipeline without leaving Salesforce or HubSpot. Model performance is reviewed monthly and retrained quarterly as new outcomes accumulate.
Why Running Start Digital
Pricing
From $10,000
Typical turnaround: 6-12 weeks
Includes
Frequently Asked Questions
The model analyzes your historical win/loss data to identify patterns: which industries close, which behaviors indicate intent, which deal sizes are realistic. New leads are scored against those patterns.
CRM data (deals, contacts, activities), website analytics, and email engagement data. The more historical data available, the more accurate the scoring model becomes.
Lead scores and insights are pushed directly into your CRM as custom fields and activity records. Your reps see scores and recommendations without leaving their existing tools.
Initial models based on historical data are ready in 2 to 4 weeks. Accuracy improves as the model processes more outcomes. Most teams see meaningful prioritization improvement within 60 days.
We augment thin CRM data with third-party firmographic and intent data signals. Thinner datasets produce less precise models initially, but accuracy improves as your team generates more outcomes for the model to learn from.
Standard lead scoring uses manually defined rules. AI scoring identifies patterns in your actual win/loss data that humans cannot see or would not think to encode as rules. It is empirical rather than assumptions-based.
Yes. We build account-level scoring that aggregates signals across all contacts at a target account and predicts account-level purchase likelihood. Works well for enterprise sales teams targeting named accounts.
Ready to get started?
Start with a $5,000 deposit. Balance due on delivery.