Sales and pricing
Lead & Opportunity Scoring
Which leads and opportunities deserve attention now. Scores and reasons route work inside the CRM, and a routing experiment measures what the scoring adds.
The problem
Leads are worked first in, first out, or by feel, so capacity goes to whatever arrived last. History only shows outcomes for the leads someone chose to work, so a model trained on it naively learns what the team already prefers.
Who owns it
Revenue operations, who own the routing rules and the weekly funnel review. Sales development and account executives work the queues, and marketing owns nurture.
What it learns from
- CRM leads, opportunities, and field history
- Marketing automation engagement
- Product usage signals, for product-led motions
- Firmographic enrichment, within its permissions
How it works
Predict, decide, act, measure
The same four steps in every solution, in this order, each one visible to the team that owns it.
- 01
Predicts who will convert
Each lead and open opportunity is scored on the CRM as it looked at the time, never on fields edited after the outcome, with the top reasons on every score. Duplicate leads and contacts are resolved to the right account.
- 02
Decides routing through a policy
Score bands, territory, and rep capacity set routing, response-time tiers, and nurture assignment. Caps keep new segments from being starved, a small share of low-scored leads is always worked so the system keeps learning, and no lead is rejected on score alone.
- 03
Acts in the CRM queues
Scores, reasons, and queue position land in the CRM. Hot leads route to senior reps within their response window, and low bands enroll in nurture through marketing automation and sales engagement tools.
- 04
Measures against status-quo routing
A randomized routing experiment compares score-ordered queues with status-quo queues at matched capacity. The always-worked slice is the standing guard against the model confirming its own choices.
What it moves
The business levers
Conversion per rep-hour
The same team converts more of the pipeline it works.
Win-rate mix
Effort shifts toward the opportunities that close, and at-risk deals reach managers earlier.
Rep capacity
Sales development time is concentrated where it converts instead of spread evenly.
Speed to lead
The leads most likely to convert reach a person while they are still warm.
Proof
How the return is proven
The return is the incremental conversion value of score-ordered routing over the status-quo arm, stated against the return model agreed up front. Response-time adherence, coverage of new segments, and cherry-picking are reported beside it.
What you see: the ROI readout
Every solution produces the same readout, assembled from the system's own records rather than built by hand.
Correctness
The checks the pipeline passed on your own data: leakage, point-in-time, and entity resolution.
Incrementality
The incremental effect against the holdout or equivalent design, with its confidence interval.
Return
The measured return against the investment, set beside the return model agreed before work started.
Guardrails
Complaints, cost, margin, fairness, and contact limits, each shown against its bounds.
Audit extract
Every score, action, and outcome, with the model and policy versions behind it.
Governance
What is governed
Access, approvals, and the audit trail are part of the solution, not a review step added at the end.
Identity-scoped access
Queue views are scoped by identity through your single sign-on.
Approval gates
Changes to score bands, routing rules, and response tiers need revenue operations approval.
Audit trail
Every routing decision and its outcome is logged, which also answers disputes about who worked what.
Fairness and permissions
Firmographic features are screened for proxy bias, and enrichment data is used only within the permissions it came with.
Why it holds up
Trained on your data, framed by the outcome
This solution trains models on your own data, checks every stage from data to decision, and is measured against the outcome it was built for. Because its predictive power is measured, it also shows the drivers behind the metric, so your team can fix causes as well as act on scores.
Why solutions hold upStart with one decision
Bring the problem and the systems your team works in. We scope the first solution with you, agree how its return will be measured, and run it in production with your people.