Score every visitor. Route the right ones
Account, lead, and opportunity prioritization on the same context layer, with deanonymization, propensity tiers, and the Ask Reli natural-language filter built in.
Which accounts do we prioritize? Sorted by propensity
| Account | Segment | Score | Stage | Owner |
|---|---|---|---|---|
| Cursor | Enterprise | 94 | Awareness | K. Liu |
| OpenAI | Mid-market | 91 | Consideration | M. Patel |
| Anthropic | SMB | 89 | Intent | K. Liu |
| Lovable | Enterprise | 86 | Decision | R. Chen |
| ElevenLabs | Mid-market | 84 | Purchase | M. Patel |
Every account in your TAM scored on propensity to buy, then bucketed High Fit, Medium Fit, and Low Fit. Each tier carries its count, projected pipeline value, and average projected-to-pipeline rate, plus a Digital Paid Touched split. High Fit gets the AE's calendar. Low Fit gets nurture.
- Propensity scoring on ICP + intent + engagement
- High Fit / Medium Fit / Low Fit tiers with projected pipeline
- Digital Paid Touched vs Non-Touched split per stage
- Scores write back to Salesforce and HubSpot
- Round-robin or rule-based rep ownership
Which leads do we prioritize? The right 30
| Lead | Company | Signal | Score |
|---|---|---|---|
| Anika Shah | Truevo | 3 pricing visits | 91 |
| Marcus Holt | Pomelo | Demo + 2 doc views | 88 |
| Priya Iyer | Vyne | Webinar + pricing | 86 |
| Jay Mehta | Cipher Pay | Comparison page | 84 |
| Lena Park | Stak.io | Whitepaper + 2 visits | 82 |
The tabs automap to your funnel stages, from pre-form-fill anonymous visitors through SAL, so the view always mirrors the funnel you actually run. The in-data search bar reads Ask Reli to filter on any column, so an SDR types a plain-English query and the list filters itself. Every row carries a journey timeline sparkline that expands to the full path.
- Tabs automap to your funnel stages, visitors through SAL
- Ask Reli to filter on any column, in plain English
- Journey timeline sparkline per lead, expandable
- Reasoning per lead surfaced inline
- One-click sequence assignment
Open opps, sorted by who slips first
| Opp | Stage | Amount | Prob. | Risk |
|---|---|---|---|---|
| ElevenLabs · Q2 exp. | Negot. | $240K | 82% | Champion AWOL |
| OpenAI · net-new | Eval | $148K | 68% | No exec mtg |
| Cursor · exp. | Proposal | $120K | 71% | Stage stale |
| Lovable · net-new | Commit | $84K | 88% | — |
| Anthropic · net-new | Eval | $96K | 59% | Procurement |
Every open opportunity ranked by projected close probability, with risk flags surfaced for stalls, missing meetings, or commit-stage gaps. This is the surface the Key Deals and Early-Stage Deals at Risk agents read from.
- Probability + risk flag together
- Risk signal library (10+ patterns)
- Forecast contribution per deal
- Slack ping when a risk flag appears
Anonymous traffic becomes a working list
412,000 visitors a quarter resolve into 38,000 known accounts with contacts. The SDR works the buyers who arrived this morning.
- Deterministic identity resolution
- Account-level visitor view
- Buying-committee contact enrichment
- First-party pixel with consent honored
Type the query. The list filters itself
| Company | Stage | State | Visits (7d) |
|---|---|---|---|
| Truevo | Series B | CA | 4 |
| Pomelo | Series B | CA | 3 |
| Vyne | Series B | CA | 2 |
| Cipher Pay | Series B | CA | 2 |
Ask Reli to filter on any column is the in-data natural-language filter that lives on every prioritization view. Type 'show leads in EMEA who visited pricing in the last 30 days' and the list filters itself. This is Reli embedded in the data, distinct from the help bot in the top bar.
- Plain-English filter against any column
- Structured-filter interpretation visible
- Save today's query as tomorrow's view
- Lives on every list, every tab
Where they are in their journey
| Account | Stage | Top signal |
|---|---|---|
| Cursor | Consideration | Comparison page · 4 visits |
| OpenAI | Awareness | Webinar attended |
| Anthropic | Decision | Demo + 3 doc views |
| ElevenLabs | Intent | Pricing visit by exec |
Engagement patterns tell you where an account actually is in its buying process. RevSure infers Awareness, Consideration, Intent, and Decision from behavior across the journey.
- Four stages: Awareness / Consideration / Intent / Decision
- Inferred from 100+ behavioral signals
- Stage-aware messaging recommendations
- Transition pings when stage moves
The team that ships this outcome
Each agent below reads this application's context, decides the next move, and ships it back into your live tools · proposed, approved, reversible.
RevSure turned 31,000 anonymous companies into a working list, sorted by who was actually buying. Our SDRs went from a 4% reply rate on a static list to 14% on the prioritized one.
Elizabeth Villarreal
Demand Gen Lead · Abnormal AI
The other applications
Marketing ROI
Demand Gen Effectiveness, MMX, Incrementality, Spend Reallocation, Board Dashboard.
ExploreFunnels & Journeys
Snapshot Funnel, Journey Sankey, Cohort Intelligence, leakage detection.
ExplorePipeline Predictability
Eight-quarter projections, daily health score, forecast confidence.
ExploreAgents
Agents that act on the context · builder, MCP, Safe Autonomy.
ExploreSpend the hours on the accounts worth the call
Implementation included. First prioritized list in week one.