Sales intelligence glossary.

A 0–100 score representing the real probability that an opportunity will close, derived from behavioural and engagement signals rather than rep-entered stage or close date. The score is explainable: every point can be traced back to a measurable signal in the CRM.

How Predara measures itPredara scores every open deal across seven signals — recent activity volume, multi-threading depth, engagement recency, stage-velocity vs. historical baseline, deal-age outliers, value-vs-ICP fit, and last-touch decay. Deals fall into four bands: Healthy (75–100), Monitor (50–74), At-Risk (25–49) and Critical (0–24).

The directional change in a deal's engagement and activity over the last 14–30 days. Positive momentum (rising activity, multi-threading expanding, response times shrinking) is one of the strongest predictors of close. Negative momentum is one of the strongest predictors of slip.

How Predara measures itPredara fires Momentum Alerts when a deal's activity decays below its trailing baseline — even if the rep hasn't changed the stage or close date. This is how slipping deals are caught weeks early.

The practice of building active relationships with three or more buying-committee contacts inside a target account. Single-threaded deals (one champion only) are 3–4× more likely to slip when that contact leaves, goes silent, or loses internal political capital.

How Predara measures itPredara measures multi-threading depth on every open deal — counting active contacts engaged in the last 21 days — and downgrades the AI Health Score of any deal that depends on a single point of contact above £50k value.

The internal contact at a target account who actively advocates for your solution to the wider buying committee. Losing a champion mid-cycle is one of the strongest leading indicators of a deal slipping or dying outright.

How Predara measures itPredara tracks champion engagement decay — message recency, internal forwarding patterns, meeting cadence — and fires a Champion Drop-Off alert when the signal weakens, prompting an exec sponsor or multi-threading play.

The speed at which revenue moves through your sales pipeline. Calculated as: (Number of qualified opportunities × Average deal value × Win rate) ÷ Average sales cycle length. Higher velocity means faster, more efficient revenue generation from the same pipeline.

How Predara measures itPredara recalculates velocity per stage, per rep and per cohort in near-real-time, and flags Momentum Alerts when an individual deal's velocity drops below its expected curve — usually weeks before the rep notices.

The ratio of qualified open pipeline to remaining quota. A common heuristic is 3× — meaning you need three pounds of pipeline for every pound of remaining quota — but the right multiple depends on your win rate and average sales cycle.

How Predara measures itPredara reports coverage by quarter and by rep, but adjusts for AI Deal Health: a 3× pipeline made up of mostly Critical deals is shown as effectively under-covered, prompting earlier prospecting decisions.

The percentage of qualified opportunities that result in a closed-won deal over a given period. Calculated as: closed-won deals ÷ (closed-won + closed-lost) × 100. Win rate is the single biggest lever in sales velocity.

How Predara measures itPredara tracks win rate per rep, per stage, per ICP segment and per lead source — and runs a Win/Loss Pattern Analysis to surface which traits correlate most strongly with wins (and losses) in your specific data.

The average number of days between deal creation (or first qualified meeting) and closed-won. A shorter sales cycle increases velocity, reduces cost-per-acquisition and shrinks the window in which deals can stall or be displaced by competitors.

How Predara measures itPredara tracks sales cycle length by stage and by ICP segment, and benchmarks every active deal against the cohort average — flagging deals that have been in their current stage 1.5× longer than peers as stage-stalled.

The discipline of keeping the pipeline free from dead deals, stalled opportunities, mis-staged records and outdated close dates. Poor pipeline hygiene is the #1 cause of inflated forecasts and broken trust between sales and the board.

How Predara measures itPredara automatically surfaces stalled deals, mis-staged records (e.g. 'Negotiation' with no activity in 45 days), and close-date drift — so leaders can clean the pipeline in minutes per week instead of hours per quarter.

A defensible measure of how likely your forecast is to land. Strong forecast confidence is built from weighted, behaviour-scored deals — not rep commit — and is presented as three scenarios: Worst case, Likely, Best case.

How Predara measures itPredara aggregates each deal's AI Health Score into Best / Likely / Worst case scenarios, with the Likely number anchored to the historical conversion rate of deals scoring at each band. Most teams reach 90%+ accuracy within two cycles.

The fixed percentage a CRM assigns to each pipeline stage (e.g. Proposal = 60%) as a forecasting heuristic. Stage probabilities treat every deal in the same stage identically and routinely produce forecasts that are wrong by 30–50%.

How Predara measures itPredara replaces fixed stage probabilities with a continuous, behaviour-based deal probability that updates every time the deal does — so two deals in the same stage with very different engagement get very different forecasts.

A data-driven description of the customer most likely to buy, succeed and renew. A real ICP is built from your closed-won history — not aspiration — and answers: industry, employee band, geography, tech stack, deal size, and the buying triggers that preceded the win.

How Predara measures itPredara's ICP Analysis turns your closed-won and closed-lost data into a ranked profile: top 5 industries, winning company sizes, dominant tech-stack signals, average winning deal size, and the lead sources with the highest win rate. Updated as new deals close.

An AI integration model where the system can analyse CRM data but cannot modify, delete or write back to records. Read-only AI is the lowest-risk way to deploy AI on top of a CRM because it cannot corrupt your source of truth, requires fewer permissions, and dramatically simplifies security review.

How Predara measures itPredara connects via OAuth in read-only mode. The platform never updates a deal stage, never edits a contact, never overwrites a forecast field — it only reads, analyses and displays. Sales operations stay 100% in control of the CRM.