KPI Tree

Attio Metric

CRM

Sales Cycle Length = Average(Close Date - Deal Creation Date)

Sales cycle length measures the average number of days from deal creation in Attio to a closed-won outcome. It captures the full duration of the active sales process and reveals how efficiently deals move through the pipeline from qualification to close.

Full guide: definition, formula, and benchmarks

Sales Cycle Length

Sales cycle length measures the average number of days from deal creation in Attio to a closed-won outcome. It captures the full duration of the active sales process and reveals how efficiently deals move through the pipeline from qualification to close.

How to calculate sales cycle length

Sales Cycle Length = Average(Close Date - Deal Creation Date)

Why sales cycle length matters for Attio users

Sales cycle length directly determines pipeline planning horizons and revenue predictability. A team with a 60-day cycle needs pipeline created two months before close, while a team with a 120-day cycle needs four months of lead time. Without accurate cycle length data segmented by deal type and size, pipeline generation efforts are either too early (wasting capacity) or too late (missing targets).

Cycle length trends reveal market and process dynamics. Lengthening cycles may indicate increased competition, more complex buying committees, or economic headwinds that slow purchasing decisions. Shortening cycles may result from process improvements, better qualification, or market urgency. Tracking these trends in Attio provides leading indicators of market conditions that affect revenue planning.

Understand and act on sales cycle length with KPI Tree

Sync Attio deal creation dates and close dates into your warehouse. KPI Tree calculates cycle length for every closed deal, segmented by deal size, company segment, rep, and source.

Add sales cycle length to your metric tree as a key efficiency metric that feeds into pipeline velocity. Assign ownership to sales managers, set alerts for cycle lengths that exceed historical benchmarks, and compare cycles across segments to identify where process or resource adjustments could accelerate revenue.

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Related Attio metrics

Sales Pipeline Velocity

CRM

Metric Definition

Pipeline Velocity = (Number of Opportunities x Average Deal Value x Win Rate) / Sales Cycle Length

Pipeline velocity quantifies the rate at which the sales pipeline in Attio converts into revenue. It combines the number of open opportunities, average deal value, win rate, and sales cycle length into a single metric representing the revenue-generating throughput of the pipeline per unit of time.

View metric

Deal Velocity Analysis

CRM

Metric Definition

Deal velocity analysis examines the speed at which deals progress through pipeline stages in Attio. It measures time-in-stage at each transition, identifies stages where deals decelerate, and compares velocity across segments, deal sizes, and reps to surface factors that accelerate or slow the sales process.

View metric

Deal Stage Conversion Analysis

CRM

Metric Definition

Deal stage conversion analysis measures the percentage of deals that successfully advance from one pipeline stage to the next in Attio. It calculates stage-to-stage conversion rates, time-in-stage, and identifies the specific transitions where deals most frequently stall or drop out.

View metric

Forecast Accuracy

CRM

Metric Definition

Forecast Accuracy = (1 - |Forecasted Revenue - Actual Revenue| / Actual Revenue) x 100

Forecast accuracy measures the percentage deviation between forecasted revenue (based on Attio pipeline data and probability-weighted projections) and actual closed revenue for a given period. It evaluates the reliability of the sales forecasting process and identifies systematic biases like chronic over-forecasting or under-forecasting.

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