Turn Attio relationship data into metric trees that reveal what drives deals forward.

Activity volume trends measure the total count and distribution of logged activities (emails, calls, meetings, notes) across time periods in Attio. This metric tracks whether activity levels are increasing, decreasing, or seasonal, and segments volume by activity type, rep, and deal stage to reveal effort allocation patterns.

Company segmentation analysis breaks down CRM performance metrics by company attributes stored in Attio: industry, employee count, revenue range, geography, and custom fields. It identifies which company segments yield the highest conversion rates, largest deal sizes, and fastest sales cycles.

Contact engagement score is a composite metric that quantifies how actively a contact is interacting with your team based on activity data logged in Attio. It weights emails exchanged, calls completed, meetings held, and recency of last interaction to produce a single score indicating relationship strength and buying intent.

Contact lifecycle analysis tracks how contacts progress through defined stages in Attio: from initial creation, through qualification, active engagement, opportunity association, and customer conversion. It measures conversion rates between stages, time spent in each stage, and identifies where contacts stall or churn out of the pipeline.

Contact-to-deal conversion rate measures the percentage of contacts in Attio that progress from initial CRM entry to being associated with an active deal. It is the most direct measure of whether your lead generation and qualification processes are producing contacts that enter the sales pipeline.

Customer acquisition cost (CAC) measures the total sales and marketing investment required to convert a prospect into a paying customer. By combining Attio's deal and activity data with cost inputs, CAC quantifies the efficiency of the entire acquisition process from first touch to closed deal.

Deal age distribution analyses the spread of open deals in Attio by their age (days since creation or days in current stage). It categorises deals into age buckets and compares the distribution against historical close patterns to identify deals that have exceeded normal timelines and may be stale or at risk.

Deal conversion rate measures the percentage of deals created in Attio that ultimately close as won. It is the broadest measure of pipeline effectiveness, capturing the combined impact of deal qualification, sales execution, competitive positioning, and pricing across the entire sales process.

Deal loss analysis examines closed-lost deals in Attio to identify patterns in loss reasons, competitive losses, deal characteristics, and sales process gaps. It categorises losses by reason, stage of loss, deal size, competitor, and rep to surface systemic issues that can be addressed to improve future win rates.

Deal size trend analysis tracks the average, median, and distribution of deal values in Attio over time. It identifies whether deal sizes are growing, shrinking, or shifting across segments, revealing trends in customer willingness to invest and the effectiveness of up-sell and pricing strategies.

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.

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.

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.

Lead response time measures the elapsed time between a new contact or lead being created in Attio and the first meaningful outreach by a sales rep (email, call, or meeting). It quantifies how quickly the sales team acts on new leads, which directly correlates with conversion probability.

Lead source attribution traces deals and revenue in Attio back to the original source that created the contact: inbound marketing, outbound prospecting, referrals, events, partnerships, or organic channels. It quantifies the pipeline and revenue contribution of each acquisition channel to inform investment decisions.

List performance analysis evaluates how contacts and companies within Attio's lists and filtered segments perform across engagement and pipeline metrics. It compares lists head-to-head on conversion rates, deal sizes, and sales velocity to determine which segmentation strategies produce the best outcomes.

Pipeline coverage ratio measures the total value of open pipeline in Attio divided by the revenue target for a given period. It indicates whether sufficient pipeline exists to achieve the target, accounting for historical win rates and the time remaining to close deals.

Pipeline health score is a composite metric that evaluates the overall quality and reliability of the sales pipeline in Attio. It combines deal age distribution, stage balance, activity recency, deal progression velocity, and coverage ratios into a single score that indicates whether the pipeline is likely to convert as expected.

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.

Revenue attribution by source allocates closed-won deal revenue in Attio back to the original acquisition channel or lead source. It goes beyond pipeline attribution by measuring which sources actually produce paying customers and revenue, not just deals created, providing the most accurate view of channel ROI.

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.

Sales rep performance analysis compares individual reps across the full spectrum of CRM metrics in Attio: activity volume, lead response time, deal creation rate, conversion rates, deal size, cycle length, and revenue closed. It identifies top performers, surfaces coaching opportunities, and reveals the specific behaviours that differentiate high and low performers.

Task completion rate measures the percentage of assigned tasks in Attio (follow-up calls, email responses, proposal sends, contract reviews) that are completed within their due date. It reflects sales process discipline and directly impacts deal progression and pipeline health.

Win rate by deal size segments overall deal conversion rates in Attio into value brackets, revealing how close rates vary across different deal sizes. It identifies the deal value ranges where the team is most and least competitive, informing pricing strategy, qualification criteria, and resource allocation.

Workspace utilisation analysis measures how effectively the team uses Attio's CRM capabilities: list creation and maintenance, custom field population rates, automation usage, integration activity, and data completeness. It identifies underutilised features and data quality gaps that reduce the value of the CRM investment.

Pipeline Velocity measures how quickly revenue moves through your Attio pipeline, expressed as the value generated per day. It combines the number of open deals, the average deal value, the win rate, and the average length of the sales cycle drawn from your Attio deal records and stage history. A higher figure means deals are progressing faster and converting more reliably from the moment they enter the pipeline.