Event Type Distribution - Cosmise Attribution
See which on-site events (views, carts, checkouts, purchases) occur most often.
(141,170 users)
(95,299 users)
(32,875 users)
What does this show?
Events are grouped into three stages in the selected date range. Each stage shows how many users reached that stage, with a label like “(1,234 users)” and a bar that scales to the largest stage.
What is on screen?
- Stages: Awareness, Consideration, Conversion
- Metrics per stage: users label and a horizontal bar
- Bar length: users in stage ÷ largest stage × 100
- Hover detail: list of event types for the stage with users per type
How can I read this?
Scan Awareness → Consideration → Conversion and compare bar lengths to see which stages had more users in the same date window. Use the users label beside each stage to anchor comparisons, since bars are proportional to the largest stage.
Examples
- If Consideration has a bar similar to Awareness, a similar number of users moved into mid-stage events in this window.
- If Conversion has a noticeably shorter bar than Consideration, fewer users reached purchase events in this window.
Interactions
Hover a stage row to see a popover listing its event types (for example, checkout or cart) with user counts.
Notes on the selected dates
All counts and bar sizes reflect the currently selected date range. Changing the dates updates the stage totals and the hover lists.
Event Type Funnel — FAQ

See this insight in action
Want a quick walkthrough tailored to your goals? Book a live demo to explore how this widget works and how Cosmise can help.
More insights
Last Channel Before Abandonment
See which marketing channel users last touched before dropping off to target smarter retargeting.
Touchpoints Before Drop-Off
Measure how many interactions users have before abandoning to spot friction and fix leaks.
Average Time to Convert
Understand the typical time from first touch to purchase to set expectations and optimize funnels.
30/60/90-Day LTV by First Touch
Track cohort lifetime value at 30, 60 and 90 days, grouped by the channel that first acquired customers.
Customer Behavior Patterns
Identify the most common browsing and buying behaviors to tailor journeys and messaging.
Channel Impact by Journey Stage
Quantify each channel’s impact at every stage of the buyer journey to allocate budget effectively.
Conversion Time Distribution
Visualize how long conversions take across customers to uncover fast vs. slow-moving segments.
Conversions by Hour & Channel
Find the hours of day that drive the most conversions and the channels behind them.
Core User Metrics Overview
Monitor total, new, returning and active users for the selected date range.
Daily User Metrics Trends
Trend daily totals for new, returning and active users to spot momentum and dips.
First-Time vs. Repeat Purchases
Compare new vs. repeat order volume and revenue to gauge retention health.
New vs. Returning Users by Source
Discover the source/medium combos that attract new customers and bring users back.
Top First-Touch Sources
Identify where customers first discovered your brand to optimize acquisition.
New Customers: First vs. Last Source
Compare initial vs. closing channels for new buyers to balance prospecting and closing.
Returning Customers: First vs. Last Source
See which channels start and finish returning-buyer journeys to guide retention spend.
Funnel Step Drop-Off
Quantify how many users reach each step and where they exit to prioritize fixes.
Purchases by Hour & Referrer
See when purchases peak and which referrers dominate those hours.
Channel Lift & Assist Analysis
Measure how often channel A appears in journeys that convert on channel B to justify upper-funnel spend.
Initiating & Influencing Channels
Reveal channels that kick-off or influence converting journeys beyond last-click.
Channel Presence in Long Journeys
Find channels consistently present in complex, multi-touch paths.
Journey Length vs. Conversion Efficiency
Analyze whether longer paths correlate with higher AOV or lower conversion rates.
Journey Touchpoint Distribution
Quantify the share of short vs. long journeys to size effort to convert.
Longest Engagement Channel
See which channel holds user attention for the longest during converting paths.
Even Multi-Touch Attribution
Distribute credit evenly across all touches so fractional credits sum to 1 per journey.
New Customer Acquisition by Channel
Attribute first-ever purchases to earliest touchpoints to see where new customers come from.
Daily Platform Impact
Compare platform performance day by day across purchases, revenue and ROAS.
Platform Impact Summary
Rank platforms by total impact to guide budget allocation.
Platform Over-Reporting Audit
Compare ad platform claims (Google, Meta) to real attribution to estimate over-reporting.
Product Conversions by Channel
See which products convert from which channels to align merchandising and media.
Product: First & Last Sources
Find common first and last sources for each product’s converting journeys.
Journey Length by Product
Compare average conversion time across products to detect friction or urgency.
Daily Revenue & Orders
Track revenue and order counts by day to understand sales cadence and seasonality.
Source Performance Comparison
Benchmark sources against each other on conversions, revenue and efficiency.
Performance Spike Reasoning
Explain sales spikes by pinpointing the channels and campaigns that caused them.
Touchpoints per Journey
Count interactions per converting journey to gauge effort and attribution spread.
Vendors: Items Sold & Top Channel
Rank vendors by items sold and reveal their leading attribution channel.
Visits Before Purchase
Quantify sessions required before conversion to identify high-effort paths.
Likely Wasted Ad Spend
Estimate spend on users who would have purchased anyway to cut cannibalization.