Core User Metrics Overview - Cosmise Attribution
Monitor total, new, returning and active users for the selected date range.
User Metrics Overview
Key user engagement metrics ranked by volume. Shows how different segments contribute to your overall user base.
What does this show?
A ranked list of user metrics for the selected date range. Each card displays the label and exact count, with a filled bar to compare sizes at a glance.
What is on screen?
- Metrics: Total Users, Active Users, New Users, Returning Users
- Each card: label, exact count, and a horizontal bar showing relative size
- Popover on hover: Exact count and % of total (not shown for Total Users)
- Percent of total formula: metric ÷ Total Users × 100
How can I read this?
Scan from top to bottom. The list is sorted by count, so the top card is the largest. Use the bar length for quick comparison and the number for precision. Hover a card to see Exact count and % of total to understand how much each segment contributes.
Examples
- If Active Users is smaller than Total Users, not everyone performed checkout/cart/purchase activity in this window.
- If New Users is larger than Returning Users, more people first appeared in this window than those who had prior activity and returned.
Interactions
Hover any card to see a popover with Exact count and % of total for that metric.
Notes on the selected dates
All counts reflect the currently selected start and end dates. Changing the date range updates the card counts and the relative bars.
User Metrics Overview — 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.
Daily User Metrics Trends
Trend daily totals for new, returning and active users to spot momentum and dips.
Event Type Distribution
See which on-site events (views, carts, checkouts, purchases) occur most often.
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.