Jurni Metrics Glossary

Browse the Jurni metrics glossary for clear definitions of key terms. Understand how each metric is calculated and when to use it in your analysis.

Use these definitions when reading experience and experiment performance. Compare the same date range and traffic scope before comparing two reports.

Core metrics at a glance

Metric	What it tells you	Calculation
Sessions	The counted visits included in the report.	Visits in the selected reporting scope.
Orders	Completed orders attributed to those visits.	Count of distinct attributed orders.
Revenue	The attributed order value in the report.	Sum of the attributed order amounts.
CVR	Attributed orders relative to sessions.	Orders ÷ Sessions × 100.
AOV	The average value of an attributed order.	Revenue ÷ Orders.
RPS	Revenue generated per counted session.	Revenue ÷ Sessions.
Click-through rate	The share of sessions with the tracked click-through action.	Sessions with click-through ÷ Sessions × 100.
Add-to-cart rate	The share of sessions with a tracked add-to-cart action.	Sessions with add-to-cart ÷ Sessions × 100.
Checkout rate	The share of sessions with a tracked checkout-start action.	Sessions with checkout started ÷ Sessions × 100.

Sessions are not unique people

Jurni’s performance reports use counted visits as their session unit. One person can produce more than one visit. Do not assume the number matches unique visitors, raw PageView events, or a different platform’s session count.

Experience and experiment reports can include different traffic. For example, a direct visit to a page does not necessarily belong to an experiment. See Experience versus experiment sessions.

Orders and revenue follow attribution

Orders and revenue are connected to the visit credited by Jurni. They are not simply every order placed in your Shopify store during the same period.

The reporting window follows the attributed visit’s date. An order-date report in another tool can therefore differ even when both tools show the same calendar range. See Attribution before reconciling totals.

CVR: purchase efficiency

With 1,000 counted sessions and 50 attributed orders, CVR is 5%.

The calculation uses orders, not a separate count of unique purchasing people. It should not be silently redefined as unique customers divided by traffic. Use AOV and RPS alongside CVR when the variants have different basket sizes.

AOV and RPS: basket size versus traffic value

With 5,000 in attributed revenue, 50 orders, and 1,000 sessions, AOV is 100 and RPS is 5, in the report’s currency.

AOV can increase while fewer visitors purchase. RPS helps compare that trade-off because it accounts for the revenue generated by all counted sessions, not just orders. Neither metric is profit or return on ad spend.

Action rates are not raw event totals

For click-through, add-to-cart, and checkout-start rates, the corresponding action group is counted at most once per visit. Repeated actions within that visit do not create multiple converting sessions for the same rate.

For example, if 100 of 1,000 sessions include at least one tracked add-to-cart, the rate is 10%, even when some shoppers add several items.

Jurni’s click-through rate describes the tracked page action. It is not Meta’s ad clicks divided by ad impressions. See Meta ad insights when comparing page and ad performance.

Read the metrics together

Choose the primary goal before evaluating a test. CVR helps assess purchase completion; AOV helps assess basket size; RPS helps assess revenue from the traffic. Use intermediate action rates to investigate where a change may have helped or hurt.

A higher observed metric does not by itself establish a statistically reliable winner. Use the experiment’s available decision information and the testing guide, rather than a universal visitor-count rule.

Missing data and comparisons

No tracked data is not automatically zero performance. Before drawing a conclusion, check the active shop, date range, selected page or experiment, tracking setup, and attribution scope. Do not average percentage rows to reconstruct an overall rate: use the underlying totals.

Related guides

• Analytics overview
• Experience analytics
• Read experiment results
• Attribution overview
• Why analytics differ
• Event dictionary