---
title: "KPI definitions in e-commerce: metrics nobody negotiates anymore"
description: "Revenue, conversion rate, CAC — in most shops each of these has three definitions. What a KPI definition has to contain so that meetings argue about decisions instead of numbers."
canonical_url: "https://nuonic.de/en/insights/kpi-definitions-ecommerce"
last_updated: "2026-10-26"
---

There is a meeting that anyone responsible for numbers in e-commerce will
recognise. It is scheduled for an hour, the question on the table is whether a
measure worked — and the first twenty minutes go on the fact that three people
have three different revenue figures for the same month on screen. That leaves
forty minutes for the actual decision, and it ends up being made by whoever's
export looked most convincing.

In the [first article of this series](/en/insights/measurable-ecommerce-strategy)
this was one of five patterns that break measurable strategies: every metric
has three definitions. This article takes that one pattern apart — because it
is the one that blocks all the others. Without a binding KPI definition, no
planned trajectory holds up, no impact measurement is verifiable, and no
forecast is more than an extrapolation on soft ground.

The good news: this is not an analytics problem and not a question of BI
tooling. It is definition work, and it takes days rather than months. The
uncomfortable news: it cannot be delegated, because every definition contains
a business decision.

## Why the name of a metric is not a metric

"Conversion rate" sounds like a defined term. In practice it is a question with
at least four open slots: orders divided by *sessions* or by *users*? Do orders
that were later cancelled count? Do sessions without consent count if they are
modelled? And does this apply to the whole shop, or per channel, per device,
per language?

Each slot is harmless on its own and decisive in combination. A conversion rate
on a user basis sits well above one on a session basis, depending on assortment
and return visit behaviour — in Google Analytics a session starts when a user
views a page with no active session and ends after 30 minutes of inactivity by
default
([Google Analytics Help](https://support.google.com/analytics/answer/9191807)).
Someone who researches on Monday and buys on Thursday is one user with two
sessions. Both numbers are correct. They are simply not the same number.

The same holds for every other metric that shows up in strategy documents. And
as long as the definition is not written down, every meeting negotiates the
number first and the decision second. That is not sloppiness, it is a logical
consequence: if three departments hold three legitimate views and none of them
is marked as binding, the view that happens to fit best is the one that wins.

## The anatomy of a KPI definition

A usable KPI definition answers ten points. None of them is optional, and for
none of them is a heading enough:

1. **Name and question.** Which decision is this number supposed to enable? A
metric without an attached decision is a report, not a KPI.
2. **Formula.** Numerator and denominator, written out. Not "revenue per
order," but which sum over which line items.
3. **Source system and fields.** Which system is the binding source — and
which fields exactly. Not "from Shopware," but which table, which status,
which price basis.
4. **Time basis.** Order date, invoice date, payment date or shipping date.
This choice shifts monthly figures by double-digit percentages whenever
delivery times cross a month boundary.
5. **Scope.** What is excluded: test orders, staff orders, cancellations, B2B
or B2C, foreign currencies, marketplace channels, shipping, VAT.
6. **Granularity and dimensions.** At which levels the metric is valid —
total, per channel, per assortment group, per country. Not every metric is
meaningful at every level.
7. **Target and benchmark.** A conversion rate of 2.1% is neither good nor bad
without a point of comparison. Without a target it is merely observation.
8. **Owner.** A person, not a team. They decide on interpretation in case of
doubt, and on changes to the definition.
9. **Stability rule.** From when is the value final? Returns, cancellations
and invoicing keep changing a monthly figure for weeks afterwards.
10. **Known limits.** Where the number is systematically biased, and why. A
documented weakness is more reliable than a clean figure whose gaps exist
only in one person's head.

In practice this fits on half a page per metric. For the three most important
metrics of a goal that is an afternoon's work — and it replaces the twenty
minutes of number negotiation in every future meeting.

Written out, such a definition looks like this:

```text
KPI             Net merchandise revenue
Question        How much merchandise value did we keep this month?
Formula         SUM(line item net) − SUM(returns net)
Source          Shopware 6 — order line items, net price basis
Status          paid, partially paid; excluding cancelled
Time basis      Order date (returns assigned to the originating month)
Scope           excluding shipping, excluding test orders (internal customer
                group), foreign currency at the order day's booking rate
Granularity     total, per sales channel, per assortment group
Target 2027     EUR 1.2m · benchmark previous year EUR 980k
Owner           Head of E-Commerce
Stable from     T+45 days (return window + processing)
Limits          marketplace revenue not included — separate metric
Version         v2, effective 2026-10-01 (previously: gross, before returns)
```

The last point is the one most often missing. A KPI definition gets changed,
and that is normal — assortments shift, systems are added, a scope rule turns
out to be wrong. But if the change happens silently, nobody can explain the
jump in the time series any more. A definition therefore needs a version with
a date and a reason, exactly like the guiding statement from part one.

## The five metrics most often broken in shops

There are dozens of metrics in e-commerce. Disagreement almost always concerns
the same five.

### Revenue

The metric with the most variants: gross or net, with or without shipping,
before or after returns, with or without cancellations, order date or invoice
date, foreign currency at which rate. Every combination has a legitimate use —
finance needs the invoice date, marketing needs the order date, purchasing
needs the net merchandise volume.

The mistake is not having several variants. The mistake is calling all of them
"revenue." If you need three variants, name three metrics: gross order value,
net merchandise revenue and invoiced revenue. Technically this hangs off the
states of the three state machines that start with every order — order,
transaction and delivery
([Shopware Developer Docs](https://developer.shopware.com/docs/concepts/commerce/checkout-concept/orders.html)).
Which states feed into the metric is a business decision and belongs in the
definition, not in a SQL query only one person knows.

### Conversion rate

Settle the denominator — sessions or users — exclude bots and internal
traffic, and decide how non-consented traffic is handled. Google Analytics
models the behaviour of users who decline analytics cookies based on similar
users who accept them
([Google Analytics Help](https://support.google.com/analytics/answer/11161109)).
That is useful for trend statements and unusable as the numerator of a
revenue-relevant metric.

From this follows a rule that saves a lot of argument: **orders come from the
shop, sessions come from analytics.** The conversion rate is therefore a metric
spanning two systems — and for exactly that reason it needs a definition
recording which system supplies which part. The same applies to intermediate
steps: what counts as a key event is a configuration, not a law of nature
([Google Analytics Help](https://support.google.com/analytics/answer/9267568)).

### Contribution margin

The most important and most rarely defined metric. From net merchandise
revenue, subtract: cost of goods, shipping cost as actually incurred rather
than as a flat rate, payment fees per payment method, returns cost including
processing and loss of value, discounts and vouchers. What is not subtracted
because it cannot be attributed — warehousing, staff, tooling — is left out
deliberately and documented as a limit.

This metric decides almost every prioritisation in assortment and marketing.
Without it, you steer growth on a revenue basis and learn about your margin in
the annual accounts.

### CAC and ROAS

Two questions to settle before any calculation. First: which costs count? Media
spend only, or agency fees, tool cost and internal hours as well. Both variants
are usable, they just are not called the same thing. Second: which revenue
counts? Attributed revenue depends entirely on the chosen attribution model
([Google Ads Help](https://support.google.com/google-ads/answer/6259715)), and
which model applies is a company decision, not a tool's default.

There is a further point that routinely gets lost in practice: a ROAS on a
revenue basis is not a statement about profitability. Google Ads optimises
bidding strategies against the conversion value you pass in
([Google Ads Help](https://support.google.com/google-ads/answer/6268637)). If
that value is the gross order value, the system optimises towards large baskets
— including the ones with the highest return rates. Only a conversion value
close to contribution margin points the bidding logic at what actually stays in
the business. We will cover channels and attribution in detail later in this
series.

### Return rate

Per item or per order? On a unit or a value basis? And over which time window —
because a return arrives weeks after the order. Dividing this month's returns
by this month's orders systematically understates the rate; the clean approach
assigns returns to the originating month of the order, with a stability rule
for the point at which the value counts as final.

The order of magnitude justifies the effort. The Returns Management Research
Group at the University of Bamberg expects around 560 million return parcels in
Germany in 2026, after roughly 542 million in 2025; close to one in four
parcels shipped in German B2C e-commerce is returned
([retourenforschung.de](https://www.retourenforschung.de/info-aktualisierte-schaetzung-bezueglich-der-anzahl-an-retourenpaketen-im-jahr-2026.html)).
Keeping three variants of a metric that describes about a quarter of your
volume is expensive.

## One metric, one source of truth

Shop, analytics, ad account and Search Console will never show the same
numbers. They measure at different points, in different time zones, with
different consent coverage and different attribution. Trying to reconcile that
gap away is wasted time.

The productive move is the opposite commitment: every metric has **exactly
one** leading system — the one that sits closest to the event.

- Orders, carts, returns, cancellations → shop
- Sessions, entries, funnel behaviour → analytics
- Cost, clicks, impressions on paid surfaces → ads
- Impressions, clicks and position in organic search → Search Console
- Invoices, incoming payments, credit notes → ERP or finance

Anything computed across several systems gets its composition written into the
definition — including the shared key used to join. The interesting metrics
arise exactly at those seams: contribution margin per channel, revenue per
organic click, return rate per campaign. And so do the misattributions, when
the key is not clean.

## How many metrics a goal carries

The typical failure mode is not a shortage of metrics but a surplus. A
dashboard with forty numbers signals control and delivers none: if everything
is watched, nothing is prioritised.

A three-way split works. Every goal carries **one lead metric** it is measured
by. Alongside it sit **two or three drivers** — the metrics through which the
lead metric is moved. And alongside those sit **guardrails**: metrics that are
not meant to improve but must not deteriorate. Conversion optimisation with a
return-rate guardrail is a different task from one without. This reduction to a
few metrics that relate to each other is the actual substance of the
[Balanced Scorecard](https://hbr.org/1992/01/the-balanced-scorecard-measures-that-drive-performance-2) —
and it has not worn out in more than three decades.

Everything else is diagnostics. Diagnostic metrics are useful when a lead
metric tips over and you want to know why. They belong in the analysis, not in
the goal structure.

## Four anti-patterns a definition will not fix

**A ratio without an absolute.** A conversion rate that rises because traffic
collapsed is a deterioration. Every ratio needs its numerator and denominator
in view.

**An average over a skewed distribution.** An average order value of EUR 85 can
consist of EUR 85 orders, or of very many small ones and a few very large ones.
For assortment, shipping logic and free-shipping thresholds those are two
entirely different shops. Where the decision depends on the distribution, a
median or a percentile belongs in the definition.

**A metric without a data basis.** Many metrics from strategy documents cannot
be computed at all with the systems that are actually connected. Knowing that
early is worth more than a nice target figure — because then the first measure
is the data integration, not the optimisation.

**A target metric without a guardrail.** Any metric a team is measured on will
be optimised — including by routes nobody intended. Lowering the return rate by
making returns harder. Lifting the conversion rate by switching off expensive
traffic. Which is why every target metric needs the counter-metric that makes
the abuse visible.

<faq-section :items="[{"question":"What belongs in a KPI definition?","answer":"Ten things — the name and the decision it enables, the formula with numerator and denominator, the source system and its fields, the time basis, the scope, the granularity, a target and a benchmark, a named owner, a stability rule, and the known limits of the number. Plus a version with a date and a reason, so later jumps in the time series stay explainable."},{"question":"Should the conversion rate use sessions or users?","answer":"Either is valid, but it has to be decided once and written down. On a user basis the value is higher, because someone who researches on Monday and buys on Thursday counts as one user with two sessions. In Google Analytics a session ends after 30 minutes of inactivity by default."},{"question":"Which system is the source of truth for revenue?","answer":"The shop, not the analytics tool. Orders, carts, cancellations and returns originate in the shop system and are recorded there in full. Analytics supplies sessions and behaviour, the ad account supplies cost and clicks, finance supplies invoices. Every metric gets exactly one leading system — the one closest to the event."},{"question":"When is a monthly revenue figure final?","answer":"Only after the return window and processing have elapsed, in practice often 30 to 60 days after the order date. Until then the value is provisional. That is why every metric needs a stability rule naming that point — otherwise provisional numbers get treated as final ones."},{"question":"How many metrics should a goal have?","answer":"One lead metric the goal is measured by, plus two or three drivers that move it, plus guardrails that must not deteriorate. Everything else is diagnostics and belongs in the analysis, not in the goal structure. A dashboard with forty numbers signals control and delivers none."}]" background="default" label="FAQ">

Common questions about KPI definitions.

</faq-section>

## How we model this in nuonic Lens

We ran this definition work in spreadsheets and Confluence pages for years, and
it decayed every time — not because it was wrong, but because the definition
and the number lived in two different places. Whoever sees the number on the
dashboard does not go and look up the definition.

In [nuonic Lens](/en/insights/measurable-ecommerce-strategy) the KPI is
therefore not a field on a dashboard but the object itself: a formula over named
fields of the connected sources, with time basis, scope, target, benchmark,
owner and stability rule — versioned, with a date and a reason for every
change. Every number in the system can be expanded down to the fields it comes
from. And where the connected sources cannot produce a requested metric, the
system says so instead of filling the gap with an approximation.

nuonic Lens is still in development — there is no public sign-up and no pricing
for the time being. If you want to follow the series or talk to us about it
early, [just get in touch](/en/contact).

## The next step

Three checks that need no new tooling:

1. **Take your most important metric and have two people calculate it
independently.** If the results differ, you do not have a metric, you have a
term.
2. **Write out the ten points above for your three most important metrics.**
Every point where you have to ask the owner is an open business decision —
and that is precisely the source of the discrepancy.
3. **Check that every metric can be computed with the systems you have
connected.** What cannot be computed is not a goal, it is a data project.

Before this series moves into the specialist topics, we cover the
fundamentals: the next article is about the goal systems themselves — OKR,
Balanced Scorecard, KPI trees and Hoshin Kanri side by side, and which of
them fits which shop. Because the definitions from this article need a
structure to hang in.

If you would rather not build the goal structure and the KPI definitions
alone: that is exactly what we do in [consulting](/en/services/consulting), and
in [growth](/en/services/growth) we run it as a cycle with before-and-after
measurement. [Get in touch](/en/contact) — a conversation with the people who
also build it.

## Sources and further reading

- [Shopware Developer Docs: Orders (order, transaction and delivery state machines)](https://developer.shopware.com/docs/concepts/commerce/checkout-concept/orders.html)
- [Google Analytics Help: About Analytics sessions](https://support.google.com/analytics/answer/9191807)
- [Google Analytics Help: Behavioral modeling for consent mode](https://support.google.com/analytics/answer/11161109)
- [Google Analytics Help: About key events](https://support.google.com/analytics/answer/9267568)
- [Google Ads Help: About attribution models](https://support.google.com/google-ads/answer/6259715)
- [Google Ads Help: Target ROAS bidding](https://support.google.com/google-ads/answer/6268637)
- [Returns Management Research Group (University of Bamberg): return parcels 2026](https://www.retourenforschung.de/info-aktualisierte-schaetzung-bezueglich-der-anzahl-an-retourenpaketen-im-jahr-2026.html)
- [Harvard Business Review: The Balanced Scorecard — Measures that Drive Performance](https://hbr.org/1992/01/the-balanced-scorecard-measures-that-drive-performance-2)

## Keep reading

- [Measurable strategy in e-commerce: why goals without numbers aren't goals](/en/insights/measurable-ecommerce-strategy)
- [F.O.C.U.S. — the method behind our projects](/en/framework/focus)
- [Consulting: decisions based on data](/en/services/consulting)
- [Growth: scaling is a system](/en/services/growth)
- [E-commerce search: why your shop needs search that actually finds](/en/insights/ecommerce-search-that-finds)