Baseline
The before picture — without it, you can claim a lift but you can never prove one.
- Term
- Baseline
- Part of speech
- Noun
- Field
- Analytics / Experimentation
- Syllables
- base·line
Forms & parts of speech
Definition in plain terms
A baseline is the starting level of a metric, measured before you make a change, that you compare against afterward to judge the change's effect. It's the "before" in before-and-after — the reference point that turns a number into a result by giving it something to be measured against.
The mechanics
You establish a baseline by measuring the metric over a representative period before an intervention (a campaign, a feature, a price change), ideally long enough to capture normal variation and seasonality. The change's impact is the difference from the baseline — the lift. A good baseline accounts for trends that would have happened anyway, which is why a control group (a held-out baseline) is stronger than a simple before-after comparison.
When it matters
A baseline matters for any claim of improvement: without one, a rise could be the change working, normal fluctuation, or a trend already underway. It's foundational to experimentation, goal-setting, and reporting. The common failure is declaring victory against no baseline, or against a cherry-picked or unrepresentative one that makes any result look good.
Synonyms & antonyms
Synonyms
Antonyms
Usage trends
Search interest for this term over the last five years:
Common questions
- What is a baseline?
- A reference level of a metric measured before a change, used to judge the effect of that change.
- Why is a baseline important?
- Without it, a change in a metric could be the result of your action, normal fluctuation, or a pre-existing trend — you can't prove the effect.
- What makes a good baseline?
- A representative pre-change period that captures normal variation and seasonality — and ideally a control group rather than a simple before-after.
Related tools & calculators
Resources & people to follow
- bookTrustworthy Online Controlled Experiments — Kohavi, Tang, Xu
- bookLean Analytics — Croll & Yoskovitz
- thought leaderRonny Kohavi — experimentation
Curated, non-competitor resources verified per term.
Related training
- moduleMarketing analytics
Disciplines
Areas of marketing where baseline is a core concern: