Measurement
Part of Programmatic advertising measurement without vanity metrics
How to compare programmatic advertising attribution methods
A practical comparison of programmatic advertising attribution methods, from last-click to incrementality testing, with a checklist for agency measurement plans.
What to take away
Programmatic advertising attribution methods are the written rules that decide which impressions, clicks or modelled touchpoints receive credit for a conversion.
- Match the method to the decision you need to make, not the dashboard you already own.
- Last-click stays useful for counting, but it hands credit to whatever ran last.
- Multi-touch and data-driven models need clean event data and a documented lookback window.
- Incrementality tests answer causal questions that credit models cannot.
- Agree the method, the owner and the reporting cadence before launch.
What do the main attribution methods compare on?
Line the methods up against the same question and the differences become practical rather than philosophical. Compare them on four things: what each one credits, what data it needs, how it behaves when tracking breaks, and how easily a client can challenge the result.
Attribution methods compared
Last-click
- What it credits
- Final click
- Data needed
- Click tags
- Main trap
- Flatters retargeting
First-click
- What it credits
- First touch
- Data needed
- Click tags
- Main trap
- No proof of value
Position-based
- What it credits
- Fixed shares
- Data needed
- Tags plus rule
- Main trap
- Arbitrary shares
Data-driven
- What it credits
- Modelled shares
- Data needed
- Event-level data
- Main trap
- Fragile when tagging breaks
What it credits
- Last-click
- The final click before conversion
- First-click
- The first recorded touch
- Position-based
- Fixed shares to first and last touches
- Data-driven
- Modelled shares across touchpoints
- Marketing mix model
- Channel contribution over time
- Incrementality test
- Lift against a holdout or geo split
Data needed
- Last-click
- Click and conversion tags
- First-click
- Click and conversion tags
- Position-based
- The same tags plus a written rule
- Data-driven
- Event-level data, enough volume to train
- Marketing mix model
- Aggregate spend and outcome history
- Incrementality test
- A controlled test design
Main trap
- Last-click
- Flatters retargeting and brand search
- First-click
- Rewards prospecting with no proof of value
- Position-based
- The shares are arbitrary and hard to defend
- Data-driven
- Hard to explain and fragile when tagging breaks
- Marketing mix model
- Needs months of history, no user-level detail
- Incrementality test
- Slow, and only covers what you test
Two axes separate these methods: association against cause, and user level against channel level. Credit models are cheap to run and easy to report, but they only describe association.
User-level and channel-level models answer different questions. A marketing mix model might show that paid social tracked with growth over a quarter. An incrementality test asks whether switching that channel off cost you sales. Neither replaces the other. If your pack still blends counting with causality, the measurement and reporting guidance shows how to keep them in separate columns.
Which method suits a tight agency budget?
Small budgets rule out anything that needs months of clean history. A team spending, for example, £3,000 a month on media can still run last-click from the ad server, then add one geo holdout each quarter. That pairing answers a counting question and a causal question without buying a measurement platform.
Vendor tooling is rarely the constraint; data discipline is. Document the rule in the plan rather than inside the platform, because platform defaults change and an undocumented default is hard to defend in a quarterly review.
Put media budgets beside ONS gross domestic product data when you write the plan, so spend reads as a share of output rather than an isolated figure. For background on how buyers and sellers structure this work, the IAB Media Centre collects resources on media buying and selling, including programmatic.
How do you test attribution without a full measurement stack?
Write the hypothesis first, then choose the control. A holdout group, a matched region or a paused channel all work if you fix the window before launch. Decide the primary metric in advance, because switching metrics after the results land voids the test. Record what you changed and when.
Running a small attribution test
- Write the hypothesis first
- Choose the controlholdout, region or paused channel
- Fix the test window before launch
- Decide the primary metric in advance
- Record what changed and when
- Report lift with confidence interval
Keep the test small enough to finish, since a two-week holdout on one channel beats a six-month study that never reports. Report the lift with its confidence interval, or state plainly that the result was inconclusive. Benchmarks give that number context, and programmatic advertising benchmark research explains how to set ranges you can defend.
What belongs on an attribution comparison checklist?
Use this list when you compare methods for a client:
- The decision the method will inform, written in one sentence.
- The credit rule, including the lookback window and any exclusions.
- The data source for clicks, impressions and conversions, with the owner named.
- The identity resolution approach and how it handles consent.
- The test design, if the method claims to measure lift.
- The reporting cadence and who signs off changes to the rule.
- The running cost, in licence fees and analyst hours.
Anything you publish about results is still an advertising claim, and the ASA sanctions guidance sets out what can follow a breach of the codes. Revisit the checklist whenever tracking, consent or channel mix changes, because a stale rule quietly flatters whichever channel ran last.
Common questions
How many attribution methods should one agency run?
Two is usually enough: one credit model for routine reporting and one test design for causal questions. Adding more models multiplies reconciliation work without settling anything.
Is last-click still acceptable?
Yes, as a counting metric. It answers how many conversions followed a click. It does not answer what the advertising caused, so avoid presenting it as proof of performance.
Should the client sign off the method?
Yes. The method changes which channels look effective, so it belongs in the plan rather than in a footnote.
