Academy · Attribution · Guide
Attribution splits the credit across touchpoints,
it does not prove what worked.
Before someone buys from you or sends an inquiry, they have usually seen you several times: a post, a newsletter, a search, a referral. Attribution is the rule you use to split one deal across those touchpoints. This guide walks through the common models with a fictional example and shows where each rule gets it wrong.
Which decision should your attribution prepare: budget, content or sales?
2 questions in the plan. First question: “Is our LinkedIn effort paying off?”
The four models
Collect touchpoints per deal Pick a rule and stick to it
“Is our LinkedIn effort paying off?”
First touch, last touch, linear, position-based.
Before someone buys from you or sends an inquiry, they have usually seen you several times: a post, a newsletter, a search, a referral. Attribution is the rule you use to split one deal across those touchpoints. This guide walks through the common models with a fictional example and shows where each rule gets it wrong. Example (fictional): a €9,000 deal after three touchpoints, a LinkedIn post, a newsletter, a Google search. First touch gives LinkedIn everything, last touch gives it all to search, linear gives each channel €3,000, position-based gives 40% to the first and last touch and 20% to the one in between.
From reading to doing
Your questions. For your numbers.
Prepare an evaluation.
2 questions selected
- “Is our LinkedIn effort paying off?”
The model follows the question: to judge attention, look at the first touch.
- “What finally gets trial accounts to buy?”
To improve the close, look at the last touch and write the model next to it.
Collect touchpoints, pick a rule, read it honestly.
it does not prove what worked.
First you need the list of touchpoints for each deal, then a fixed rule, then a way of reading the result that doesn't mistake assignment for cause.
“Is our LinkedIn effort paying off?”
The model follows the question: to judge attention, look at the first touch.
Collect touchpoints per dealFor each deal: which channels did the person touch before, and in what order? Sources are UTM parameters in links, a "How did you hear about us?" field and notes from the first meeting. In B2B, where decisions take a while, asking people is often the most reliable source.
Pick a rule and stick to itFirst touch shows what creates attention; last touch shows what triggers the close; linear and position-based spread the credit in between. Decide once, name the model in the report and don't switch it from month to month.
Read assignment, not causeAttribution tells you where customers passed by, not whether they would have bought without that channel. To learn that, you need a comparison, such as the period before and after a campaign or a region without it.
First touch100% to the first channel · LinkedIn €9,000
Last touch100% to the last channel · Google search €9,000
Linearsplit evenly · €3,000 each
Position-based40 · 20 · 40% · €3,600 · €1,800 · €3,600
The playbook
Collect touchpoints, pick a rule, read it honestly.
Attribution in three steps
it does not prove what worked.
Collect touchpoints per deal → Pick a rule and stick to it → Read assignment, not cause
- 01
Collect touchpoints per deal
For each deal: which channels did the person touch before, and in what order? Sources are UTM parameters in links, a "How did you hear about us?" field and notes from the first meeting. In B2B, where decisions take a while, asking people is often the most reliable source.
Example · Harbourview Agency (fictional)“Is our LinkedIn effort paying off?”
First touch as the model, because this is about attention - 02
Pick a rule and stick to it
First touch shows what creates attention; last touch shows what triggers the close; linear and position-based spread the credit in between. Decide once, name the model in the report and don't switch it from month to month.
Example · Taktwerk Software (fictional)
Last touch as the model, stated openly“What finally gets trial accounts to buy?” - 03
Read assignment, not cause
Attribution tells you where customers passed by, not whether they would have bought without that channel. To learn that, you need a comparison, such as the period before and after a campaign or a region without it.
Example · Nordwind Travel Goods (fictional)“Does Instagram drive revenue even when people buy in the online shop?”
Capture pre-purchase touchpoints separately
Your quality check
Will the evaluation hold up?
Tick what you have checked. Your selection stays in this view only.
0 of 3 points checked
What this article is based on.
Editorial page with fictional examples (Harbourview Agency (fictional), Taktwerk Software (fictional), Nordwind Travel Goods (fictional)). The guide describes an approach; where Peak Analytics covers a step today, the page says so explicitly. No measurements, no customers, nothing is sent or saved.
- Editorial demo
Synthetic numbers in the browser. No real data is read, computed or saved.
- Checked evidence
Peak Analytics is a preview: pivot over orders, receipts, tasks, goals and files; count, sum, average, minimum, maximum; day to year; CSV export; sharing a released snapshot; largest value as a task.
peak-one app/w/[scope]/apps/analytics, lib/bi/model.ts, lib/views/pivot.ts, lib/bi/share.ts · checked 2026-10-29
One model, named openly, read honestly.
Which touchpoints you can capture reliably in the first place is what a tracking plan settles.
Frequently asked questions
Do I need Peak Analytics for this guide?
No. The guide works with any spreadsheet. Peak Analytics is a preview; where it covers a step today, the page says so.
Which attribution model is the right one?
The one that fits your decision: first touch for attention, last touch for closing. What matters is naming it and not switching all the time.
Does attribution prove a channel works?
No. It splits credit by a rule. Whether a channel has an effect only shows in a comparison, such as before and after.
Can Peak Analytics calculate attribution?
Not yet. Attribution analysis is planned. The preview shows revenue from orders per channel and marketplace, meaning where things sold.