Free tool · Marketing
Build a typical customer journey (the channels that touched your customer, in order) and instantly compare how last-click, first-click, linear, time decay and position-based attribution split conversion credit. Free, no sign-up — everything runs in your browser.
How it works
Add each channel in the order it touched your customer, from first contact to final conversion.
Last-click, first-click, linear, time decay (7-day half-life) and position-based 40-20-40: the 5 classic multi-touch attribution models, still the conceptual backbone of most marketing and CRM tools.
Each model assigns a different % of credit to each channel, using the same maths analytics platforms use.
Table and stacked bar chart to see, channel by channel, how much your "winning channel" changes depending on the model.
Attribution models, explained
Last methodology review: July 2026.
When a customer converts, they've almost never arrived through a single channel. They saw an ad on social media, searched for the brand on Google a few days later, opened an email, and finally clicked a paid search ad before buying. An attribution model is the mathematical rule that decides how much credit for that conversion each of those channels gets. Picking a model isn't a technical footnote — it changes which channel looks like a "winner" in your reports, and therefore where you move budget.
Last-click gives 100% of the credit to the channel that closed the sale — Google Analytics' default model for years, and still the easiest to read, though it penalises demand-generation channels (social, display) in favour of demand-capture ones (branded search, warm email lists). First-click does the opposite: all the credit goes to the channel that discovered the customer, useful for measuring demand generation but blind to what happens afterwards. The linear model splits credit equally across every touchpoint, an honest snapshot that doesn't distinguish real impact. Time decay gives more weight to touchpoints closer in time to the conversion (with a configurable half-life, 7 days here, the standard reference). And position-based, or U-shaped (40-20-40), recognises that the first and last touches tend to matter most, giving 40% to each and splitting the remaining 20% among the touchpoints in between.
No model is objectively best — each answers a different question. If your goal is to measure which channel closes sales, last-click is more useful; if you want to know which campaigns drive real awareness, first-click or position-based give a better read. What matters is using the same model consistently when comparing periods, and understanding that switching models can move a channel's apparent ROI without its real performance changing at all. One nuance worth knowing: both Google Analytics 4 and Meta Ads Manager have phased out these manual models as selectable options within the platform itself (GA4 replaced them with Data-Driven Attribution in 2023; Meta retired its standalone Facebook Attribution panel in 2021) in favour of data-driven attribution. They remain, though, the standard vocabulary of the field and the backbone of most marketing and CRM tools — understanding them helps you read any attribution report, on any platform. This simulator lets you see the effect of each model on your own customer journey before deciding how to read your real data.
You can dig deeper into the logic and real examples in our article (in Spanish) modelos de atribución: una herramienta imprescindible para optimizar tus campañas, or review the rest of the marketing services we offer to turn this data into budget decisions.
Frequently asked questions
It's the mathematical rule that splits credit for a conversion among the different channels or touchpoints a customer touched before converting. Without an attribution model, you only know a sale happened — not which combination of channels made it possible.
First-click gives 100% of the credit to the channel that discovered the customer (useful for measuring demand generation); last-click gives 100% to the channel that closed the conversion (useful for measuring which campaigns convert best). They're the two extremes — almost no business should rely on only one of them.
It depends on your goal: to see which channel closes sales, use last-click; to measure which campaigns generate new demand, use first-click or position-based; for a long journey and a balanced view, try linear or time decay. What matters most is keeping the same model when comparing periods and, with enough volume, considering a data-driven (machine-learning) model like GA4's.
It gives more credit to touchpoints closer in time to the conversion, using a half-life (the time it takes for the weight to halve). This simulator uses a 7-day half-life and assumes each touchpoint is 7 days apart from the next, the most common convention; in your real platform you can set both to exact dates.
It gives 40% of the credit to the first touchpoint, 40% to the last, and splits the remaining 20% equally among the touchpoints in between. It recognises that discovery and closing tend to be the most decisive moments of the journey, without fully ignoring what happens in between.
What now?
Book a free 30-minute session and we'll go through which attribution model fits your business, how to set it up in GA4 or Meta Ads, and how to use it to move budget with confidence.