Understanding and using attribution models in Juicy

This guide explains every attribution model in Juicy: what it does, when to use it, and what it tells you. It also covers how Juicy builds a customer's journey, how direct and organic traffic behave, and how to pick the right model for a question.

Overview

Attribution is how you assign credit to the ads that influenced a sale. Some customers do not buy the first time they see an ad. They might click a Facebook ad on Monday, a Google ad on Wednesday, then come back and buy on Thursday. An attribution model decides how the credit for that sale is shared across those clicks.

Juicy records the ad clicks that lead up to each order and lets you switch between models on the fly. The orders never change. Only the way credit is shared changes, so you can look at the same sales through different lenses and answer different questions.

Juicy attributes on clicks. A touchpoint counts when a shopper actually clicks an ad and lands on your store with the ad's tracking tags attached. Juicy does not credit ad views or impressions, and it does not use post-purchase surveys, so your attributed totals stay grounded in real visits to your store.

How Juicy builds the journey

Before any model is applied, Juicy works out the list of real clicks behind an order.

1. The pixel on your store records each visit that arrives from an ad.
2. When an order is placed, Juicy looks at the visits tied to that shopper's session in the run-up to the order.
3. It tidies that list into real clicks. Several loads of the same ad within 30 minutes count as one click, and visits that carry no ad information are set aside.
4. Each remaining click that maps to an ad or an ad platform becomes a touchpoint on the order.
5. Your chosen model decides how the order's revenue and profit are shared across those touchpoints, and that is what your dashboard shows.

The models at a glance

Single-click models give all of an order's credit to one click.

Weighted models share an order's credit across every click in the journey.

Single-click models

First click

First click gives 100% of the order to the first ad the shopper clicked. In the example, Facebook gets the full order.

• Use when you want to see which ads introduce new customers and start journeys.
• Strength highlights top-of-funnel ads that create demand, which last-click reporting tends to undervalue.
• Watch out it ignores everything that happened after the first click, including the ad that actually closed the sale.

Last click

Last click gives 100% of the order to the final ad before the purchase. In the example, Google gets the full order.

• Use when you have short purchase cycles or want to know what converts.
• Strength focuses on the ads that finish sales, which is useful for lower-funnel budget decisions.
• Watch out it over-credits demand-capture channels like Search and hides the ads that first brought the customer in.

Last click per platform

Each platform gets full credit for its own most recent click in the journey. In the example both Facebook and Google are credited with the order, because each was the last click on its platform.

• Use when you want to compare platforms as if each were reporting on its own, close to what you see inside Facebook Ads Manager or Google Ads.
• Strength every platform sees its true last-click contribution, so no platform is starved by another closing the sale.
• Watch out the same order can be counted under more than one platform, so platform figures can add up to more than your real order count. This is why your dashboard's overall total is not the plattorms simply added together. Use a single-credit model when you need a total that reconciles with your shop's actual orders.

Weighted models

Linear

Linear splits the order equally across every click. In the two-click example, Facebook and Google each get half the order and half its revenue.

• Use when you want a neutral, unbiased baseline that respects the whole journey.
• Strength no single click is over-valued or under-valued.
• Watch out by spreading credit evenly it can flatten the difference between an ad that did real work and one that was just along for the ride.

Position based

Position based rewards the first and last clicks most. The first and last each get 40%, and the remaining 20% is split across any clicks in between. With just two clicks it is a clean 50/50. With three clicks, say Facebook then TikTok then Google, Facebook and Google get 40% each and TikTok gets 20%.

• Use when you believe the ads that open and close a journey matter more than the ones in the middle.
• Strength captures both discovery and conversion in a single view.
• Watch out the shape is a fixed rule of thumb, not a measurement of true influence, so treat it as a lens rather than a verdict.

Time decay

Time decay gives more credit to clicks that happened closer to the purchase, easing off the further back you go. A click made the day before buying carries more weight than one from a week earlier, on a roughly seven-day half-life.

• Use when recent touches tend to drive your sales, or your purchase cycles are short.
• Strength reflects momentum, giving the closing stretch of a journey its due without ignoring earlier clicks entirely.
• Watch out it deliberately underweights top-of-funnel ads, so pair it with first click if you also want to see what starts journeys.

How direct and organic traffic behave

Not every visit arrives from an ad. Someone might type your address, follow an organic search
result, or come from a link with no tracking tags. Juicy cannot tie those visits to a specific ad.

• In every model, a click only takes part if Juicy can match it to an ad or an ad platform. Visits with no ad information are set aside when the journey is built.
• If an order has no ad clicks at all, it falls back to the order's own recorded source rather than being credited to a paid channel. So a purely organic order is not quietly handed to an ad.

If a channel you expected to see is missing or looks low, the usual cause is missing tracking tags on the links, so it is worth checking that your ad links carry their tracking parameters.

Which model should you use

There is no single correct model, only the right model for the question you are asking.

• Finding new customers. First click shows which ads open journeys and bring fresh demand.
• Optimising for conversions. Last click shows which ads close, which suits short cycles and bottom-of-funnel work.
• Comparing platforms head to head. Last click per platform lines up most closely with each network's own dashboard. Read it per platform, not as a shop-wide total.
• A balanced, neutral read. Linear treats the whole journey evenly and makes a good baseline.
• Valuing discovery and closing together. Position based leans on the first and last clicks.
• When recency matters. Time decay favours the ads nearest the purchase.

A practical habit is to keep one reconciling model, such as first click, last click, or linear, as your everyday view, and switch to last click per platform only when you are benchmarking a single platform against its native reporting.

Known simplifications

• Juicy attributes on clicks only. Ad views and impressions do not receive credit.
• Several loads of the same ad within 30 minutes count as one click, so a redirect or a double-loaded page does not inflate a journey.
• Visits after the order was placed do not count toward that order.
• Only clicks carrying ad tracking tags can be attributed. Everything else falls back to the order's recorded source.
• Last click per platform can credit one order to several platforms at once, so platform totals may exceed your real order count. That is expected, and it is why the main total is not the platforms added together.
• Switching models never changes your underlying orders. It only changes how existing sales are credited, so it is always safe to try a model and switch back.

Updated on: 01/07/2026