How Do I Measure Assisted Conversions Across Campaigns

use case assisted conversion featured image

Your ad platforms will give you all the conversions they believe should be credited to their platform (based on their data and attribution models). What they can’t tell you is all the clicks your customers made on other platforms before they clicked ‘Buy’ on theirs.

Those clicks are assisted conversions and they matter just as much as the last purchase click, if not more.

So if you’re only tracking conversions through multiple ad platforms, you’ll come face-to-face with a problem: a distorted campaign performance report.

You’ll notice two things when you analyze your campaign results:

Closing channels get overcredited (because most ad platforms favor the last interaction)
Mid-funnel campaigns get undervalued (because of the credit logic used by ad platforms)

What you end up with is a lack of visibility across all ad platforms which means your assisted conversions (the interactions that influence and lead users to convert) stay hidden.

But why is this such a problem?

This is a problem ecause you end up making budgeting decisions based on short-sighted or incomplete data. You don’t have the full picture of your buyers customer journey to final conversion.

This then leads to the following scenarios:

You end up cutting spend on channels that are actually driving new demand
And increasing ad spend into bottom of the funnel campaigns that target customers who would have converted anyway

In this use case we explain why you can’t measure assisted conversions in individual ad platforms like Meta or Google Ads, and how tools like RedTrack can solve the problem so you get complete conversion data (including assisted conversions) all neatly housed in one place.

Challenge: You Can’t Track & Measure Assisted Conversions in Ad Platforms

The main reason you can’t track and measure assisted conversions though individual ad platforms isn’t because they’re nasty and they don’t want to give you the data. It’s because each ad platform operates on their own separate ecosystem.

So performance buyers face three major challenges when trying to decipher and measure assisted conversions.

1. Fragmented Attribution Across Ad Platforms

Each platform, whether Meta, Google, TikTok or other uses its own conversion reporting model.

They use different attribution windows, models and have different definitions of what they count as “conversions”.

Here’s a snapshot of the differences amongst the main ad platforms.

Ad Platform	Attribution Window	Attribution Model	Conversion Definition
Meta	7-day click, 1-day view	Last touch	Click-through: User clicks & converts View-through: User sees ad, doesn’t click instantly, but converts within 24 hours
Google	30-day click, 1-day view	Data-Driven-Attribution (AI assisted fractional credit)	Click-through: Conversion after a user clicks a Search, Display or YouTube ad View-through: User sees a display banner or thumbnail, doesn’t click & converts
TikTok	7-day click, 1-day view	Last touch	Click-through: User clicks the “Shop Now” or CTA button View-through: Use sees the video in their “For You” page and converts

So even if you try to manually decipher these results, you’re not dealing with data on a level playing field.

2. Mid-Funnel Contributions Go Uncredited

The second challenge is that most ad platforms default to last-click attribution models. This means all your mid-funnel campaigns don’t get reported or credited.

It also means:

Prospecting and awareness building campaigns seem unprofitable
Retargeting gets more credit than it should in reality

Assisted conversions in fact lie in mid-funnel campaigns and this means they are invisible.

3. Optimizations are Made on Last-Click & Incomplete Data

You need something to base you optimization and budget decisions on. Because all you have is what the ad platforms give you, you are boxed into following their models and rules.

Since most ad platforms give most credit to closing conversions, you end up making decisions that favor bottom-funnel campaigns, weakening the overall funnel that feeds and nurtures buyers to convert.

Your reporting guides you to:

Scale your “closer” campaigns
Neglect and undermine your “nurture” campaigns

And while you might not see the damage initially, it won’t take too long before you see sales dropping because you’ll end up cutting back on all the awareness ads that create the initial connection with your brand or product.

Solution: Use a Cross-Channel Tool to Reveal All Contributions to Conversions

To get the full picture and reveal all the contributions that led to your final conversions, you need a platform-agnostic tool like RedTrack.

It collects, collates and compares data from across all your ad campaigns across platforms, and centralizes it in one place so you can build unified reports and make optimization decisions based on true contributions.

Once you have the tool, you can measure assisted conversions accurately by moving away from platform-based attribution to model-based analysis.

RedTrack will let you:

Apply the same attribution model across all your ad channels
Compare different models to understand contribution better
See how credit attribution shifts based on different attribution models

The best way to find your assisted conversions is to do a model comparison between:

Last paid click (shows which ad and platform closed)
Linear attribution (shows which ad and platform contributed to the final close)

This gap between these two models will uncover assisted conversions.

Here’s an example to help make this logic clearer.

Say you have the following results when you do a last paid click and liner attribution model comparison for two channels Meta and Google Ads:

Meta Ads
- Last click – 100
- Linear – 180

Google Ads
- Last click – 150
- Linear – 140

The logic is, if a channel’s linear credit is higher than last click, it means the channel is playing a mid-funnel, assisting role in driving conversions.

So, if we look at the example above, Meta Ads is playing a strong assisting role in driving conversions, while Google Ads is acting mainly as a closer (not an assistor).

How RedTrack’s Attribution Modelling Report Solves the Assisted Conversions Problem

What RedTrack’s Attribution Modelling report does, is apply a single attribution model across all your connected traffic channels. It does this independently, and doesn’t rely on the ad platform’s specific model.

On top of that, it also lets you compare different models (like the one we mentioned in the above example) side by side, so you can instantly see which channel is delivering assisted conversions.

Here’s a step-by-step guide explaining how you can build an attribution modeling report using RedTrack.

Step 1: Open the report

When you log into RedTrack, go to:

Reports

Select Attribution Modelling

Step 2: Define your analysis scope

Next, you need to define your analysis scope. To do that:

Select the brand or website you want to analyze

Set the date range you’re interested in

Choose one of the following attribution windows:

7-14 days (for short purchase cycles)
30-56 days (for longer consideration journeys)

Step 3: Choose your baseline model

Now it’s time to select your baseline attribution model.

For measuring assisted conversions:

Select the Last Paid Click option

This model will:

Assign credit to the final paid interaction
Exclude any organic noise
Give you a clean performance baseline to start with

Step 4: Add a comparison model

Now you need to add another attribution model to compare your baseline results against.

Here, again for measuring assisted conversions:

Select the Linear attribution option

This is the model that will:

Distribute credit across all user touchpoints
Highlight assisted contributions

Step 5: Compare the two models side-by-side & identify assisting channels

To make comparison easier:

Select the option to view both models in the same table

Then spot the channels that rate higher for Linear.

These are your assisted conversion channels, which:

Influence earlier stages of the customer journey
Support future conversions without closing them initially

Step 6: Make better optimization decisions for long-term returns

You now have the full picture and pathway of all the ads, campaigns and channels that assisted your final conversions.

With that insight, you can make smarter optimization and budgeting decisions that will help you drive long-term growth by investing and focusing on the channels that generate and nurture new demand.

Some actions you can take might include: