Signal Quality
Ad platforms thrive on conversion signals — but most upper-funnel ads don't drive immediate conversions. SegmentStream fixes the broken feedback loop with Synthetic Conversions.
01.Ad Platforms Underperform Due to a Lack of Conversion Signals
Meta, Google, and LinkedIn thrive on conversion signals to target and optimise ad campaigns. Yet most upper-funnel ads don't drive immediate conversions. They happen later — often from another device, browser, or cookie. As a result, such campaigns are undervalued, under-optimized, and unable to scale.
The problem is structural. Meta, for example, only counts conversions that happen within 7 days of a click. If a user takes longer to convert — which is the norm for high-value products, B2B services, or anything with a consideration cycle — Meta never sees that conversion. It can't use it for algorithm optimization. As far as the platform is concerned, that click produced nothing.
A potential customer clicks on your Instagram ad, explores your site, but doesn't buy immediately. Two weeks later, they return via brand search from another device and complete a purchase. Despite the critical role of the Instagram ad in acquiring this customer, it doesn't get any credit.
Instagram drove the acquisition, but brand search gets 100% of the credit. The ad platform never learns which clicks are valuable.
This breaks ad optimization for exactly the campaigns that need it most: upper-funnel prospecting and businesses with long sales cycles. The audiences most likely to convert are the ones the platform stops targeting — because the feedback loop is blind to delayed conversions.
Meta's 7-day attribution window means every conversion after day 7 is invisible to the algorithm. Your best prospecting campaigns die from a data gap — not poor performance.
02.What Are Synthetic Conversions?
Synthetic Conversions are AI-powered signals that predict the likelihood of a future purchase based on real-time user behavior. They enable ad platforms to optimize for valuable visits even before an actual conversion occurs.
Instead of focusing on clicks, impressions, or random website events, you can achieve greater performance by optimizing for metrics directly tied to revenue. Synthetic Conversions signal ad platforms about valuable website interactions with a high potential to convert soon — ensuring each paid click instantly receives the credit it deserves, even if the actual conversion occurs later on a different device, browser, or cookie.
- Assign proper incremental value to all paid clicks — not just the ones that convert immediately.
- Scale upper-funnel prospecting campaigns with confidence, knowing ad platforms can see which clicks drive high-intent visitors.
- Optimise ads that lack cookie-tracked conversions — especially cross-device and long-cycle purchases.
| Visitor ID | Conversion Probability | Value | Predicted CV | Synthetic Conv. |
|---|---|---|---|---|
vis_4E82 | 48% | $349.00 | $167.52 | Sent |
vis_1A03 | 41% | $215.00 | $88.15 | Sent |
vis_9F31 | 36% | $178.50 | $64.26 | Sent |
vis_2B47 | 32% | $420.00 | $134.40 | Sent |
vis_7D19 | 24% | $195.00 | $46.80 | — |
vis_3C55 | 15% | $89.00 | $13.35 | — |
vis_8A92 | 9% | $310.00 | $27.90 | — |
vis_6E08 | 3% | $125.00 | $3.75 | — |
Visitors scored in real time. Those above the 30% threshold trigger a Synthetic Conversion sent to ad platforms.
03.How Synthetic Conversions Work
Step 1: ML-Powered Visit Scoring
SegmentStream trains custom machine learning models on a client's conversion data and user behavior to identify high-intent journeys. The model evaluates every visit in real time, scoring it on signals like:
- Active time spent on site
- Page and content engagement depth
- Product or service interactions
- Historical conversion patterns for similar users
Step 2: Synthetic Conversion Generation
When a non-converted user has a strong prediction to convert in the nearest future, SegmentStream generates a Synthetic Conversion with fractional value. The AI model evaluates the likelihood of a future purchase and assigns a conversion probability score. Visits with high incremental value trigger Synthetic Conversions that are instantly pushed to ad platforms.
vis_4E82Two models score each visitor: conversion probability × predicted value = fractional Synthetic Conversion. Only visitors above the 30% threshold trigger a signal.
Step 3: Ad Platform Signal Optimization
This signal is sent to Meta, Google, and LinkedIn via Conversions API (CAPI). The ad platforms use Synthetic Conversions to:
- Improve audience targeting by finding more users similar to high-value visitors
- Adjust bidding strategies based on real-time intent signals
- Scale upper-funnel campaigns that previously lacked conversion data
04.Amplify Smart Bidding with More Value Signals
While Synthetic Conversions don't equate to a final sale or closed deal, they are strong indicators of intent to complete a final conversion. Think of them as valuable visits — engagement patterns that statistically precede a purchase.
To give ad platforms as much conversion data to work with, you can use Synthetic Conversions as an amplification tool. Instead of training algorithms on a handful of weekly conversions, you feed them hundreds of calibrated intent signals — 10x more data points for smart bidding to learn from.
Synthetic signals carry fractional value — not full conversions.
The algorithm gets more data points to learn which clicks are valuable.
Without Synthetic Conversions, only 3 real conversions reach the platform from 1,000 clicks. With them, 10 additional fractional-value signals give the algorithm far more data to learn which clicks are valuable.
The result: ad platforms recognize high-value clicks faster, find more similar users, and scale campaigns that would otherwise be throttled by thin conversion data.
Same Instagram click, different outcome. Without Synthetic Conversions the platform kills the campaign. With them, it scales it.
05.Important Considerations
Synthetic Conversions are not real conversions
A Synthetic Conversion is not a sale. It is a valuable signal that tells ad platforms: find, target, and acquire more audience like this. The main aim is to ensure your ad campaigns can optimize and perform well when it's not possible to optimize for real tracked conversions alone — whether due to long sales cycles, cross-device journeys, or thin conversion volumes.
Better than clicks or random website events
Many advertisers optimize for page views, add-to-carts, or plain clicks when real conversions are too sparse. These signals have weak correlation with actual revenue. Synthetic Conversions are fundamentally different — they are trained on real purchasing behavior and validated for prediction accuracy. The model learns what genuine buyers look like and scores every visit against that pattern. The result is a signal that is far more meaningful to ad platform algorithms than any proxy event.
Only high-intent visitors trigger a signal
There is no need to send Synthetic Conversions for all visitors. Only a portion of visitors — those with genuinely high intent to convert — trigger a signal. Low-probability users remain as they are: non-converters. This keeps the signal clean and concentrated. Ad platforms learn the difference between a valuable click and noise, rather than being flooded with weak data points that dilute targeting quality.
Synthetic Conversions bridge the gap between what ad platforms can see and what actually drives revenue. They don't inflate your conversion count — they give the algorithm the signal it needs to do its job.
This whitepaper is best experienced on desktop. It includes interactive demos and data tables that show how the technology works. Send yourself a link to read later.