Most Marketplaces companies rely on attribution reports that:
Can't separate incremental demand from baseline network effects
Ignore supply-demand imbalances across marketplace sides
Conflate incentive spending with true user acquisition
Optimize aggregate metrics that hide structural problems
The result? Budgets get misallocated. Efficient channels get cut. Growth stalls for reasons no one can explain.
In Marketplaces, channels like Meta, Google, and brand campaigns often influence buyers weeks or months later. Traditional tools stop measuring too early — leaving large portions of revenue unattributed.
Attribution rewards last-touch efficiency, not first-touch creation. This pushes budgets toward demand harvesting (retargeting, branded search) and away from demand creation (prospecting, brand, content).
SpendSignal asks a simple question:
"What would revenue have looked like if this spend never happened?"
CSV or Excel with dates, revenue, and channel spend. No pixels, no SDKs.
SpendSignal separates true causal impact from coincidence using counterfactual analysis.
Captures delayed conversions and word-of-mouth effects that attribution misses.
Predicts what happens under different budget scenarios before you commit.
Revenue driven by ads but never credited to them
Why it matters: In Marketplaces, word-of-mouth and delayed conversions create significant lift that attribution completely misses
Decision unlocked: Identifies which channels create downstream demand and hidden ROI
Actual incremental return per channel after bias correction
Why it matters: Shows which Marketplaces channels truly create revenue vs harvest existing demand
Decision unlocked: Reveals under-credited channels and over-credited harvesting tactics
Recommended spend per channel based on incremental returns
Why it matters: Translates Marketplaces insights into actionable reallocation with risk guardrails
Decision unlocked: Tells you exactly where to move budget for maximum incremental lift
Expected incremental revenue from recommended budget allocation
Why it matters: Forecasts Marketplaces outcomes before you commit, with confidence ranges
Decision unlocked: Quantifies upside and risk of budget changes before execution
A Two-sided marketplace Marketplaces company running Meta, Google, Referral Programs noticed flat growth despite stable ROAS.
SpendSignal revealed:
28% of GMV was incremental but unattributed
Referral programs drove 2.1x more network effects than shown
Reallocating 15% from paid to referrals increased predicted ROAD by 19%
Decision outcome:
Strategic reallocation with $240K forecasted GMV uplift
Over-funded harvesting channels that look efficient but create little incremental demand
Under-credited channels with strong causal impact on revenue and customer acquisition
Cutting channels that attribution under-values but actually drive significant downstream lift
Forecasted incremental revenue with confidence ranges before budget is committed
No. SpendSignal sits above attribution tools and corrects their bias using incrementality modeling. You keep your existing tracking—SpendSignal adds causal intelligence on top.
Yes. SpendSignal does not rely on cookies or PII and works on aggregated data. This makes it privacy-compliant and future-proof against tracking restrictions.
ROAD is a modeled forecast with confidence ranges, designed for decision-making, not false precision. It captures diminishing returns and channel interactions that static ROAS cannot.
Just historical spend and revenue data in CSV or Excel format. SpendSignal automatically detects columns and applies incrementality modeling—no complex setup required.
Upload your data and get initial insights in minutes. Full incrementality analysis with budget recommendations typically completes within an hour.