A privacy-safe affordability index for advertising relevance—not income targeting, not credit scoring, not eligibility decisions.
Designed for relevance optimization and suppression. Not income targeting. Not credit scoring. Not eligibility decisions.
The AffordX index is continuously refreshed so deciles remain current as markets, seasonality, and consumer behavior change.
No data science team required. No bespoke modeling. Use category presets and apply the decile bid layer in minutes.
Start with a suppression-only pilot. Avoid heavyweight, multi-month data agreements and complex onboarding.
Outputs deciles + net-CPM-neutral bid multipliers. Clear actions: suppress, de-emphasize, neutral, emphasize.
Pilot without creative changes or channel shifts. If it doesn't work, you learn exactly where waste lives.
AffordX assigns impressions to affordability deciles based on probabilistic modeling of purchasing power and category fit.
This helps advertisers align their spend with audiences most likely to convert—without needing personal financial data.
The bid strategy is designed to shift distribution (suppress low-fit, emphasize high-fit) while keeping net CPM flat.
You don't inflate costs—you reallocate impressions toward better-fit audiences.
AffordX does not label users by income bracket or financial status. It's a relative, probabilistic index—not a demographic segment.
AffordX is not used for creditworthiness, underwriting, or lending decisions. It's strictly for advertising relevance.
AffordX does not determine access to credit, housing, employment, insurance, or public services. It's a marketing optimization tool.
Start from presets. Generate a plan. Apply exclusions and multipliers.
No custom modeling. No feature engineering. No complex pipelines.
30 days, one campaign, control vs. AffordX. Low risk, clear outcome.
AffordX is designed as a privacy-safe, relevance optimization layer for advertising. It does not enable discrimination, does not use sensitive personal financial data, and is not intended for use in regulated decision-making contexts.
For more on compliance and intended use, see About.