Top Alternatives to Affinity for Transaction Data in 2025

Key Highlights:

Use Cases by Function

7 Key Selection Criteria

Affinity provides transaction data primarily sourced from debit and credit card users. It’s widely used in performance marketing and rewards programs, particularly where targeting upscale audiences is the priority. However, teams seeking full-wallet coverage, broader demographic representation, or data extensibility beyond marketing analytics may find Affinity’s scope limiting.

This guide evaluates Affinity’s performance and shows when Facteus may be a better fit.

Why Teams Replace Affinity

Organizations typically expand beyond Affinity when looking for a broader view into all consumers vs reward and loyalty enthusiasts.  Common friction points include:

  • Limited visibility into, prepaid, or commercial card spend
  • Demographic skew toward users of reward/mileage programs or loyalty
  • Limited product or store-level resolution

Collectively, these limitations result in an incomplete picture of consumer behavior. With limited visibility into all American demographic types, teams lack a full 360-degree view of wallet and market share. The absence of product-level data prevents analysis of basket composition, product-level substitution, or promotional impact—critical inputs for some retail strategy, pricing optimization, and forecasting models.

Comparing Affinity Alternatives

Facteus
Alternative Providers (Affinity)
Receipt Panels
Survey Data
Mobile Location Data

Data Source

Includes sales transactions, surveys, GPS

Sales Transaction

Sales Transaction

Sales Transaction

Survey

GPS, cell tower ping

Retailer Breadth

5M physical locations

1M online retailers

uknown

44k physical locations

NA

Similar

Consumer Breadth

180M active cardholders

150M cardholders (~50M active)

1M receipt panelists

500-1000 panelists

Large

Consumer Depth

Includes demos, affinities, cross-shopping

Good

Good

Good

Good

Mediocre

Transaction Depth

Includes store vs. UPC

Store, UPC

Store

UPC

Can be product level

Store

Time Granularity

Includes day part, day, week

Good

Good

Good

Poor

Good

Speed

<48hrs

Typically >5 days

Typically >7 days

Slow

7-21 days

Custom Questions

NA

Sometimes an add’tl service

Sometimes an add’tl service

Yes

NA

Facteus

Facteus provides real transaction data across 185M+ cards—including credit, debit, prepaid, and commercial sources—with a 1-day lag and UPC/store-level fidelity. Its data is fully synthetic and statistically rebalanced, offering clean demographic coverage across income tiers, regions, and purchase types. This structure minimizes compliance risk while maximizing data utility.

Unlike Affinity, Facteus supports raw data delivery, API access, and flexible integration into BI tools or ML workflows. It is used by hedge funds, FP&A teams, and product analysts alike to power decision automation, competitive benchmarking, and spend modeling. While Affinity remains strong in performance marketing use cases, Facteus extends well beyond that domain.

Who Should Switch From Affinity—and Why

Use Case
Affinity Limitation
Facteus Advantage

Granular modeling

Merchant and demographic views

UPC, store, and demographic views

Compliance + procurement

PII exposure, loyalty-only sourcing

Synthetic, PII-free, enterprise-safe

Final Take

Affinity continues to be a valuable solution for marketing teams focused on loyalty audiences and high-level trend analysis. Its structured approach and stable merchant metrics support a range of activation and targeting strategies. However, for organizations seeking real-time signals, full-wallet modeling, or integration into operational systems, complementary or alternative providers like Facteus may offer more flexibility and analytical depth.

Facteus provides multi-source coverage, granular metadata, and enterprise-ready infrastructure that broadens what teams can build and benchmark. Choosing between these platforms depends on your specific goals—campaign targeting versus strategic forecasting, signal breadth versus precision, and static reporting versus dynamic integration.

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