Mastercard Limitations in Spend Data
Understanding data availability and privacy constraints in Mastercard’s Geo Insights for Almanac
Overview
Almanac’s Spend data is powered by Mastercard’s Geo Insights — a sophisticated data service that provides granular views into sales and transaction patterns across geographies. However, due to strict privacy requirements, not all data points are always available. This article explains the limitations you may encounter and why certain data might be missing or suppressed.
How Geo Insights Works
Mastercard Geo Insights aggregates transaction data from Mastercard cardholders and merchant locations, then indexes that data across highly specific geographic areas called “quads” — as small as 150m x 150m in size. The platform offers metrics like total spend, number of transactions, average ticket size, and account activity, enabling retailers to benchmark performance over time and against broader market baselines.
Privacy Thresholds and Data Suppression
- No data is shown for areas (quads) with too few transactions, merchants, or cardholders.
- Highly granular levels (e.g., Zoom Level 18 — ~150m x 150m) are more likely to have suppressed data than broader levels (e.g., Zoom Level 15 — ~1.2km x 1.2km).
- Urban areas with low commercial density (e.g., residential blocks with few stores) are particularly prone to gaps.
Note: Mastercard does not publish data for a given quad unless it meets internal thresholds that protect individual anonymity and transaction obscurity.
How This Affects Almanac Users
- It's likely due to Mastercard’s privacy enforcement — not an issue with data quality or errors.
- Aggregated views (e.g., neighborhoods or zip codes) may still include adjacent quad data to maintain usefulness while preserving compliance.
- In some cases, data from neighboring quads is lightly weighted and blended to offer a relative sense of performance without violating privacy thresholds.
Best Practices for Interpretation
- When zooming in, expect occasional data gaps — especially in low-traffic commercial areas.
- Treat extreme dips or absences in the data as signals of insufficient volume, not necessarily actual business decline.