Competitive Intelligence from Credit Card Data
Analyze your named competitors using their credit card transaction data to:
- Know where to expand
- See where you’re losing customers
- Benchmark market performance
- Spot winning channel mixes
Get a Competitor Sales Data Demo
Use Your Competitor's Sales Data to:
Accelerate Expansion
- Size opportunity by category, region, or product using real sales data from named competitors
- Validate category or product demand with visibility into customer cross-shopping activity across specific competitors
- Evaluate target markets and de-risk site selection by analyzing competitor site performance
- Learn from successful or failed competitor expansions by monitoring their customer sales to see what worked and what didn’t
- Allocate capital to winning markets, channels, or categories based on real-world purchase behavior
- Identify underserved geographies where competitor presence is weak or declining but customer demand is strong
- Track competitor pricing & promo performance in near real-time to fine tune price, mix, and timing
Defend Share and Margin
- Identify which named competitors are winning your customers by tracking wallet drift
- Spot defection triggers and correlate them to specific competitor actions (promos, new sites, launches)
- Protect your loyalty base by watching competitor promo-driven shifts in trips, frequency, and AOV
- Defend local markets by modeling the impact of competitor openings, closures or daypart promos
- Focus win-back investments on truly recoverable customers by measuring active vs. inactive churned customers
- Identify at-risk, high-value customers by segment or geography based on cross-shopping behavior
Benchmark Competitive Performance
- Monitor and react to named competitor sales performance in near real-time (same store trends, frequency, channel mix basket size)
- Objectively measure competitor share gains and losses against actual category sales
- Generate board and investor-ready benchmarks based on competitor sales data, not industry reports or averages
- Spot performance gaps and opportunities with daily visibility into competitor sales data (frequency, basket size, retention)
- Explain comps correctly – split traffic vs. ticket, and quantify competitor discount intensity and returns drag
- Quantify the impact of competitors’ ecommerce, delivery, loyalty, membership programs and 3P distribution on share and comps
- Measure revenue cannibalization based on competitor moves
Competitive Customer Profiling
- Identify your highest value customer segments by looking at purchase behavior across your entire competitive set (by frequency, basket size, lifetime value)
- Spot underserved, yet high value, segments who spend heavily with your competitors
- Measure customer overlap by segment with specific competitors to uncover if everyone is fighting for the same wallet
- • Track customer segments your competitors win or lose with over time, and rapidly re-allocate resources toward stealing share with the right targets
- Track competitor discount depth, refund/return volume, and private label share
Optimize Channel Mix
- Maximize channel profitability based on your top performing competitors’ channel results (retail, ecommerce, 3rd party)
- Benchmark against competitor revenue by in-store, online, and omnichannel customer value
- Validate major investments across channels before committing capital, based on competitor sales ROI
- Identify markets or channels where competitors are underinvested but customer purchase demand is high
Evolve from market research to market truth.
$1.6T
Consumer spending
180M
Active card holders
5M
Stores
6y
History
1d
Delay
Facteus uses AI to summarize your competitor’s customer transactions and extract actionable competitive intelligence insights from them
Data Coverage
3,000+ Competitors
Over 47 Categories Covered
Strategic Leaders Start with Facteus
FP&A Leader in Top Retail Brand
"Facteus has transformed how our FP&A team forecasts, benchmarks and allocates - all based on competitive consumer transaction data."
Facteus data is trusted by:









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