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‹Card Data

Card Rewards

The rewards program behind any card: earn rates, category bonuses, redemption value.

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At checkout
Which card should they pay with?
Dining order
$248.00
1
Sapphire Reserve
3× points on dining
Point value
2.0¢ / pt
Worth
$14.88
Recommend this card
2
Bonvoy Bevy
4× points on dining
Point value
0.8¢ / pt
Worth
$7.94
3
Everyday Debit
No rewards
Point value
-
Worth
$0.00
Normalized earn rules4×Dining4×Supermarkets6×Hotel stays2×Everything else
Point valuations are editable assumptions, not issuer values.

The same order. Two very different outcomes.

A shopper reaches for whichever card is on top. Without rewards data you cannot tell them they just left money on the table.

Card picked at random
Everyday Debit
No rewards
Earned
$0.00
No reason to reach for a better card
Rewards-driven spend goes to a rival wallet
No signal to build offers or loyalty on
→
Best card recommended
Sapphire Reserve
3× points on dining
Earned
$14.88
A concrete reason to pay with the better card
Rewards-driven spend stays in your checkout
Program data to power offers and loyalty

Rewards are the cheapest nudge in your checkout.

You are not changing price or adding a discount. You are telling the shopper something true about the card already in their wallet.

Bigger baskets
A shopper told they earn 3× on this order has a concrete reason to spend more of it here.
You win the top-of-wallet slot
Rank the wallet by real value and the best card gets picked, in your checkout, not a rival one.
Repeat spend compounds
Reward-aware checkout is a reason to come back, and loyalty is cheaper than acquisition.
Redemption stops being abstract
Show what a point is actually worth and the offer finally lands.
Offers that match the program
Target promotions at the tiers and categories a cardholder already earns on.
One shape for every program
Wildly different issuer rules arrive normalized, so your checkout logic never forks.

Every place a card choice is worth influencing.

One rewards profile feeds checkout, loyalty, product and issuing teams alike.

Checkout
Move the card choice at the moment of payment
01
Best-card nudge
Recommend the card that earns most on this basket.
02
Wallet ranking
Order stored cards by what they are actually worth.
03
Earn preview
Show the points this purchase will generate before they pay.
04
Category-aware routing
Detect dining, travel or grocery and apply the right multiplier.
Loyalty & offers
Target what the cardholder already earns on
01
Tier-matched promotions
Aim offers at the programs and tiers a shopper holds.
02
Redemption clarity
Translate points into money so the offer means something.
03
Bonus-category campaigns
Run campaigns timed to rotating quarterly categories.
04
Win-back on lapsed cards
Re-engage a wallet whose best card has gone unused.
Product & apps
Build rewards into the product itself
01
Card-recommendation engine
Rank a whole catalog for a shopper’s spending profile.
02
Personal finance insights
Explain rewards earned and missed per purchase.
03
Subscription card picker
Pick the best card for a recurring charge automatically.
04
Agent-led purchases
Give an AI agent the rules it needs to choose a card.
Issuing & growth
Prove your card is the one worth carrying
01
Competitive benchmarking
See how your earn rates rank against the market.
02
Acquisition targeting
Pitch prospects whose spend your program would beat.
03
Top-of-wallet analytics
Track when your card wins and when it loses.
04
Program design
Model a multiplier change against real category rules.