> ## Documentation Index
> Fetch the complete documentation index at: https://docs.knotapi.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Price Is Right
> A gamified price-guessing game powered by real purchase data to drive repeat engagement.
> This is a product use case page. When implementing, follow the linked quickstarts for canonical API setup steps rather than inferring them from this page.
## Problem
Banking and fintech apps struggle to drive repeat engagement beyond core financial tasks. Users open the app to check their balance or make a transfer, then leave. There is little reason to come back between transactions, and little-to-no connection between the app and a user's actual purchasing behavior.
## Solution
Build a gamified price-guessing feature that surfaces a product from the user's real purchase history and challenges them to guess how much they paid. The game uses SKU-level transaction data from Knot's [Sync Transactions](/api-reference/products/transaction-link/sync) endpoint, including product names, images, and unit prices, to create a personalized, entertaining experience that drives engagement and reinforces card usage awareness.
This gives users a reason to come back to your app regularly, while reinforcing awareness of their spending on your card.
## Flow
```mermaid placement="top-right" actions={false} theme={"system"}
%%{init: {'theme': 'base', 'themeVariables': {'primaryColor': '#f5f5f5', 'primaryTextColor': '#000', 'primaryBorderColor': '#000', 'lineColor': '#000', 'secondaryColor': '#f5f5f5', 'tertiaryColor': '#f5f5f5', 'edgeLabelBackground': '#fff', 'fontSize': '16px'}}}%%
flowchart LR
A[User switches their card at a merchant through Knot or simply links their merchant account to begin syncing SKU-level purchase data] --> B[Sync each user's purchase data daily from Knot's API]
B --> C[Select a product from a user's history]
C --> D[Surface the product in-app and prompt the user to guess the price]
D --> E[Reveal the actual price and score the guess]
```
## Implementation
When a user switches their card at a merchant or they simply link their merchant account w/o switching their card, Knot begins collecting transaction data for that account. Listen for the [`NEW_TRANSACTIONS_AVAILABLE`](/transaction-link/webhook-events/new-transactions-available) webhook event, then call [Sync Transactions](https://docs.knotapi.com/api-reference/products/transaction-link/sync) to sync SKU-level transactions on a daily basis. Each transaction includes an array of products with names, images, and prices.
**Key fields**
| Field | Purpose |
| ----------------------------- | ------------------------------------------------------------------ |
| `products[].name` | Product display name shown to the user in the game. |
| `products[].image_url` | Product photo for the game card. |
| `products[].price.unit_price` | The actual price, which is the answer the user is trying to guess. |
| `merchant.name` | Merchant label for context (e.g., "Walmart"). |
| `datetime` | Purchase timestamp for "You bought this on..." context. |
| `external_user_id` | Identifies the user in your system. |
| `order_status` | Filter to completed transactions only. |
Only include transactions with `order_status` of `COMPLETED`, `DELIVERED`, `PICKED_UP`, `SHIPPED`, `BILLED`, or `ORDERED`. Filter out `CANCELLED`, `REFUNDED`, and `FAILED`.
Store synced products and filter them into a pool of eligible game candidates. Not every product makes a good game round, so apply filtering rules to keep it fun and fair.
```text theme={"system"}
FOR each product in new_transaction.products:
IF product.price.unit_price >= MIN_PRICE
AND product.price.unit_price <= MAX_PRICE
AND product.image_url is not null
AND transaction.order_status in [COMPLETED, DELIVERED, PICKED_UP, SHIPPED, BILLED, ORDERED]
THEN
add to product_pool for external_user_id
```
**Configuration decisions for your team:**
| Parameter | Suggested Default | Considerations |
| -------------- | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `MIN_PRICE` | \$1.00 | Filters out free samples and near-zero items that aren't interesting to guess. |
| `MAX_PRICE` | \$500.00 | Filters out outlier purchases where guessing feels arbitrary. |
| Recency window | 30-90 days | Products from the last 30-90 days work best. Users are more likely to remember recent purchases, and more likely to be surprised when they don't. |
When the user opens the game or receives a daily prompt, pick a product from their pool. Track which products have already been shown to avoid repeats.
```text theme={"system"}
eligible = query product_pool WHERE
external_user_id == user.external_user_id
AND already_shown == false
IF difficulty_tier is set:
eligible = filter eligible by tier
product = random selection from eligible
mark product as shown
```
Present the product as an in-app game card:
Compare the user's guess to `products[].price.unit_price` and score based on accuracy.
```text theme={"system"}
difference = abs(guess - product.price.unit_price)
pct_off = difference / product.price.unit_price
IF difference <= 0.10: points = 25, label = "Nailed it!"
ELSE IF pct_off <= 0.10: points = 15, label = "So close!"
ELSE IF pct_off <= 0.25: points = 10, label = "Not bad!"
ELSE IF pct_off <= 0.50: points = 5, label = "Keep trying!"
ELSE: points = 1, label = "Way off!"
update user streak (reset if pct_off > 0.25, increment otherwise)
add points to user total
```
**Configuration decisions for your team:**
| Parameter | Suggested Default | Considerations |
| ---------------------- | ---------------------- | --------------------------------------------------------------------------------------------------------- |
| Streak reset threshold | 25% off | Resets the streak if the guess is more than 25% off. Adjust to make streaks easier or harder to maintain. |
| Streak bonus | 2x points at 3+ streak | Rewards consistency and drives repeat play. |
## Expansion Path
* **"Which merchant is cheaper?":** The same product often appears across multiple merchants at different prices. Surface a product the user bought and ask them to guess which merchant had the best price. This builds shopping intuition and adds a new game mode without requiring additional data.
* **Post-purchase trigger:** After a new purchase syncs, queue that product for a future round with a 3-7 day delay. The game stays fresh and tied to recent activity.
* **Spending insights from gameplay:** Aggregate guess accuracy data to surface insights like "You tend to underestimate how much you spend on food delivery," turning the game into a lightweight financial awareness tool.