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Overview

The Data Warehouse Ingestion Module allows you to push selected loyalty data directly into your own data warehouse. This enables you to combine Gameball data with data from other business systems and analyze everything in one centralized analytics environment. This feature was designed primarily for you if you already rely on internal dashboards and BI tools (such as PowerBI, Metabase, or similar) for daily reporting and decision-making. Instead of building and maintaining analytics separately inside each tool, businesses can centralize their data in a data warehouse and build unified dashboards across all systems.

Why This Feature Exists

Most large organizations already store their operational data in a data warehouse, which acts as a single source of truth. Data from multiple systems—such as order management, inventory, CRM, and communication tools—is pushed into the warehouse and then consumed by analytics tools. With the Data Warehouse Ingestion Module, Gameball becomes part of this ecosystem. You can now:
  • Combine loyalty data with revenue, inventory, and customer communication data
  • Build cross-system dashboards in one place
  • Run advanced analysis without relying solely on Gameball’s in-dashboard reports

How You Typically Use It

A common setup looks like this:
SystemData Pushed
Order / POS system (e.g. Microsoft Dynamics)Revenue and order data
Inventory management systemStock and product data
Customer engagement platform (e.g. Braze)Communication and campaign data
GameballLoyalty and rewards data
All of this data is stored in the data warehouse, and an analytics tool (such as PowerBI or Metabase) reads from it to create dashboards. This allows you to answer questions like:
  • How does revenue trend by loyalty tier?
  • How many points were earned from completed orders?
  • What is the distribution of customers across tiers?
  • How do loyalty actions correlate with repeat purchases?

Available Gameball Data Models

Gameball currently provides four built-in data models that can be pushed to a data warehouse. You can choose which models to enable during setup.
Contains customer-level loyalty data. Useful for segmentation, tier analysis, and customer-level reporting.
FieldDescription
customer_unique_idCustomer identifier from the client’s external system, used for integration and mapping
display_nameCustomer’s display name as shown in the loyalty program interface
is_migrateInteger flag indicating if this customer was migrated from another system (1 = migrated, 0 = native)
referred_by_unique_idCustomer identifier of the person who referred this customer, if applicable
referral_activation_dateDate when the customer’s referral was activated and confirmed
is_referred_customerInteger flag indicating if this customer was referred by another customer (1 = referred, 0 = not referred)
current_tier_nameCurrent loyalty tier name the customer belongs to
current_tier_orderCurrent loyalty tier order the customer belongs to
customer_pointsCurrent number of loyalty points the customer has available for use
total_earned_pointsThe lifetime amount of points that the customer have earned
total_redeemed_pointsThe lifetime amount of points that the customer have redeemed
total_expired_pointsThe lifetime amount of customer’s points that have been expired
customer_scoreCurrent customer score (frubies) value the customer has accumulated
customer_pending_pointsPoints that have been earned but not yet activated or confirmed for the customer
tier_entry_dateDate when the customer entered their current loyalty tier
customer_typeCustomer lifecycle state: Registered (full customer profile) or Guest (limited profile)
is_includedInteger flag indicating if the customer is included in active program participation
created_atDate when the customer record was created in the Gameball platform
updated_atDate when the customer record was last updated
is_deletedIndicates if this is a deleted row
Represents all points and order-related movements. Use this model to analyze how points are earned and spent over time.
FieldDescription
gameball_transaction_idUnique identifier for the transaction
transaction_idUnique identifier for the transaction in the client system
customer_unique_idIdentifier of the customer who did the transaction
merchant_nameThe merchant name where this transaction happened
branch_nameThe branch name where this transaction happened
transaction_typeThe type of the transaction: cashback, redemption, expiry, etc.
directionThe direction of the points transaction: + or -
tier_nameThe name of the tier the customer was on when this transaction happened
tier_orderThe order of the tier the customer was on when this transaction happened
points_amountThe amount of points in the transaction
points_used_amountThe amount of points that has been used from this transaction (for positive transactions only)
redemption_factorThe factor used to calculate the value of points
points_valueThe monetary value of the points at the time of the transaction
transaction_statusThe status of the transaction: active or pending (for positive transactions only)
points_expiry_dateThe date when the points will expire (for positive transactions only)
created_atTimestamp when the transaction record was created in Gameball
updated_atTimestamp when the transaction record was last updated in Gameball
is_deletedIndicates if this is a deleted row
Includes all loyalty events and campaign-related actions such as reward campaigns, referrals, and tier progressions. This data closely matches what is available in Gameball’s activity logs and reports.
FieldDescription
gameball_achievement_idUnique identifier for the achievement event
customer_unique_idIdentifier of the customer who earned the achievement
achievement_typeBroader grouping of the achievement type (e.g., Level, Campaign, Referral, Transaction, Manual)
achievement_sub_typeDetailed classification such as Level, Challenge, Milestone, Quest, Referral, Purchase Reward, Manual action
campaign_nameIdentifier of the campaign associated with the achievement event
is_coupon_rewardedIndicates whether a coupon was issued as part of the achievement
current_tier_nameCustomer’s current tier name at the time of achievement
current_tier_orderCustomer’s current tier order at the time of achievement
achieved_tier_nameThe name of the tier reached by the customer if achievement type is related to tier progression
achieved_tier_orderThe order of the tier reached by the customer if achievement type is related to tier progression
achieved_pointsNumber of points earned from this achievement event
points_valueMonetary equivalent of the achieved points in the client’s currency
achieved_scoreScore gained from this achievement (if the leveling method is based on score)
created_atTimestamp when the achievement record was created in Gameball
updated_atTimestamp when the achievement record was last updated in Gameball
is_deletedIndicates if this is a deleted row
Contains coupon assignment data with lifecycle status, discount amounts, and usage metrics. Supports reporting on reward redemption and coupon usage.
FieldDescription
gameball_unique_idUnique identifier for each coupon per customer per assignment
coupon_codeThe actual coupon code that customers use to redeem the offer
customer_unique_idIdentifier of the customer who received this coupon assignment
coupon_typeCoupon discount mechanism: Fixed, Percentage, Free Shipping, Free Product, Store Credit, etc.
coupon_sourceSource usage context: Online, POS, Permanent, Reward Campaign, or Automation
coupon_sub_sourceOrigin of the coupon creation: Campaign, Reaching a Tier, Referral, or Automation
amountDiscount amount — for fixed types this is the actual discount amount; for percentage types this is the percentage value
total_paid_amountTotal monetary value across all orders where this coupon was applied (only for used coupons)
total_order_countTotal number of orders where this coupon was applied (values > 1 indicate multiple uses if multi-use enabled)
current_stateCurrent lifecycle status: deleted, expired, used, or assigned (default)
created_atTimestamp when the coupon was originally created
updated_atTimestamp when the coupon was last updated
is_deletedIndicates if this is a deleted row

Example Use Case

You may want to build a dashboard showing:
  • Revenue from your order management system
  • Points earned from those same orders (from Gameball)
By joining order data from your POS system with transaction data from Gameball inside the data warehouse, you can create a single dashboard that visualizes both revenue and loyalty performance together.

How to Set Up the Integration

1

Open Data Warehouse Integration

Go to Admin Settings in the Gameball dashboard, then navigate to Data Warehouse Integration and click Set Up Connection.
Data Warehouse Integration
2

Select Data Warehouse Provider

Choose your data warehouse provider (for example, Amazon Redshift), then click Next.
3

Add Connection Details

Enter the required account and connection details, then click Next.
4

Define Data Push Frequency

Choose how often Gameball should push data:
  • Daily
  • Weekly
  • Monthly
You will also define the exact time (for example, daily at midnight).
Higher frequencies come with higher costs.
5

Select Data Models

Choose which Gameball data models you want to push: Members, Transactions, Achievements, or Coupons.
6

Submit Request

Once submitted, the request is sent to Gameball’s technical team.

What Happens After Submission

The connection is not established automatically.
StageDetail
Initial submissionActs as a configuration and request flow
Technical setupGameball’s technical team manually completes the integration
Connection liveStatus changes to Connected
Ongoing pushesEach scheduled push appears in the dashboard with its status and details
After the connection is live, each scheduled data push (daily, weekly, or monthly) will appear in the dashboard with its status and details.

Availability & Enablement

The Data Warehouse Ingestion Module is offered as an add-on.
1

Enable the Feature

The feature must be enabled on your account before use.
2

Coordinate with Your CSM

You should coordinate with your Customer Success Manager to start the implementation process.