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GrowthLoop Launches Composable AI Decisioning Platform — PR Newswire (April 2026)

GrowthLoop announced Composable AI Decisioning on April 15, 2026. The platform adds three capabilities: (1) Decisioning Node — real-time channel and offer allocation within marketer-defined journeys, automatically adjusting toward options that drive stronger outcomes; (2) Always-On Lift Measurement — continuous incremental impact tracking across marketing activities; (3) Agentic Context Graph — a causal knowledge base that learns which marketing decisions actually improve key outcomes like revenue or lifetime value, compounding over time. Unlike correlation-based AI decisioning, it uses causal measurement. Runs natively on BigQuery and Snowflake without copying or moving data. Named enterprise customers: Costco, Albertsons, Ford. Founded by former Google executives. G2 Momentum Leader.

prnewswire.com — view original source
confidence 75%v1published April 2026indexed May 12, 2026growthloop, composable-cdp, composable-ai-decisioning, agentic-cdp, bigquery, snowflake, lift-measurement, causal-ai, warehouse-native, 2026, compound-marketing-engine

GrowthLoop Launches Composable AI Decisioning Platform — April 2026

Announcement date: April 15, 2026
Source: PR Newswire (wire service distribution of vendor press release)

Composable AI Decisioning — Three Capabilities

1. Decisioning Node
A node within GrowthLoop's Universal Journey builder that performs real-time channel and offer allocation. Within marketer-defined customer journeys, the Decisioning Node automatically allocates customers across channels, offers, and tactics, adjusting in real time toward options that drive stronger results (e.g., revenue, LTV).

2. Always-On Lift Measurement
Continuous incremental impact tracking across all marketing activities. Unlike point-in-time A/B tests, Always-On Lift Measurement tracks the causal impact of every marketing decision on key outcomes continuously and feeds learnings back into the decisioning model.

3. Agentic Context Graph
A causal knowledge base built natively on the data cloud. Unlike traditional AI decisioning tools that rely on correlative data, black-box models, or disconnected systems, the Agentic Context Graph uses causal measurement and compounds learning over time without copying data or locking teams into specific channels.

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