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The New Data Usage category addresses how to leverage non-traditional data sources — proprietary scores, live-collected preferences, and declared interests — to enhance personalisation beyond static segmentation.

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Key Challenges in this Category

Proprietary Scoring Data Usage

Common to all Use Cases. Leverage scoring data from in-house algorithms — for example, integrating a proprietary anti-churn score to prioritise high-risk customers on reactivation communications, displaying their score vs another profile to decide the level of promotional aggressiveness. Fresh contextual data outperforms static segmentation.Connected Use Cases: 3

Intent & Preference Qualification

Dynamically identifying purchase intent and individual preferences to refine personalisation. Declarative data collected via Live Polling enriches customer knowledge and improves relevance.Connected Use Cases: 3

Preference & Interest Collection

Encouraging preference sharing through interactive mechanics to enrich the customer profile and improve personalisation. The richer the customer data, the more relevant and effective the personalisation.Connected Use Cases: 3

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Connected Use Cases

Use CaseRole in new data challenges
Live PollingCollects declared preferences and qualifies audiences in real time
Enriched Product RecommendationLeverages preference data for more relevant recommendations
1:1 Personalised DigestCombines multiple data sources into a fully personalised email

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Required Datasources

DatasourcePrimary usage
CRM 360Proprietary scores, customer attributes
Workflow EventsLive Polling responses, interaction history
NavigationBrowsing behaviour, viewed categories
Product ReviewsProduct affinities from review patterns

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Key Principle

Static segmentation creates a snapshot that decays over time. By integrating fresh, contextual data — scores computed daily, preferences declared last week, navigation from this morning — personalisation stays relevant and responsive to individual evolution.