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Spend Personality
The Spend Personality algorithm gives you dynamic behavioral profiles for every customer using AI and behavioral science—so you can curate engagements, recommendations, and products tailored to individual needs, with greater precision than demographics or static segments alone.
Enrich transactions into personality scores, act on them in real time, and refine continuously as behavior shifts—without abandoning your existing decisioning stack.
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Each customer receives a blended score across every dimension—not a single label—so profiles stay nuanced as behavior changes.
Action-oriented connectors who respond to momentum, interaction, and socially driven experiences.
Curious explorers who engage through discovery, interaction, and real-world experiences.
Deliberate decision-makers who seek depth, clarity, and control before taking action.
Independent thinkers who prefer self-guided journeys, thoughtful exploration, and minimal pressure.
Efficiency-driven planners who value structured, goal-oriented paths to the best outcome.
Socially driven participants who thrive on connection, energy, and shared engagement.
Business value
Move the metrics that matter—acquisition, engagement, revenue, and retention—with personalization grounded in how people actually spend.
Ensure every message, recommendation, and offer stays individually relevant, so customers consistently experience value and remain engaged over time.
Use existing personality profiles and behavioral patterns to guide outreach, helping you engage new customers with relevant, contextual messaging from the very first interaction.
Deliver tailored recommendations and messages for each personality type, naturally encouraging meaningful action and reducing friction at key decision moments.
Example use case
Banks often hold large portfolios of credit card customers who never activate or use their cards after issuance, creating ongoing costs with no revenue return.
Used in combination with solutions such as Digital Personality and Intelligent Sales, Spend Personality helps determine the optimal activation strategy—guiding the right offer or nudge, message framing and tone, and the best timing for engagement, to align with behavioral archetypes.

Trusted by industry leaders
Configure and deploy through the platform’s modular architecture: define data inputs, scoring triggers, and downstream actions from the Workbench with low-code workflows. Once live, the prediction server ingests transaction data in real time, computes personality scores, and returns outputs to recommenders, experiments, journeys, or CRM tools. Deploy on major clouds or private environments using packaged containers; monitor with your existing observability stack.
Architecture

Modular prediction server, workbench configuration, and REST-style score delivery—mirroring the deployment story on the Spend Personality algorithm overview.
Expose scores through standard APIs to recommenders, experiments, journeys, and CRM workflows
Ensure personality profiles are up-to-date, enabled by real-time dynamic experimentation and online learning.
Use Spend Personality Algorithm to enrich transactional data with behavioral insights.
Developer resources
Read our documentation or get started with our Quick Start Guides on our developer site.
Quick answers derived from the same product story as the rest of this page.
You can identify a customer’s financial motivation by analyzing their spending behavior — including categories, frequency, and transaction value. These inputs are scored using models like Spend Personality, which evaluates behavior across six core dimensions to reveal underlying motivations and decision patterns.
Spend Personality is a behavioral analytics model that uses customer spending data to generate personality scores. These scores reflect how individuals make financial decisions, enabling more accurate segmentation and personalized engagement than demographic-based approaches.
The six Spend Personality types group into two families: Extrovert, Experiential, and Enthusiastic (E); and Intentional, Introvert, and Industrious (I). Rather than assigning a customer to a single type, each individual receives a blended score across all six dimensions, creating a more nuanced and accurate behavioral profile.
Spend Personality scores are used to create a “segment-of-one” for each customer by assigning a unique behavioral profile. These scores can then power real-time use cases such as personalized recommendations, targeted messaging, and more effective human-to-human interactions.
The best alternative to demographic segmentation is behavioral segmentation based on individual customer data. Instead of grouping people by age, gender, or location, behavioral approaches analyze how each customer actually spends, interacts, and makes decisions. One example is Spend Personality, which segments customers using real spending behavior rather than demographics. This creates “segments of one,” enabling far more accurate targeting and true hyper-personalization.