Synthetic data is a powerful tool and we use it together with direct audience interaction. Initial and periodic surveys (whether directly fielded, purchased from panel providers, or taken from holistic industry data) still matter, especially when market conditions change.

We strategically incorporate synthetic data where it provides the most value and confidence in results.

Our experts will discuss any use of synthetic data with you to ensure maximum understanding and confidence in your results.

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Why We Use Synthetic Data

Motivational data is powerful, but collecting it exclusively through surveys can create operational overhead and respondent fatigue especially when dealing with niche segments or repeat engagements.

Apex leverages synthetic data to reduce the burden on your audience while preserving the richness of motivational intelligence. By generating modeled motivational responses based on existing patterns, Apex ensures your models stay fresh, responsive, and scalable even in the absence of new survey data.

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How Synthetic Data Is Created

We follow a rigorous process that respects both behavioral science and data fidelity:

1

Seed from Real Responses

Depending on your needs and the data you have available, the learned motivational patterns used by our synthetic generators can begin from any combination of:

  1. Your zero-party Apex survey data
  2. Purchased survey sample for your brand (e.g. from a panel provider)
  3. Holistic industry data (e.g. from a panel provider, Apex’s own industry datasets)
2

Connective CRM Data as Inputs

We enhance motivational assumptions using CRM-linked behavioral, transactional, and demographic signals. These “connective” data points act as bridges allowing our models to predict motivational patterns.

Example:

For illustration only. Actual data fields can vary by client and use case.

From your CRM, you provide us 20,000 ≤ n ≥ 1,000 customer-level attributes such as:

  • Segment ID
  • Tenure
  • Gender
  • Age
  • Income
  • Location
  • Product List
  • Any open-ended customer feedback/support details

See our PRIZM integration as another possible example of a strong connective data link that can connect your CRM data to the motivational profiles of your audiences.

We do NOT require any connective data to include sensitive information/PII.

3

Simulation and Expansion

We find motivational patterns from the seed data from step 1 and model motivational patterns of those (n) people with the same combinations of connective data (i.e. 45-55 females in San Francisco having 3 products…) from step 2.

We append predicted motivational responses to the connective data you provided to create a synthetic dataset.

This can include simulated motivational responses for under-sampled segments or edge-case scenarios, ensuring strategic coverage across your full customer base.

4

Validation and Guardrails

All synthetic outputs are cross-tested against real outcomes to ensure statistical plausibility and business relevance. We prioritize consistency with known data and limit overextension.

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Benefits of Synthetic Data

  • Reduces Audience Fatigue and Overhead
    Eliminates the need for constant surveying, which can lead to drop-off or disengagement.

  • Extends Coverage
    Predicts motivations across segments that may not be directly sampled, helping deliver guidance across your full customer base.

  • Accelerates Planning
    Enables Apex to generate next-best actions and predictive models without waiting on survey cycles.

  • Preserves Privacy
    Ensures anonymized, non-PII signals for safe and ethical extrapolation. Never generating synthetic individuals, only motivational profiles tied to real business contexts.

  • Strengthens Strategic Confidence
    Allows for “what-if” testing across potential interventions, helping validate options before full deployment.

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Limitations (and Why They Don’t Break Value)

While synthetic data enhances scalability and speed, it has reasonable constraints:

  • Synthetic motivational profiles are only as strong as the real data they’re trained on. That’s why we periodically refresh them with live responses to avoid drift.

  • Synthetic expansion enriches and amplifies the valuable insights gained from direct audience interaction. This is why we always include some element of zero-party motivational measurements.

  • Synthetic data generation assumes stability in key relationships between motivation and behavior. We monitor for deviation and tune models accordingly to stay anchored in truth.

These boundaries are by design. They keep synthetic modeling useful without overstating certainty ensuring our clients act with confidence, not assumption.

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Where It Fits in the Apex Stack

In all use cases, synthetic data lets Apex act with greater speed and specificity, continuously evolving alongside your customer landscape.

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MotiveModel

Synthetic data can play a role in MotiveModel to remove or reduce requirements for motivational measurement via survey if the right training data is available.

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MotivePath

Synthetic data can enhance MotivePath’s analytical pipeline by training models with a more robust foundation.

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MotiveLoop

Synthetic data plays the largest role in MotiveLoop, our embedded intelligence layer. It helps to:

  • Refresh and retrain motivational models with maximum accuracy without exhausting audiences
  • Fill gaps when CRM segments are too small to sample
  • Test strategic interventions in sandboxed environments before live rollout