Research and evidence

A lift is not proof. The decision, comparison, and limits matter.

Behavioral context creates value only when it changes a product decision in a way that can be measured. This is Fluence's public framework for evaluating that incremental impact without turning a promising signal into an unearned claim.

Evidence

What we can say publicly

A Fluence partner pilot integrated behavioral context into existing systems across 3.4 million profiles. The deployment reported a 40% churn reduction, a 2.3x conversion lift, and a 3.5x improvement in ML model accuracy, with integration completed in under 10 hours.

3,4M

profiles processed

−40%

churn

2,3x

conversion

3,5x

ML accuracy

<10h

to integrate

These are reported outcomes from one specific pilot, not the result of a published controlled study or a guarantee for another product, sector, or user base. Customer-level raw data and detailed measurement materials are not public.

Read the pilot case studyRead the measurement article

Method

The measurement framework

Five steps to turn a behavioral signal into a decision that can be measured.

  • 01Name the decisionChoose the specific action behavioral context can change: timing of a support handoff, a checkout response, a recommendation, or an agent's level of autonomy.
  • 02Define the comparisonCompare the changed decision against a credible counterfactual. A before-and-after chart alone cannot show that context caused the outcome.
  • 03Measure outcomes and guardrailsTrack the intended result alongside corrections, reversals, escalations, time to complete, voluntary reuse, and downstream retention.
  • 04Log the interventionRecord who was eligible, what context was available, which action changed, the confidence level, and the outcome window.
  • 05Decide with limitsScale only when the incremental benefit is clear and guardrails remain healthy. A signal without a testable decision is not evidence of impact.

    • Evidence without overclaiming

    Fluence does not publish or require private interaction content. Any partner evaluation should use the minimum behavioral signals needed for the defined decision, with an explicit evidence window, confidence levels, and action boundaries. Results should describe the population, comparison, outcome window, and limitations.

    Security and privacy

    FAQ

    Frequently asked questions

    Are the pilot results a guarantee?

    No. They are reported outcomes from one deployment. Different products, interventions, populations, and measurement methods can produce different results.

    Does Fluence publish raw customer data?

    No. Customer-level data and private interaction content are not public research materials. The public framework explains how a partner can measure an implementation responsibly.

    What should a first pilot measure?

    Start with one decision and one primary outcome, then add a small set of guardrails. The comparison should make clear what would have happened without the behavioral-context intervention.

    How were the pilot results measured?

    They are outcomes reported by the partner deployment, not by a published controlled study. Detailed measurement materials and customer-level data are not public.

    What kind of comparison is acceptable?

    A credible counterfactual, such as a control group that doesn't receive the context-based intervention. A before-and-after chart alone cannot show that context caused the outcome.

    How long should a pilot run?

    It depends on the decision and traffic volume. What matters is defining the outcome window before starting, long enough to observe the primary outcome and the guardrails.

    Which guardrails should I track?

    Beyond the intended result: corrections, reversals, escalations, time to complete, voluntary reuse, and downstream retention. In e-commerce, also include the cost of interventions, such as discounts given.

    Start with one decision and an honest measure of impact.

    We'll design a pilot with you, with a defined comparison, guardrails, and outcome window.

    Design a measurable pilot