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Behavioral Signals Design
Behavioral Signals Design is our proprietary method for building more predictive KPIs. It locates the conversion points and behavioral types hidden in noisy, siloed data, exposes untested assumptions, and turns them into hypotheses and experiments.
The problem behind the problem.
Most organizations measure what is easy to count rather than what predicts the outcome they care about. Revenue, enrollments, churn and satisfaction scores arrive after the fact, when the behavior that produced them is already finished. Meanwhile the early signals sit scattered across a CRM, a product database, a call center platform, a scheduling tool and a survey vendor, each owned by a different team and keyed to a different identifier. No one can see the whole journey, so no one can see which moments in it actually matter.
Into those gaps flow assumptions. A sales team believes a demo drives purchase. A product team believes a feature drives retention. A clinical team believes reminders drive adherence. Some of these beliefs are correct, and some are expensive guesses that have never been tested. Because the assumptions are invisible, they shape budgets, staffing and roadmaps without scrutiny. Behavioral signals design exists to make those assumptions visible, test them against the data, and replace the ones that fail with measures that genuinely predict performance.
How we deliver behavioral signals design.
- 01Observe
Anchor on the outcome and the journey
We start by agreeing on the single outcome that matters most, such as conversion, adoption, retention or adherence, and defining it precisely enough to measure. Through stakeholder interviews, contextual inquiry and journey mapping we document every step people take toward or away from that outcome, plus every system that records those steps. We also capture the working beliefs each team holds about what drives results.
- 02Signal
Find conversion points and behavioral types
We integrate data across siloed systems, resolve identities, and build an event-level view of the journey. Using cohort analysis, survival analysis and sequence modeling, we identify the few conversion points where trajectories diverge and the behavioral types that move through them differently. Each candidate signal is tested for lead time, stability across cohorts and whether a team can actually influence it.
- 03Design
Turn assumptions into hypotheses and KPIs
We place each untested assumption beside the evidence and rewrite it as a falsifiable hypothesis. Signals that survive become predictive KPIs with clear definitions, owners, thresholds and refresh rates. For each KPI we use the Fogg Behavior Model to diagnose whether motivation, ability or a missing prompt is the constraint, then specify the intervention most likely to move it.
- 04Test
Run focused A/B tests and pilots
Every hypothesis gets an experiment plan before anything is built: the primary metric, a minimum detectable effect, a power calculation, guardrail metrics to catch harm, and stopping rules. Where randomization is impractical we design staged pilots or matched comparisons. Results confirm which KPIs truly lead the outcome and which interventions move them, and which assumptions should be retired.
- 05Scale
Embed the signals in decisions
Validated KPIs move into operating rhythms: decision dashboards, weekly reviews, alert thresholds and team goals. We document the data pipeline so it survives staff changes, coach leaders on interpreting leading indicators without overreacting to noise, and set a cadence for retesting as markets and behavior shift. The method becomes a capability your teams can run themselves.
Deliverables.
What changes.
Who engages us.
Behavioral signals design serves chief executives, chief growth and marketing officers, product leaders, heads of analytics and operations, and health system and association executives. It suits organizations with plenty of data but little confidence in which numbers to manage, often after a merger, a platform migration, a stalled growth plan or a board request for better forward-looking metrics. Private equity sponsors also use it to establish predictive KPIs in a new portfolio company.
Industries
Beyond the balance sheet.
Predictive KPIs built on real behavior benefit more than the income statement. Customers and users encounter fewer dead ends because friction is found and fixed early. Patients and members receive support at the moment it helps rather than after they disengage. Employees are measured on behaviors they can influence, which is fairer and more motivating. And because the method replaces guesses with evidence, scarce resources in health, education and community programs go further toward the people they are meant to serve.
Frequently asked questions.
How is behavioral signals design different from a standard analytics engagement?
A standard analytics engagement usually starts with the data and describes it. Behavioral signals design starts with the outcome and the human behaviors that produce it, then looks for the specific moments and behavioral types that predict it. It also treats untested assumptions as first-class objects to be tested. The end product is not a report but a short list of predictive KPIs, each linked to a hypothesis and an experiment.
What if our data is spread across systems that have never been integrated?
That is the normal starting point. We map each source, define the identifiers and timestamps that can link them, and build an integrated event-level view of the journey, often in a lightweight analytical environment before any permanent infrastructure is changed. Where linkage is imperfect, we quantify the gaps and design around them, and we recommend the minimum data changes needed to keep the signals reliable.
How do you know a signal is truly predictive and not just correlated?
We look for lead time, consistency across cohorts and time periods, and a plausible behavioral mechanism. Survival and cohort analysis show whether the signal precedes the outcome. Holdout periods check whether it predicts out of sample. Ultimately, the strongest evidence comes from experiments: if changing the behavior changes the outcome, the signal is a genuine lever rather than a coincidence.
How long does a behavioral signals design engagement take?
Timing depends on the number of systems involved, data access and the complexity of the journey. A focused engagement on one outcome and one journey typically moves from discovery to an initial set of predictive KPIs and experiment plans in a matter of weeks to a few months. Testing and scaling then run on the cadence your traffic, enrollment or sales cycle allows.
Often paired with.
Predictive KPI Design
Replace lagging and vanity metrics with behavior-based leading indicators that forecast results and give teams something they can actually influence.
ExploreConversion Behavior Analytics
Find the specific moments where prospects commit or drift away across digital, phone and in-person channels, and design tested changes that improve conversion.
ExploreBehavioral Segmentation
Group customers, users, members and patients by how they actually behave, so every journey, message and service moment fits the people it is meant to reach.
ExploreRelated insights.
What Is Behavioral Signals Design?
A complete guide to Behavioral Signals Design, the method for finding the behaviors that drive outcomes and turning them into predictive, testable KPIs.
Read
The Cost of Untested Assumptions
Why untested assumptions are among the most expensive hidden risks in any organization, where they hide, and how to surface and test them systematically.
ReadReady to talk about behavioral signals design?
Every engagement begins with a conversation. Tell us what you are facing and we will tell you, candidly, how we would approach it.
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