Financial Services · Digital Acquisition · Experimentation
A large financial services organization wanted to improve digital acquisition, but lacked the infrastructure, operating model, and decision loops to run behavioral experiments at scale. The goal wasn’t more tests — it was a practice that could sustain itself.
100+
Experiments conducted
3
Core acquisition flows optimized
↑
Measurable lift in account starts
0
External dependency at close
The question
How do you turn experimentation from isolated tests into a repeatable decision-making practice?
The organization had data and ambition. What it lacked was an operating model to connect behavioral insight to product decisions systematically — and a team that could sustain that capability independently.
Most organizations don’t have an experimentation problem. They have a decision loop problem — tests accumulate without changing how the team thinks.
Challenge
The organization had run tests before. But results weren’t feeding back into product decisions consistently. No shared standard for test design, no clear ownership of results, no operating rhythm connecting findings to the roadmap.
Each test was a one-time event rather than a contribution to accumulated organizational knowledge.
How we worked
Phase 01 — Identify opportunity areas
Mapped the acquisition journey to identify where behavioral friction caused the most drop-off — and where intervention was most likely to produce measurable lift.
Phase 02 — Build experimentation discipline
Created test design standards, result interpretation frameworks, and a decision loop that connected outcomes to product prioritization — consistently, not opportunistically.
Phase 03 — Create sustainable capability
Transferred full ownership to internal teams — with the operating model, governance, and institutional knowledge to sustain it without external support.
Key insights
Insight 01
The bottleneck wasn’t running tests — it was the decision loop downstream. Who reviewed results, how findings were interpreted, whether they reached the people who controlled priorities. Without that loop, well-designed tests accumulated without consequence.
Insight 02
Robust analytics already existed. What was missing was organizational structure to translate data into testable hypotheses, run them systematically, and feed findings back into product. Analytics without operating model is observation. With it, it becomes strategy.
Insight 03
Any individual test could produce a meaningful result. Real leverage came from the compounding effect of a team that tested consistently, interpreted results with shared standards, and built institutional memory from what they learned. Repeatability was the strategy.
“The goal was never more tests. The goal was better decisions.”
Reflection — Digital experimentation practice, Financial Services
Experimentation maturity — from isolated tests to organizational capability
Illustrative representation. Identifying details abstracted.
From insight to action
Finding
Acquisition friction was concentrated in specific flow transitions — not distributed evenly across the journey.
Decision
Focused the initial test program on high-friction transitions — faster results, more legible learning.
Finding
Results were being reviewed by people who couldn’t act on them — and not reaching the people who could.
Decision
Redesigned reporting loops to route findings directly to product owners — with interpretation and recommended action embedded in the output.
Finding
Test quality varied because there was no shared standard for hypothesis formation or success criteria.
Decision
Created a test design framework requiring explicit hypotheses, measurable outcomes, and pre-agreed interpretation criteria before any experiment launched.
Finding
The practice had no long-term owner — it would stall the moment external support was withdrawn.
Decision
Designed for ownership transfer from the start — embedding the operating model inside existing team rituals and reporting structures.
Outcomes
Measurable lift in account acquisition and application starts across the three core flows where testing was concentrated.
100+ experiments conducted with consistent design standards and decision routing — turning isolated tests into a coherent body of learning.
Experimentation governance embedded inside existing team rhythms — no parallel process, no external dependency at engagement close.
Internal teams equipped to continue independently — with the operating model and institutional knowledge to scale the practice.
Product prioritization became more evidence-driven — experiment findings feeding directly into roadmap conversations for the first time.
Reflection
Experimentation becomes transformative when it shifts from isolated optimization to organizational capability.
A single test can improve a flow. A practice changes how a team thinks.
The goal was never more tests. The goal was better decisions — and a team that kept making them long after we left.
Work with us
No formal pitch. Just a conversation about what you’re working on and whether we’re a fit.
hello@candelita.studioCandelita engagements are led by Jennifer Dopazo and tailored to each client.