Problem Experience Decisions Impact
Shipped

Livongo Registration

Reshaping onboarding as a high conversion tool for trust and partnership.

Role
Senior PM, Member Growth
Scope
Strategy, Product Design, Stakeholder management
Platform
Web registration, Salesforce config, internal APIs

Why this project?

This is the same problem as CPQ.

Programs are SKUs. Qualification rules are pricing rules. The registration flow is the quote. The spreadsheet is the same artifact that CPQ platforms replace with automated configuration. We replaced it with a system that reads upstream data and adapts the flow in real time.

Framing

Livongo, a chronic conditions management company, was in growing pains. In 2 years, it had grown from one to five health programs sold in dozens of combinations. Every combination changed which registration fields a member saw. The rules for 50 unique client configurations lived in a spreadsheet that operations cross-referenced manually for every new launch. Complexity ballooned & metrics suffered.

Nowhere was the downstream product pain felt more than during onboarding members. The registration flow grew from 20 standard questions to 74 possible fields.

The data told the story. Every step bled members, but the reasons weren't what anyone expected.

Identity & Basic Info
−9%
Sponsor
−12%
Insurance
−19%
Program Selection
−12%
Program Setup
−21%
Health Intake
−8%

The program steps were one unsurprising culprit — historically 11% drop-off, this had ballooned to more than 33% for our multi-program members. Moreover, people weren't signing up for all of the programs they were offered. At a step where the system already knew which programs the member qualified for, the product was overoptimizing for choice. This left revenue, but more importantly, benefits on the table for people who already enrolled.

How could we reduce the friction in registration? How could we minimize what we asked?

Deliverable

At its core, the solution was simple, but a large technical lift. Due to the nature of our client relationships, we had information upstream about members — demographics, health conditions, even specific health data.

This led us to build a system that, given member verification, would allow us to prefill, confirm, or skip the information we needed during onboarding. The art was keeping the member in control & maintaining transparency so the process built trust rather than eroded it.

01

Verification

Confirm membership & identity

To prefill information, we needed to know with high confidence who the person was. We passed this through several signals, but had to verify with confidence to reduce the risk of PII leakage.

Data Sourced

  • • Employer name and sponsorship status from HR feed
  • • Eligibility verified server-side before page load

What changed

  • • Reduced data to the minimum needed to PII match a member
  • • Build trust early by surfacing employer — "we know who you are"
  • • Privacy footer with encryption disclosure

02

Account

Shifting control to the member

Employer data gave us email and phone — but not always the right ones. Work emails and desk phones don't help a member manage diabetes at home. The account step introduced the independent relationship with Livongo, but reinforced that their employer was a partner.

Data Sourced

  • • Email and phone pre-filled from employer HR data
  • • Member can override with personal contact info

Trust Signals

  • • Pre-fill shows we have their data — editing shows we respect their choice
  • • Password creation gives ownership over the account

03

Programs

Let the system make the product decisions

The old flow asked members to choose programs from a list they didn't understand. The redesign reframed their offering as a unified plan for all programs we know they qualified for. In some cases, we would let people opt in explicitly when we didn't have enough data to make a determination.

Data Sourced

  • • Program eligibility from employer benefit config
  • • Health record matching for condition-specific programs

What changed

  • • Reframed as a unified plan covering all eligible programs
  • • "Qualified" vs "Optional" badges set clear expectations

04

Program Setup

Personalize without interrogating

Historically a growing drop-off step. Blue dots mark pre-filled fields — data sourced from health records and employer HR. The "From Your Records" accordion set a pattern for trust — showing what the system already knows and how it knows it. Members always had the ability to edit or change information.

Data Sourced

  • • Monitoring frequency from health records
  • • Diagnosis type, date, and medications pre-filled

Trust Signals

  • • Blue dots visually distinguish pre-filled from manual entry
  • • "From Your Records" accordion with edit controls

05

Health History

Show your sources, earn their trust

Two banners — personal records and health records — show the member what the system already knows. Height, weight, and health conditions pre-filled with source attribution. The member confirms what's there rather than entering from scratch.

Data Sourced

  • • Height, weight, and conditions from health records
  • • Personal profile data from employer HR feed

Trust Signals

  • • Source attribution on every pre-filled value
  • • Separate banners distinguish personal vs clinical data

06

Shipping

Set expectations for what arrives

Kit preview shows what's coming. Shipping address cascades in from employer HR data. The member confirms or corrects. Every field that auto-fills is one fewer reason to drop off.

Data Sourced

  • • Mailing address from employer HR feed
  • • Kit contents determined by selected programs

Trust Signals

  • • Visual kit preview shows exactly what arrives
  • • Editable address gives the member final say

07

Next Steps

Bridge the gap between signup and first use

The final screen reframes enrollment as the start of a relationship. Three concrete actions — download the app, meet your coach, set up your kit. Everything in the flow is designed to get the member here with enough trust to take the next step.

Data Sourced

  • • Coach assignment based on program and language
  • • App download link personalized to device

Trust Signals

  • • Concrete next steps replace vague "you're done" messaging
  • • Named coach creates a human connection before first use
Walk the full flow yourself
Both the original 9-step flow and the optimized 6-step flow are interactive prototypes. Use arrow keys to navigate each step.

Process

Why did more context increase completion?

The org assumed shorter = better. But members weren't dropping off because of length — they were dropping off because they didn't understand why they were being asked. Transparency banners, data source attribution, and partnership-oriented copy gave people a reason to keep going.

Why reframe onboarding as trust, not completion?

Enrollment drove 6 months of revenue. But activation — 6+ blood sugar checks in 3 weeks — drove 12+ month retention and 18 months of revenue. The org bias was "less is more" and "completion, not context." But for someone newly diagnosed, onboarding is the first trust moment. Partnership over authority.

Impact

37→54%
Onboarding completion
Registration redesign
+2.1
Activation lift (top line)
6+ checks in 3 weeks
~$14M
Revenue impact
+3.7% enrollment topline

No spike in support tickets or errors post-launch.

This is the same problem as CPQ. Programs are SKUs. Qualification rules are pricing rules. The registration flow is the quote. The spreadsheet is the same artifact that CPQ platforms replace with automated configuration. We replaced it with a system that reads upstream data and adapts the flow in real time.

View the interactive flow comparison at ctrl.rodeo/reg →