Case study · B2B Web

Reduced customer time-to-value from 45 days to 7 days with a self-serve onboarding system

Shipped Timeline — add dates Lead Product Designer B2B Web 1 PM · 5 Eng · Growth Product Specialist · Customer Support
Reviewing pre-selected services for Smart Start onboarding

Reviewing pre-selected services for Smart Start Onboarding

TL;DR
Background
Pricebook Pro onboarding historically required hands-on support from a Growth Product Specialist — creating long wait times and inconsistent experiences.
Problem
Every new customer's time-to-value was capped by specialist availability, not their own readiness to get started.
Approach
Designed Smart Start, a guided self-serve onboarding flow with AI-backed pricing suggestions and pre-curated services, validated through moderated testing with 5 customers.
Outcome
Time-to-value dropped from 45 days to 7 days, with a 23% drop in onboarding-related escalations.
23%
Drop in onboarding-related escalations
38
Days saved in onboarding time
90%
Coverage of out-of-the-box service jobs

The Problem

Pricebook Pro is a pricing and service catalog tool that helps contractors standardize services and pricing across their business. While powerful, onboarding to Pricebook Pro has historically required hands-on support from a Growth Product Specialist, which created long wait times, inconsistent onboarding experiences, and led to customer frustration.

The product had no path for a customer to succeed on their own. Every new customer's time-to-value was capped by specialist availability, not by their own readiness to get started.

How might we onboard our B2B customers without needing live support?

Solution

I led design on Smart Start, a guided onboarding flow that let customers configure a production-ready Pricebook — guiding users forward with confidence and reducing decision fatigue without a specialist. Along with my PM, we conducted moderated testing with 5 customers to get feedback on the overall workflow, which helped us further refine the experience.

Decision 01

AI-driven suggestions as a trust signal, not just automation

Customers faced with a blank pricing setup tend to stall out and procrastinate rather than guess. By grounding pricing suggestions in real market data, customers had a confident starting point to act on, rather than guessing and losing out on potential revenue.

Suggested pricing guide backed by market data per region

Suggested pricing guide backed by market data per region

Decision 02

Reduce decision fatigue through curation, not just choice

Rather than asking customers to build their service catalog from scratch, the flow pre-selects relevant services by industry and region, with clear reasoning for why each was recommended and the ability to edit anytime — reducing decision fatigue for a first-time user.

Reviewing pre-selected services for Smart Start Onboarding

Reviewing pre-selected services for Smart Start Onboarding

Decision 03

Keep specialists in the loop without keeping them in the critical path

Removing the live-support dependency didn't mean removing support — it meant redesigning where it lived. I reviewed existing support patterns to identify exactly where onboarding was breaking down, then built standardized in-product help and documentation customers could return to on their own, at any step.

Help guide which can be revisited at anytime

Help guide which can be revisited at any time

Challenges & Constraints

  • 01 GPS booking integration (removed). I had an initial idea at the end of the flow to book time directly with a Growth Product Specialist, like a Calendly experience. After talking it through with my PM and eng, it wasn't easily feasible due to time constraints and GPS scheduling constraints that made this difficult to scale. Instead, we provided a direct email pathway to GPS support within the help guide.
  • 02 Reusing the existing Pricebook table (rejected). Engineering wanted to reuse the existing Pricebook table to save time on designing a new flow, but I pushed back — we didn't need all the information associated with it, and it would have overloaded the user at a critical decision moment. I also argued for a modular design in the next iteration that could support AI-driven recommendations.

Outcome

This project transformed onboarding from specialist-dependent into a scalable design system: faster customer activation, more consistent onboarding, reduced operational strain on Growth Product Specialists, and improved technician productivity in the field.

  • Faster time-to-value for Pricebook Pro customers — 45 days to 7 days
  • Improved customer satisfaction and confidence during setup
  • 23% drop in onboarding-related escalations

Post-MVP

After the initial success of the MVP launch, we continued gathering feedback from customers to guide the next round of improvements to the flow.

Next project

Budget Code: unlocking a financial tracking system