H&R Block
2025
Product strategy
Growth design
UX/UI
H&R Block users felt deceived by hidden pricing, hurting satisfaction and potential retention. I designed a mid-flow personalized price estimate that increased conversions 34% and measurably improved both user satisfaction and intent to return to H&R Block.
Problems I was solving for
User need: Transparent pricing throughout the tax filing process
Business need: Higher conversion rates from price transparency
Impact in 2025
Submissions rate ⬆️ 34%
Expectations ratings ⬆️ 0.4 pts
Mentions of price as deterrent ⬇️
The problem
The origin of the problem
Discovery insights
Why the simple visual: Gives just enough context to the range since there was limited data on other customers' prices to compare against for our first launch
Why the micro-macro overview: Franchisees can set their own prices, which means there's no consistency from office to office; better to arm the user with what info affects price than mislead with incorrectly labeled line items
Initial usability issues
Issue 1: Users tried to move the UI and change the range manually
None of the participants acknowledged the “tax trait” tags, but when prompted understood where the tags had come from.
Shipped designs
Impact in 2025
Expertise rating
82.4
0.3
How knowledgeable or skilled customers think their tax pro is on a scale of 0 to 100 points
(Before March 21st, 2025: 82.1/100)
Expectation rating
84.6
0.4
How clearly H&R Block met a customer's expectations on a scale of 0 to 100 points
(Before March 21st, 2025: 84.2/100)
Overall satisfaction rating
82.1
1.3
How satisfied a customer is with H&R Blocks service on a scale of 0 to 100 points
(Before March 21st, 2025: 80.8/100)
Intent-to-return score
80.8
1.0
How likely a customer is to return the following tax sdason on a scale of 0 to 100 points
(Before March 21st, 2025: 79.8/100)
Future ideas
Increases revenue per client and estimate accuracy
Reduces manual errors and frees up advisors for client consultation
Competitor analysis and user research showed strong demand for detailed pricing
User testing revealed confusion about when/how to use coupons