Arbor Day Foundation
role
Sole UX designer
type
E-commerce, Consumer
Arbor Day Foundation
Reduced support dependency by 48% through clearer product guidance and confident purchasing decisions
Conversational Design, UX Research, UI Design and Prototypes, Stakeholder Alignment, Cross-functional Collaboration
Website
·
2024
·
Team: Solo Product Designer (me), Design Mentor, Business Analyst, Engineering, Data Analyst
,
−48%
Support dependency
+10pts
,
NPS score
+12%
,
Add-to-cart rate
OVERVIEW
Pre-purchase support contacts were rising
The Arbor Day Foundation's e-commerce experience was built like any standard product catalog — browse, select, add to cart. But trees aren't phone cases. Trees ship only during optimal planting windows. Suitability also depends on climate zone and planting conditions. The product never communicated any of this. So customers called support to ask.
The business goals were clear: Reduce support dependency, increase conversion, and improve satisfaction.
Before
After
PROCESS
I ordered a tree first.
Then I read 2,000 support tickets.
2K+
Support ticket analysis
03
Hotjar heatmap analysis
50
User surveys
04
Competitive analysis
Research
Insight
The experience assumed customers understood tree logistics
The experience assumed customers understood tree logistics. Research surfaced the same three questions again and again:
Seasonal shipping confusion
Customers did not understand why some trees would ship months after purchase
Compatibility uncertainty
Hardiness zone information was buried and was not surfaced as a confident purchase signal
Confidence gap
Basic filters helped narrow products, but did not explain which tree was right for a specific yard or climate.
Turning point
The support requests weren't the problem. They were the symptom.
The root cause was a confidence gap at the exact moment of decision. Shoppers weren't reaching out because they were confused — they were reaching out because the product never gave them a reason to trust themselves.
How might we surface the right information at the right moment so shoppers can make confident purchase decisions without contacting support?
DEFINING GUIDELINES
I turned the confidence gap into three design principles.
01
Surface zone compatibility early in the journey
02
Set clear shipping expectations before purchase
03
Build confidence into the product experience
Finding the right solution
Early explorations
Reduce Compatibility Uncertainty
Reduce compatibility related support contacts by surfacing zone compatibility early in the journey and increase purchase confidence.
Compatible
Uncompatible
Iteration 1
Good Match for Zone 9A - 98004
Zip: 80303
AI
Poor
Fair
Excellent
Safe to buy
92% compatibility confidence
Iteration 2
Available
Ships by Tue, July 12
Change
Compatible for your zone 9A-98004
Final Iteration
Compatible for your location
Zone 9A-98004
See Details
Proactive shipping clarity on PDP
Shipping timing shown before purchase, not after — cutting confusion-driven support tickets.
Iteration 1
1
Pre-order
Ships by the week of 07/12
We hold your tree until planting weather is right in your zone
Know more
Iteration 2
Ships between 7/12/24 - 7/18/24
We ship when your climate is ready for planting
Today
Place order
Day 30
Nursery prep
Day 60
Ships to you
1
Pre-order
Final Iteration
Order now & we’ll ship on
Fri, Jul 24 (45 days)
1
Pre-order
Edge cases
Sold out for this season
The nursery is out for pear tree until next season, expected August 2025
See Details
Browse similar trees
Notify me
Reassurance before commitment
The assistant handled open-ended questions shoppers couldn't easily translate into filters.
Defining the AI assistant
Knowledge Base Inputs (Defined with Support team + Business team)
35+ SKUs tagged by zone, sun, soil, size, and ship window
Shipping rules by state and season
Plain-language glossary for bare-root, dormancy, and planting windows
Top 20 support intents converted into bot-ready answers
Conversation Guardrails
Answer only selection, shipping, care, and order-tracking questions
Say "I'm not certain" instead of guessing
No price promises or promotional commitments
Use an 8th grade reading level
Sound like a nursery expert, not a salesperson
Guided AI flow
The assistant confirms location before giving compatibility answers, since a wrong compatibility claim is high-stakes and hard to walk back
Recommends zone compatible
trees without loosing context
Fallback state
Designed the scenarios where the assistant could fail
The assistant confirms location before giving compatibility answers, since a wrong compatibility claim is high-stakes and hard to walk back
Hands over to the human when the
Lets shoppers correct their own input mid-conversation, without restarting the flow
Recommends zone compatible
trees without loosing context
Reassurance before commitment
Added real delivery and UGC images, quick links and guides
Iteration 1
Iteration 2
Final Iteration
IMPACT
Team feedback
"We're getting fewer 'when does it ship' calls and more questions about care instructions"
Support team sync, Week 8 post-launch
KEY LEARNINGS
What this project taught me
Research doesn't tell you what to build—it helps you decide what not to build. Prioritizing
compatibility guidance created a focused, measurable solution instead of a pile of features.
Confidence can be a product metric. Compatibility signals, shipping transparency, and guidance all addressed the same underlying uncertainty.
The best ideas come from collaboration. Cross-functional alignment with marketing, support, and engineering drove the strongest decisions.
This summer I had the pleasure of working directly with Anjali through our Harris Entrepreneurship Program.
Anjali played a critical role in ideating and designing major deliverables for this program. Her ability to quickly analyze and problem-solve in an adaptable way was refreshing to observe. Anjali consistently sought and embraced feedback. This humble approach allowed her to conceptualize and produce user-centered design with tailored depth.
More importantly, Anjali was such a pleasure to be around as she consistently brought positive and enjoyable moments to our culture. Her high-quality work ethic and quick ability to create applicable solutions was impressive. There is no question in my mind that
Anjali will have a major hand in bringing forth new, user-centered designs for substantial impact.
AUSTIN MACKRILL,
