Hudson’s Bay, a large retailer, has used experimentation to help optimize their checkout experience. As consumer’s expectations rise, it becomes even more important to ensure that the checkout experience is as seamless as possible, regardless of channel or device. Hudson’s Bay has built a data-driven culture focused around creating quality omnichannel experiences for their customers and testing throughout that experience. In this webinar, Joanna Narbuntowicz, Senior Product Manager at Hudson’s Bay, shares how they have created consistent customer experiences throughout the conversion funnel. You’ll learn: How to approach testing across the checkout funnel How Hudson’s Bay prioritizes tests and earns stakeholder buy-in Why Hudson’s Bay emphasises testing throughout the omnichannel experience

1. 1
Optimizing the Checkout
Process
Joanna Narbuntowicz & Mei Luo
+

2. 2
Mei Luo
Customer Success Manager
Joanna Narbuntowicz
Senior Product Manager
Introductions

3. 3
Housekeeping
● We are recording this webinar
● You’ll receive the recording and slides
● We’ll answer all questions at the end

4. optimizely.com/digital-change-agents/

5. 5
Agenda
● Introduction
● About Optimizely
● The Hudson’s Bay Company’s
Journey
● Q&A

6. Revenue, share of wallet, funnel conversion, risk
mitigation, ops efficiency
What
We Do Next gen “Test and Learn” platform for
enterprise-wide digital experience optimization
Over 1B impressions daily
Replaces Digital Guesswork
With Evidence-based Optimization
Digital Experimentation
SaaS Platform
Apply the scientific method to “at-scale”
business decision making.
20X increase in Yield

7. Experimentation: Testing variations of digital experiences
with real users and deploying what wins
+21%
-5%

8. Frontend UI Backend Business
Logic & Data
The anatomy of an experience
i.e. navigation,
search location
& visual treatment
Copy
Images &
Colors
Layout Search algorithms
Personalize content
based on previous
behavior
Recommendations
Make your headlines
more personal

9. “Our success is a function of
how many experiments we do
per year, per month, per week,
per day.”
Jeff Bezos
“Our aim is to create the best
product for our customers, and
we do that through constant
innovation and testing.”
Gillan Tans, CEO
“Our company culture
encourages experimentation
and free flow of ideas.”
Larry Page
“We use experimentation and
testing to inform as much of the
business as we possibly can” -
Gregory Peters, CPO
Today’s Digital Leaders Win By
Using Experimentation At-Scale

10. Spent with Digital Media
19hr
week
2018
Digital-Centric Customer
Spent with Digital Media
41
$396m
Mobile commerce Mobile commerce
$1 8t.
2008
Digital-Convenient Customer
hr
week
Your customer has fundamentally
changed how they engage

11. What
We Enable
1500+
+51%
+$21M
+19%
+28%
Improved subscription
acquisition
Users Scale and agility
of experiments; users
incremental
in revenue
Improved Driver
Acquisition
increase in cross-sell
performance

12. We’re Proud to Work With Great Global Enterprises
24 of the Fortune 100 have chosen Optimizely to drive their digital experience

13. 13
Hudson’s Bay | Improving the Purchase Funnel

14. 14
Responsive Checkout Project
Challenges & Opportunities
What were the existing problems with
the checkout experience?
What are the industry best practices
around the checkout experience?
What was planned as part of the
product roadmap?
Results
How are customers reacting to the
new checkout experience?
How is the new checkout experience
impacting key metrics?
How can we iterate on these results to
get the optimal experience?
Approach to Solution
What is the best solution to address
customer concerns and feedback?
What are other competitors doing?
03
01 02
Iterative
Experimentation
Cycle

15. 15
Purchase Funnel
| Mini Bag | Bag | Checkout

16. 16
Challenges & Opportunities
Challenges & Opportunities
What were the existing problems with
the checkout experience?
What are the industry best practices
around the checkout experience?
What was planned as part of the
product roadmap?
Results
How are customers reacting to the new
checkout experience?
How is the new checkout experience
impacting key metrics?
How can we iterate on these results to get
the optimal experience?
Approach to Solution
What is the best solution to address
customer concerns and feedback?
What are other competitors doing?
03
01 02
Iterative
Experimentation
Cycle

17. 17
Customer Feedback & Funnel Data
■ Customer feedback indicated poor experience on legacy checkout
■ Analytics data supported customer feedback showing checkout abandonment rates higher than industry standard
“Simplify checkout procedure, specially for ‘old’ customers!”
“There’s a lot of text that is the same weight. It’s not easy to read. There’s a lot going on here”
“Checkout is not clear. I have more than one address and credit card info on my profile. One would not
think you have to go into ‘edit’ to select which to use”

18. 18
Challenges & Opportunities
■ Legacy checkout was feature heavy and backend code has a lot complexities
■ Disparate mobile checkout experience due to lack of responsiveness
■ Mobile traffic was growing YOY surpassing desktop but mobile conversion was comparatively lower to desktop and app
Mobile Desktop

19. 19
Responsive Checkout Project
Challenges & Opportunities
What were the existing problems with
the checkout experience?
What are the industry best practices
around the checkout experience?
What was planned as part of the
product roadmap?
Results
How are customers reacting to the new
checkout experience?
How is the new checkout experience
impacting key metrics?
How can we iterate on these results to
get the optimal experience?
Approach to Solution
What is the best solution to address
customer concerns and feedback?
What are other competitors doing?
03
01 02
Iterative
Experimentation
Cycle

20. 20
Approach to Solution
■ Front-end Optimization Opportunities
○ Single page experience
○ Clean up the interface, simplify steps and remove friction
○ Minimize data entry by eliminated unnecessary fields
○ Implement auto recognition and auto populate features
■ Produce a Minimum Viable Product
○ Conduct a thorough review of all features in order to define MVP, fast follows and sunset
elements
○ Start experimenting on mobile first
■ Test and Iterate!

21. 21
New Bag Design on Mobile Web
Old Bag Design New Bag Design

22. 22
New Checkout Design on Mobile Web
Old Checkout New Checkout

23. 23
Challenges & Opportunities
What were the existing problems with
the checkout experience?
What was the impetus to the initiative?
What was planned as part of the
product roadmap?
What are the industry best practices
around the checkout experience?
Results
How are customers reacting to the
new checkout experience?
How is the new checkout experience
impacting key metrics?
How can we iterate on these results to
get the optimal experience?
Approach to Solution
What is the best solution to address
customer concerns and feedback?
What are other competitors doing?
03
01 02
Iterative
Experimentation
Cycle
Responsive Checkout Project

24. 24
Results on Mobile Web
+6% Conversion Lift
Control - Legacy Experience Variant - New Experience

25. 25
Results on Desktop
Control - Legacy Experience Variant - New Experience

26. 26
Results on Desktop
Control - Legacy Experience Variant - New Experience
+2.2% Conversion Lift
Increased Bag Page views

27. 27
Results for Editing in Bag
Control - New Bag without Editing Variant - New Bag with Editing
Significant reduction in Bag Page views

28. 28
Results for Place Order CTA
Control
Place Order CTA in line with Order
summary
Variant C
Dual Place Order CTA
+1.75% Conversion Lift
Variant B
Place Order CTA in line with steps

29. 29
Responsive Checkout | Key Takeaways
● Challenges & Opportunities:
○ Leverage analytics and qualitative user feedback to inform testing opportunities
● Approach to Solution
○ Experiment first with a minimum viable product and iterate upon the feature
● Results
○ Track metrics across every step of the customer journey to help identify additional areas
of the experience for improvement

30. 30
Q&A
We’ll be answering questions submitted in
the chat box of the webinar console