Join us as we hear Ramkumar Ravichandran, the Director of A/B Testing at Visa Checkout, explain how he created a high impact experimentation program. Ram will take us through the growth of Visa’s program: from selling the value, to laying down the vision, the roadmap and success criteria, to creating the right team and driving engagement with the program. Attend this webinar to learn: -How an experimentation program drives business impact. -A model to drive continuous stakeholder engagement with the program. -How to build a roadmap that goes above and beyond simple UX optimization.

1. 1
The Journey to a Culture
of Experimentation
Ramkumar Ravichandran
Visa
Nate Wright
Optimizely
A look at the defining moments that made Visa’s
experimentation program

2. 2 3
Nate Wright
Director, Product Marketing
Optimizely
Ramkumar Ravichandran
Director of A/B Testing
Visa

3. 3
OPTIMIZELY.COM/DIGITAL-CHANGE-AGENTS

4. 4
Housekeeping
! We are recording this webinar
! You’ll receive the recording and slides
! We’ll answer all questions at the end

5. 5
Agenda
! Introduction
! Optimizely Overview
! Visa’s Journey to a Culture of
Experimentation
! Q&A

6. 6
Digital Experience Optimization:
Digital Products, commerce & campaigns
Up to 5X Increase in Yield:
Revenue, share of wallet, funnel conversion,
risk mitigation, ops efficiency
Partner of Choice:
Work with leading global enterprises & “digital
disruptors” including 26 of F100
OUR COMPANY
Digital Experimentation Platform:
Next gen “Test and Learn” system
Replaces Digital Guesswork:
with evidence-based optimization
Speeds Innovation & Optimization:
Single platform for marketing & product teams
Best-in-class stats & machine learning
Consumer-grade usability
Enterprise program management & prof. services
OUR SOLUTION

7. 7
“Our success is a function of
how many experiments
we do per year, per month,
per week, per day.”
“Instead of saying ‘I have an
idea,’ what if you said
‘I have a new hypothesis,
let’s go test it.’”
“Our company culture
encourages experimentation
and
free flow of ideas.”
“One of the things I’m
most proud of, and I think
what is the key to our
success, is this testing
framework we’ve built.”
Experimentation is the
Next Great Business
Transformation
Jeff Bezos Larry Page
Mark Zuckerberg Satya Nadella
The Surprising
Power of Online
Experiments

8. 8
10x more experiments
Consumer-grade usability
Open data integration
Maximum yield of business value
UX and feature-level experiments
and personalization at every digital
touch point
Enterprise-wide
management & governance
Captures, governs and shares
ideation, analyses & results
World’s most trusted outcomes
BestinclassStatsEngine
FasttimetoresultsviaML
Accelerates digital innovation
Speeds dev ops & deployment
De-risks continuous feature delivery
Ensures success of new features
Unifying flagging & experiments
enables controlled testing of new
features while maintaining high
performance
Ideate
Manage
StoreGovern
Analyze
Share
Open Data
Integration
Security &
compliance
Stats
Engine
Stats
Accelerator
Consumer-
grade
usability
APIs &
Developer
Tools
Feature
Flags
Open source
SDKs
X-Channel
Full Stack
Experimentation
Personali-
zation
Recommen-
dations
Web
Experimentation
PRODUCTS
COMMERCE
CAMPAIGNS
Optimizely X Unlocks the Experimentation Best Practices
of the World’s Greatest Digital Companies

9. 9
26 of the fortune 100 have chosen Optimizely to drive their digital experience
We’re Proud to Work With Great Global Enterprises

10. 10
B U S I N E S S V A L U E
VELOCITY/VOLUME
LEVEL 1
Executional
Start
LEVEL 2
Foundational
Growth
LEVEL 3
Cross-Functional
Advancement
LEVEL 4
Operational
Excellence
LEVEL 5
Culture of
Experimentation
Our Products and Services Take
You on Your Experimentation Journey

11. Visa’s Journey of Experimentation
Optimizely Webinar
Feb 2018

12. Intended for Knowledge Sharing only
Quick recap of what it is
Visa’s Journey
12

13. MARKED BY THREE BROAD ERAS: GETTING BUY-IN, FOUNDATION & TRUST BUILDING AND FOLLOWED BY GROWTH
2014 2015 2016 2017 2018
• Product launched
• KPIs & goals established
• Selling Experimentation
• Build vs. Buy
• Optimizely integrated
• POC Tests
• New Test Pipeline
• A/B Testing Kanban
Process, Team & KPIs
• New Flow launch
with Learn, Listen &
Test framework
• Cross functional
stakeholder
engagement
• Educate on full
potential and Vision
for Experimentation
• Evangelism and Point
of Contact for other
business units within
Visa
• Data Driven Strategy
(Analytics & Testing)
• Workflow
Management and
Program Optimization
• Targeting &
Personalization
Pivotal decisions along the
journey!

14. PIVOTAL DECISION 1: GETTING EXPERIMENTATION IN THE DOOR
A compelling needs, USP & impact story, getting right stakeholder sponsorship and executive support got us in…
• Gap vs. KPI goals
• Time to action on actionable insights
• UX decisions that could have been answered better (vs. Hippo, small samples, competitions)
• Technology investment, time and effort in delivering fixes that didn’t move the needle
• Personalization
• Learning goals for future initiatives
The Story
• Right stakeholders with the right need (Product Launch Management) and right “heft”
• Positioning at the right time (after baselines and analytics)
• Clear Success Criteria
Stakeholder
Sponsorship
• Customer focus – UX, UX, UX
• Demands on accountability (progress and results)
• Focus on execution efficiency and optimization (Agile)
• Long term vision
Executive
Support

15. PIVOTAL DECISION 2: BUILD VS. BUY ON EXPERIMENTATION TOOL
Tool needs to support a variety of experimentation needs but at the same time making it easy for non tech users to learn
and use, manage the Workflow and with keep latency low…
• Supported experiment designs: Multi level, multi factor, multiple A/B
• Custom Traffic distribution: Segment filters, Universal Controls
• Type of Tests: Placement/Prominence/Messaging, Funnels, Omni Channel, Algorithms
• Test Metrics: Standard & Custom
• Implementation effort
• Supported Channels: Web, Mobile Web, Native SDK, Single Page Applications
• Pricing packages
• Programming experience
• Analysis options: Integration with Web Analytics/CXM and data export to data lakes
• Security limitations
…the key factor being can in house tool be kept current with market needs, the migration or integration cost and support
need/cost from Engineering team

16. PIVOTAL DECISION 3: SETTING UP THE RIGHT FOUNDATION (PROCESS, TEAM & PROGRAM KPIs)
We iterated our way into a working team framework and process set up for selecting right experiments, setting them up
correctly/quickly, ensuring we have Dev/QA/PM support and is guided by Product Strategy…
• A/B Test Analyst (Analytics): The driver of the testing program. Involved from start to finish up until the hand-off of a successful test to its
respective product owner. A SME in the Optimizely tool, owner of test setup, deployment, and analysis.
• Product Partner: Talks to and brings in the right people for different steps of the process. Offers product’s perspective in terms of
gatekeeping duties on test ideas. Well connected to different product owners and acts as the liaison towards the product team.
• QA Partner: Helps ensure that there are no bugs in the test setup, from a usability standpoint.
• Technology Partner: Offers consultation on feasibility for tests, assists in setup of advanced tests.
• Design Partner: Helps the team germinate ideas, as well as give the team visuals to work off of in a test.
Ideation
Prioritization /
Grooming
Setup QA Deployment Analysis Implementation
Analytics, Product, Design, Tech
Analytics, QA
Analytics, Product
Team
Process

17. PIVOTAL DECISION 3: SETTING UP THE RIGHT FOUNDATION (PROCESS, TEAM & PROGRAM KPIs) contd…
Apart from the business KPIs, we defined a set of internal operational KPIs for the Experimentation Program to ensure we
are driving value both efficiently and effectively…
Program KPIs (Operational)
• # of Tests run per month
• % Successful tests
• % Learning Tests
• % Workaround/Bug fix Tests
• #Channels Tested on
• Time from ideation to deployment
• Time from test outcome to product implementation
• Program RoI
• Stakeholder NPS
• KPI Delta vs. Universal Control
…both raw
and YoY
growth forms

18. PIVOTAL DECISION 4: LEARN-LISTEN-TEST FRAMEWORK FOR NEW FLOW ROLL OUT
Analytics provides insights into “user behavior”, Research context on “motivations” & Testing helps verify the “tactics” in
the field and everything has to be productized…
Key benefits
Focus on Big Wins
Reduced Wastage
Quick Fixes
Adaptability
Assured execution
Learning for future
initiatives
Strategy
Data
Tagging
Data
Platform
Reporting
Analytics
Research
Cognitive
Iterative
Loop
Optimization

19. PIVOTAL DECISION 4: LEARN-LISTEN-TEST FRAMEWORK FOR NEW FLOW ROLL OUT contd…
Iterative & quick improvement (15% pts) of the KPI performance during the new experience launch helped us gain trust of
our stakeholders…
1 2 3 4 5 6 7 8
Months since launch
Iterative Testing helped us
improve the performance of
new product...
New Experience Current Experience
…doing it as a cross functional group of PM, Data Scientists, Engineering/QA and UX helped us educate the value & impact of
experimentation

20. PIVOTAL DECISION 5: MOVING EXPERIMENTATION UP TO THE TOP OF THE PRODUCT DEVELOPMENT LIFECYCLE
Leveraging insights from experiments to prioritize new ideas/features/functionalities/forms and making Test & Learn a
standard rollout process…
Concept Design Prototype Build Run Retire
Business Case
Whathappenshere?
The Flow
Testing the
waters
Development
Launch &
Sustain
Migration from
the current
product to
newer one.
Moved up the Strategic Value Chain
signified the arrival of “A/B Testing”

21. PIVOTAL DECISION 6: EDUCATING STAKEHOLDERS ON FULL POTENTIAL AND LONG TERM PROGRAM VISION
Over past few years we progressed along maturity curve, but still ways to go. The most important critical element to up
level experimentation and continuously engage stakeholders is to show that lot more is possible and should be done…
SELL
SCALE
EXPAND
DEEPEN
TRANSFORM
Phases of Maturity
ValueAdd
We are here
• Sell the value and get it in
• Solid foundation of
Team/process/KPI
• Successful deployment of Test &
Learn to drive impact
• Complex tests
• Data Driven
Design
• Personalization
• Champion/Challenger
• Platform
• Algorithmic Testing
• Test Modularity &
Portability
• Monetizable Product
More at: https://www.slideshare.net/RamkumarRavichandran/advancing-testing-maturity-in-your-organization

22. OTHER BEST PRACTICES THAT WORKED FOR US
Knowing what we are testing & how much to expect, i.e., rank ordering between Visual(Messaging,
Prominence, Placement), Page Design (Flow, Form, CTA), Platform Performance and Content/Personalization.
Saying no: Keeping the pipeline focused on high impact tests, leveraging alternatives for low value tests
(Prototypes/usability studies/surveys) ensure that real Tests don’t suffer from low sample or contamination.
Sharing the wins: Credit where it is due- Engineers, Testers, Program Managers are as critical to the test success
as is analyses, product strategy or Design. Ensure they get the credit and make it a win-win for everyone.
Communication: Regular reporting of pipeline, impact and learning help with mindshare & engagement.
Planning it ahead: Intake criteria/process, prioritizing with strategic goals, pre analyses (impact/success
criteria/proxies/past learning), multi KPI tracking set up and decision protocols help improve effectiveness.

23. Intended for Knowledge Sharing only
Quick recap of what it is
Was it a fairy tale always?
23

24. LESSONS LEARNT THE HARD WAY
Part time involvement: Not everyone on the Kanban team is fully dedicated to Testing->rotation affect
continuity. Build in buffers for managing external dependencies and get ‘right’ help when needed.
Not keeping key external facing team always in the loop: Lax Testing Governance & Lineage can severely
impact brand integrity, pose legal challenges or become tricky for external facing teams. Proactive
communication mandatory.
Platform means everything required for making it self-serve: Optimize onboarding exercise, simplify adoption,
make it easy to learn/engage/ask questions/take help, creation of an active community, selling the vision and up
level the conversation.
What’s works once and at one place, doesn’t work same every time and everywhere: Offsite QA necessary.
Soft target for Product issues: Anything goes wrong, must be testing. Only response was to actually jointly
address each blame and prove that it was indeed not the case.

25. STILL HAVEN’T BEEN ABLE TO SOLVE CONCLUSIVELY
Resourcing & budgeting: As experimentation matures, the investment and support needs spike. Repeat selling
becomes tougher and tougher with increasingly complex message and large scale dependencies.
Moral hazard: Since Optimizely can do things quicker, it’s often used for bug fixes to workaround engineering
protocols. Also since Optimizely can ramp the winner variation to 100% right away, the incentive to make a
product change right away becomes lesser. It leads to multiple concurrent experiments.
External Factors: Regulatory requirements, privacy issues, non traditional GUIs and AI solutions
Globalization issues
Victim to vagaries of set up: Cannot and should not be an independent fiefdom, will depend on the overall set
up and has to work within the constraints.

26. Intended for Knowledge Sharing only
Quick recap of what it is
The experimentation utopia
26

27. IF GOD DECIDED TO CREATE AN A/B TEST PROGRAM, WHAT WOULD IT LOOK LIKE…
Every major product change has been iterated, quantified &
contextualized
A centralized but modular, & integrated Learn, Listen and
Test Framework covering all domains
A Single-Source-Of-Truth Testing Datamart within the
Organization’s Datalake for year end Program effectiveness
studies
Unified Workflow & Project Management with searchable
Knowledge repository & centralized Admin capabilities
Programmatic Testing with human intervention protocols

28. Intended for Knowledge Sharing only
Quick recap of what it is
The parting words…
28

29. SUMMARY
As with any user journey management, our journey began with education/selling, followed by a POC/quick
wins to get tapped in a major initiative. The victories in major initiative helped us get engagement and
support to grow along the experimentation maturity curve.
Benefit from Experimentation is best realized when it’s anchored to Strategic goals, supported with insights
from Analytics and Research and what to test is driven by right stakeholders.
Growing along maturity curve gets more difficult progressively because of increasing needs (resourcing &
budgeting). Keep iterating on multiple selling approaches and get help when needed. But most importantly
remember it’s a “long haul”.
Organizations with a disciplined Experimentation culture within the DNA are poised to reap benefits of
higher accountability, focus on business performance and optimized Customer Experience Management
Testing Program was successful because of the right foundation of the team, ownership and success criteria.
Knowing what to test and what not to and why helped us delivering stronger Program RoI.

30. Questions & Answers

31. OPTIMIZELY.COM/DIGITAL-CHANGE-AGENTS

32. Thank You