Before you personalize any given digital experience, you obviously need to know who you’re personalizing it for. Effective personalization means defining, creating and developing the right kinds of audience groups. The ultimate goal? Providing the feel of a genuine one-to-one experience. Join our webinar to discover the ingredients of a good audience. How to identify and reach them with relevant experiences. And why experimentation is the key to optimizing every different experience for each separate group. What you’ll learn: - Why you should only focus on ‘actionable’ audiences with high reach - and what that actually means. - Key personalization use cases to target audiences across verticals. - How experimentation helps to provide the best possible personalized experiences. Learn more about creating impactful digital experiences in the Power of Personalization: https://www.optimizely.com/optimindset-personalization

1. Putting the Person
into Personalization
Jil Maassen | Senior Strategy Consultant
Identifying audiences and their reach to
realize maximum impact

2. 2
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Housekeeping

3. Jil helps leading brands like Renault and
JustEat deliver personalized experiences to
their customers and make the transition to
becoming data-driven rockstars. She facilitates
the transformation of mindsets, drives the
cultural shift of leadership and product teams,
and encourages the replacement of digital
guesswork with evidence-based optimization.
Building a Centralized Experimentation
Team
Established a Center of Excellence including
processes, governance and roles & responsibilities
for multi-team experimentation programs
Enabling Evidence-Based Optimization
Provided web assessment guidance on using data to
determine test ideation as well as testing strategy
and roadmap advice
Selected
experience
OPTIMIZELYSERVICES2019
Customer
s
Jil Maassen
Senior Strategy
Consultant, EMEA
Areas of expertise &
industry
Strategy Consultant, Optimizely
Advise enterprise customers on implementation of
experimentation programs through Optimizely’s
technologies
Management Consultant, goetzpartners
Driving digital transformation and restructuring
programs of enterprises post-mergers/acquisitions
CRM Manager, Westwing Home & Living
Responsible for all direct customer communication
through e-mailing, by coordinating a cross-
functional team
Scaling Experimentation Program
Developed enterprise experimentation
programs from simple tests to high complex
server-side testing
Education &
Certification
Ivey Business School, Western University
Master of Science, International Management
CEMS, The Global Alliance in Management
Dual Master in International Management
University of Buckingham
Bachelor of Science, Business Management

4. 4
Agenda
Audience Discovery
Key Personalization Use Cases
Experimentation vs. Personalization
Tips & Tricks

5. Audience
Discovery

6. 6
Unknown
Known
Origin Funnel Step Behavior
Marketing
Stage
Right
Content
1st / repeat
session
Location
Device Type
CRM
Campaign
Search term
Viewed X
pages
Logged in
Spent X
time
Visited
Registration
Page
Unknown
1st Session
& no
behavior
1st Session
& scrolled
on HP
2nd Session
& Clicked on
X
Welcome
Discount
Top Value
Proposition
Highlight
Regional
Content
Awareness
Considera-
tion
Decision
Usage
Increase
Cross-
Product
Usage
Unknown vs. Known

7. 7
Behavioral
What is their intent?
• Viewed category of content
• Entered certain city/zipcode
• Past Browser Behavior
• Uploaded to photo album
• Scrolled 50% down the page, but
didn’t engage.
Contextual
What can we infer from the context
of the users browser?
• Marketing Campaign
• Referral Source
• Device
• New/Returning
• Time of Day
• Browser
Demographic
Who are they?
(1st or 3rd party data)
• Geography
• Industry Vertical
• Gender
• Member/Non-Member
• Demographic
• Customer Data (CRM)
○ Customer Tier
○ Loyalty
Audience Discovery
The types of data to help identify your audience

8. 8
Behavioral
What is their intent?
• Viewed category of content
• Entered certain city/zipcode
• Past Browser Behavior
• Uploaded to photo album
• Scrolled 50% down the page, but
didn’t engage.
Contextual
What can we infer from the context
of the users browser?
• Marketing Campaign
• Referral Source
• Device
• New/Returning
• Time of Day
• Browser
Demographic
Who are they?
(1st or 3rd party data)
• Geography
• Industry Vertical
• Gender
• Member/Non-Member
• Demographic
• Customer Data (CRM)
○ Customer Tier
○ Loyalty
Audience Discovery
The types of data to help identify your audience

9. 9
3rd Party Data
1st Party Data
Dynamic Customer Profiles
(DCP)
Browser/Client
Demographic Audience Targeting

10. 10
Customer Age (30-50, Pre-Retiree, Retiree)
Gender
Birthday
Years a Customer
Camera type: dslr, point-and-shoot, mobile
Photo resolutions: S, M, L
Photography Style: Landscape/nature, Portrait/people, Art,
Travel, Kids/Family
Geography, etc.
Preferred shipping location
DCP Data (Demographic)

11. 11
Behavioral
What is their intent?
• Viewed category of content
• Entered certain city/zipcode
• Past Browser Behavior
• Uploaded to photo album
• Scrolled 50% down the page, but
didn’t engage.
Contextual
What can we infer from the context
of the users browser?
• Marketing Campaign
• Referral Source
• Device
• New/Returning
• Time of Day
• Browser
Demographic
Who are they?
(1st or 3rd party data)
• Geography
• Industry Vertical
• Gender
• Member/Non-Member
• Demographic
• Customer Data (CRM)
○ Customer Tier
○ Loyalty
Audience Discovery
The types of data to help identify your audience

12. 12
https://clickclickclick.click
Contextual Audience Targeting

13. 13
...my browser.
...my operating system.
...pixel distance of my mouse movements.
...when I made the window inactive by opening the console.
...when I resized my window.
...the number of CPU cores my device uses.
...that I was using a private browsing/incognito window.
In one minute, it knew…

14. 14
Behavioral
What is their intent?
• Viewed category of content
• Entered certain city/zipcode
• Past Browser Behavior
• Uploaded to photo album
• Scrolled 50% down the page, but
didn’t engage.
Contextual
What can we infer from the context
of the users browser?
• Marketing Campaign
• Referral Source
• Device
• New/Returning
• Time of Day
• Browser
Demographic
Who are they?
(1st or 3rd party data)
• Geography
• Industry Vertical
• Gender
• Member/Non-Member
• Demographic
• Customer Data (CRM)
○ Customer Tier
○ Loyalty
Audience Discovery
The types of data to help identify your audience

15. 15
Using Pages, Events and Tags
Luxury Shoe Shoppers:
visitors who have added to
cart any shoes over $400
in the last 30 days.
Behaviorally Targeted Audience

16. 16
Using Pages, Events and Tags
Luxury Shoe Shoppers:
visitors who have added to
cart any shoes over $400
in the last 30 days.
Behaviorally Targeted Audience
Event: Added to Cart
Tag: Category
Tag: Price

17. 17
Things to think about:
● What are your largest audiences? What is the ‘reach’ of these audiences? (% of that
page’s visitors)
● What is the unique value of these audiences (or user personas)?
● How feasible is it to target these audiences?
Campaign Ideas Audience Examples
Category Affinity Visitors that have viewed a page or resource of category X at least X times in the last X days
Customer Journey Stage Visitors that are more or less qualified as purchasers on their step of the customer journey / marketing funnel
Photo Storage Users Visitors that have registered with your site and have uploaded photos
Photography Style Visitors that have uploaded photos to their online album that can be categorized: landscape/nature,
portrait/people, art, travel, kids/family
Keyword Search Customers Visitors that have searched for X in the past X days
Location Visitors that are based in a particular region.
Social Visitors Visitors that have come to your site from X social site in the past X days
New Visitors Visitors that have not been to your site in X days
Returning Visitors Visitors that have been to your site at least X times in the past X days
Linking Audiences to Campaign Ideas
Using visitor data to develop audiences and linking them to campaign ideas

18. 18
Who are they? What is important to them?
What are they looking for?
What can you do?
New Visitor
● Looking for info/education
● Someone who can sympathize or relate to her
individual problem or need
● Acknowledge her “newness” to brand,
● Aim to get her contact information
● Educate her on offering & encourage return visit
Return Visitors ● Ability to continue her shopping session from
where she last left
● Incorporate her past site behavior to shape
offering
● Acquire her contact information
A Known Visitor Who is Not Engaged
Yet
● Understand how the product/service can benefit
her
● Look to engage him/her via interactivity
● Communicate the benefits of your
offering/product
Customer Who is Losing Interest ● A need or benefit that is not ‘perceived’ as
being satisfied by your product/offering
● Communicate quality of the product/offering
and why it’s important to hear from us.
● Think about ways to re-engage: promotions,
news, etc.
Customer Who is Gaining Interest ● Advice to narrow down the product/offering
● Offer advice on which product is best for them
● Provide ‘white glove’ service (think: they’re in
your office)
A Repeat/Loyal Customer (Highly
Engaged)
● Recognition and benefits as a repeat customer
● Use rewards or awards to encourage him/her for
being a good customer
● Surface your ‘premier’ loyalty programs
● Encourage him/her to share or promote the
brand
Connecting the ‘Who?’ to that ‘What?’
Knowing your “what” helps to focus your messaging to the target audience

19. Key Personalization
Use Cases

20. 20
Key Personalization Use Cases
Category Affinity
Create relevant offers and product placements
across key points of your experience based on
affinity shown for product or content types from
prior browsing behavior
Customer Experience as a
Competitive Advantage
Tailor your experiences to target your customers
and test how each experience resonates
Symmetric Messaging &
Session Cohorting
Ensure that customers receive messaging that
is consistent and applicable based on search
terms, creating a cohesive customer journey
Localizations
Localize web experiences based on
customer location
Behaviorally Triggered
Campaigns
Based on previous behavior, target specific customers
with personalized experiences in real time
ABM
Create relationships with your most important
customers across your experience through 1-to-1
messaging and value propositions based on which
company or industry they are in
Loyalty Tiers
Push your loyal customers to the most important
groups by offering unique benefits based on current
tier of loyalty as well as ensure consistent messaging
for a seamless experience
Abandoned Cart &
Purchase History
Personalize based on individuals purchase
history and cart abandonment

23. +113%
Content
Views
+117%
Funnel
Entries

25. +26%
SIGNUPS

26. PERSONALIZEDORIGINAL
+24%
Click to Sale
+30%
Add-to-Cart
+210%
Conversions

31. Experimentation vs.
Personalization

32. 32
A/B Testing
Find the average-best experience
Personalization
Deliver the best experience for each
visitor

33. 33
Finding the AVERAGE best experience OVERALL for everyone
Experimentation

34. 34
Segmenting out your audience and finding the best INDIVIDUALIZED experience
for each segment
What is personalization?

35. 35
Different experiences resonate with
different individuals, and
personalization enables you to
ensure you find an experience that
resonates with your customers
The right experience is
not always the same
for everyone
Personalization

36. Tips & Tricks

37. 37
Demographic
Who are they?
(First party or third party data)
• Geo, Vertical, Gender, Member Non-Member,
Demographic, CRM Data, Customer Tier, or
Loyalty
Behavioral
What is their intent?
● Viewed category of content, Entered certain
city/zipcode, Past Browse Behavior, Uploaded
to photo album, Scrolled 50% down the page,
but didn’t engage
Contextual
What can we infer from the context of
the browser?
• Marketing Campaign, Referral Source, Device,
New/Returning, Time of Day, Browser
Pro Tip #1
Mapping what we know to the customer journey

38. 38
Demographic
Who are they?
(First party or third party data)
• Geo, Vertical, Gender, Member Non-Member,
Demographic, CRM Data, Customer Tier, or
Loyalty
Behavioral
What is their intent?
● Viewed category of content, Entered certain
city/zipcode, Past Browse Behavior,
Uploaded to photo album, Scrolled 50%
down the page, but didn’t engage
Contextual
What can we infer from the context of
the browser?
• Marketing Campaign, Referral Source, Device,
New/Returning, Time of Day, Browser
NEW VISITORS RETURNING
VISITORS
KNOWN
VISITORS
Awareness Consideration Service LoyaltyPurchase
Pro Tip #1
Mapping what we know to the customer journey

39. 39
Obviously Actionable
Large
Need for Creativity
Granular
Browsed Twice; Product Category
Visitor Cohort; New, Returning,
Active, Loyal
Large Geos; Coastal Urban,
State, Key Cities
Past Purchasers
Second Priority
Pro Tip #2
Understand actionable audiences versus reach

40. 40
Pro Tip #3
Some audiences have a low technical signal and it may be difficult to target

41. 41
Next Steps: Continue Your Learning!
www.optimizely.com/optimindset-personalization/
Search Optimindset Personalization
to access other resources in the series

42. Q&A

43. Thank you