Delivering customized digital experiences based on a visitor's unique characteristics and browsing behavior has been shown — time and time again — to improve engagement metrics and increase conversion rates. As tools have evolved, the way we personalize content and the type of content that we personalize has also changed.
We know scaling personalization beyond a few use cases can be overwhelming and time-consuming, so join us for our webinar and we’ll explain how it can be made simpler through artificial intelligence. In fact, it’s never been easier to understand consumers and create personalized offers by adding AI capabilities on top of Acquia’s DXP platform.
In this webinar, we'll cover:
- How Acquia Lift in conjunction with Google AI and marketing tools take personalization to the next level
- Defining moments that lead to conversion and patterns in user behavior
- Leveraging richer data collection and enabling simpler content creation for personalization
5. RIGHT BRAIN & LEFT BRAIN
Mathematics
Logic
Facts
Language
Analysis
Creative
Feelings
Art
Rhythm
Imagination
6. IT’S RELATIVELY EASY TO GET STARTED
CRAWL
Geolocation Marketing Campaigns Visit Frequency
Device / SystemPages ViewedBrowsing Behavior
7. ENTERPRISE BANK AND TRUST
New users in markets with
acquisitions
+198%
New users
+97%
Website goal completions
+309%
Contact form completion
+26%
8. BUT IT’S EASY TO GET STUCK FROM THERE
CRAWL
Lower effort,
fast results
WALK
Requires more content
and data, but higher impact
RUN
More time & complexity,
highest impact potential
9. HOW DO WE
RECOGNIZE THESE
PERSONAS?
By using data and
artificial intelligence.
13. NARROW AI – “ACCELERATED” INTELLIGENCE
DECISION
MAKING
PREDICTIONUNDERSTAND DATA
14. PERSONALIZATION MATURITY MODEL
No organization can jump from
zero to a fully-automated, machine
learning system that dynamically
determines next best actions in
the moment.
We use a maturity model to assess
your current state, understand where
you want to be, and then help build
a crawl-walk-run roadmap to get
you there.
15. HOW DO WE USE ARTIFICIAL INTELLIGENCE?
For exploratory analysis, to…
– inform design and focus testing
– surface and refine personas
– understand journeys and cross-channel behavior
To drive activation – segment audiences and predict behaviors to…
– provide personalized content in digital experiences
– reach new audiences and influence existing audiences through
marketing and advertising
17. AI FOR EXPLORATORY ANALYSIS
Journey Analysis
– Higher education client
– How do users progress?
– When do they proceed down
the desired paths and where
do they deviate?
– What are opportunities
to intervene?
Landing Pages
Degree Programs
Homepage
Admissions
Military
Search Results
Transfer Students
Student Experience
About
Tuition
Request Info
A
B
C
18. AI FOR EXPLORATORY ANALYSIS
Content/Feature Importance
– Retailer of industrial parts
– What content or functionality
is most important to user
conversions?
– Where should we focus
design efforts and testing?
CONCEPT PRIORITY
Update Cart High
Get Assets High
Initiate Search Medium
Refine Search Medium
Gather Info Low
19. AI FOR EXPLORATORY ANALYSIS
– Exploratory analysis with AI
requires some foundation
of Measurement & Analysis
and Customer Profiles
– It further enables Integrated
Channels and helps prioritize
Optimization & Testing and
Intelligent Content
20. AI MODELS IN ACTION
Audience Segmentation & Lookalikes
– Calculate segments for personalization and targeted
marketing
– Lookalikes aren’t just about matching demographics —
they’re users who are likely to behave similarly
– Target lookalikes to get new users from advertising,
and use models to classify new users from other sources
as data takes shape
21. AI MODELS IN ACTION
Conversion Prediction & Targeting
– Compete for maximum share for high
value audiences
– Reserve branded advertising budgets and
get right to the point with personalized content
for high value audiences
22. AI MODELS IN ACTION
Lifetime Value + Purchase Prediction
– Clothing retailer
– Identify high, mid, and low value segments
– Shift spending on advertising in different
ways across those segments to maximize
the value of advertising
23. AI IN ACTION
– Requires a degree of
Integrated Channels
and capabilities for
Optimization & Testing
– Further enables building
robust Customer Profiles
with additional data
on audiences
27. HOW TO: DRIVE PERSONALIZATION
Website
Lift Profile Manager
Analytics 360
BigQuery
AI Platform
PATTERN RECOGNITION
SEGMENTATION
PERSONALIZED
CONTENT
REPORTED
INTERESTS
Mobile
OBSERVED BEHAVIOR
28. HOW TO: COORDINATE CHANNELS
Website
Lift Profile Manager
Analytics 360
BigQuery
AI Platform
PATTERN RECOGNITION
SEGMENTATION
PERSONALIZED
CONTENT
REPORTED
INTERESTS Display & Video 360
Mautic
TARGETED
MARKETING & ADVERTISING
Mobile CRM In Store
OBSERVED BEHAVIOR
29. Introducing Acquia Lift
3
2
1
Personalized Content
Deliver personalized content to both known and
unknown visitors in real time
Campaign Management
Easily track and manage all your campaigns from a
single UI
Segment Builder
Segment your visitors based on a variety of criteria in order
to deliver targeted campaigns
4
Campaign Builder
Quickly create and schedule A/B/n tests and targeted
personalization campaigns
5
Lift Analytics
Make data-driven decisions based on visitor behavior
Improve
customer
engagement by
delivering a
personalized
experience
30. What Makes Acquia Lift Different (And Better?)
✹ Create personalization in three simple steps
✹ A/B testing and targeting with no code
✹ Scheduling capability enables small teams
✹ Superior multi-lingual personalization
✹ Optimized for Drupal
✹ 6 Open APIs for integration
31. How Lift Optimizes the Customer Experience
PROFILE DATA
MANAGEMENT
CONTENT
SYNDICATION
PERSONALIZATION
ACQUIA
Profile ManagerContent Hub Experience Builder
33. ACQUIA
ACQUIRES
AGILONE
AgilOne Joins Acquia’s
DXP Product Suite
– Harnesses the power of customer
data
– Delivers the ML and AI marketers
need to make informed decisions
– Provides a single view of the
customer
– Helps marketers deliver immediate
value through personal
experiences across every channel
– Provides a unified data
intelligence layer for the Acquia
Marketing Cloud
34.
35. WRAP UP
– Use what you have, but plan ahead
to build future capabilities
– AI builds on and helps scale from
rule-based personalization
– Tools for AI range from business user
to data scientist
– Personalization should be extended
across channels