2015 is considered as the year of personalization. Personalization is creating experiences on web sites or through interactive media that are unique to individuals or segments of consumers. Visitors browse through websites just as they would roam in a supermarket. They have a certain reason for visiting different pages of the site. The job of personalization systems is to predict what she’s looking for on that page and then choose the most relevant content for her.
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2. What is web personalization?
“creating experiences on web sites or through
interactive media that are unique to individuals or
segments of consumers.”
Forrrester Research
3. Why do you need personalization?
To filter the
information
overload
on the web
To provide
experiences
considering
personal
preferences
To adopt to
the ever
changing
needs of
the users
Need for personal
experiences
Demanding
consumers
Information
clutter
5. Which features could be
personalized?
Content
-Texts
-Elements
(Visuals, Buttons etc.)
- Colors
Messages
E-mails
Promotions
Product Offerings
Product
Recommendations
Pricing
Advertising
6. Which data is used to
personalize the web sites?
CONTEXT
Weather,
Location,
Mood,
Search Items,
Categories
INTERESTS
Pages Browsed,
Items Bought,
Genres of Music,
Ads Clicked
DEMOGRAPHICS
Age, Sex,
Education,
Income
SOCIAL DATA
Likes,
Tweets,
Follows,
Mentions
7. What is Predictive Personalization?
and targeting via scientific prediction methods
Activities enabling 1-1 user analysis
are called predictive personalization.
8. Why is Real Time Personalization a
‘Must’ rather than a ‘Nice to Have’?
User related data;
- Users’ interests
- Shopping trends
- Users’ life status
- Users’ context
(location, weather etc.)
Website related data
- Stock level
- Product campaigns
- Discounts/pricing
- Product sizes
- Website content
- Products offered
- Marketing strategy
- KPIs
15. Personalized Real Time Product
Recommendations
The user is welcomed
with real time and
personalized
recommendations.
The recommendations
are updated each time
a new filter value is
chosen.
19. A/B Testing for a better content
personalization
3 different placements of the
‘recommended content’ module:
Experiment applied by the teams of
Upworthy and Optimizely