-Personalization for websites. -This presentation helps to understand the various components and concepts involved in personalization. -Formulates certain approaches and strategies,in tuning-up personalization for websites. -Explains on-site, real time, progressive personalization and related concepts. -Understanding users on the basis of visitor, shopper and customer. -Mapping user journey to personalization optimization.

1. Personalization
-In ecommerce/Internet-

2. HELLO!
I am Parkavi Vasan
(aka) Ravichandran Diavkar
2
Reach me @
https://www.linkedin.com/in/parkavivasan

3. Synopsis
3
Personalization
–(components, Objectives, Users concepts)
Classifications
-(one method of classifying, 1 to 1 , M to 1)
Levels of Personalization
-(element to experience level, reactance)
Connecting the components & elements
-(mapping users, process walk through, over view )
Personalization under Customization
-(explanation and example )

4. 1.Personalization
Fast Forwad
4

5. Personalization
5
Personalization is the process of tailoring content to individual users' characteristics or preferences.
It is a means of meeting the customer's needs more effectively and efficiently, making interactions faster
and easier and, consequently, increasing customer satisfaction and retention.
User
Business
Tomorrow’s
Internet
60% of customers
online prefer it if an
online store remembers
their interests, contact
details and purchase
information
[ ]
Personalization helps
businesses by increasing
conversion, inject users into
goal funnel, retention etc.
Personalization can already be
recognized as the dominant trend
in the industry. delivering
exceptional customer experience,
will turn into key driver.

6. Objectives & Measures
6
Conversion Metric
1. Orders, Goal, sing-up etc
2. Inject into sales Funnel
3. GMV etc.
Objectives
 Conversion: Helps to increase conversion
 User Experience: Enhance User Experience
 Engagment: Increase effetcive engagement
 Retention and Loyality
Engagement Metric
1. CTR
2. Page/Product Views
3. Time Spent etc.
User Experience Metric
1. Qulaitative & quantitative
2. Summatice & Formative
3. Usability feedbacks etc.
Retention and Loyalty
1. Return Frequency
2. Quality Conversion
3. r
Performance and Measure

7. Basic Components
7
Components Explanation Example
Inventory/Items
Inventories are the assets of a website that comprises all information
sets, such as html elements, text, images, audio, video etc. Ideally it
says “what you can” personalize.
Content, text, image etc.
Logics
Logics can be defined at two ends. The back end which involves the
data process, machine learning algorithm, CBR etc. And at front end it
is the concept that dealt with user- like cross sell, recommends,
complementary sell, feeds etc.
Using “Neighborhood models” at back end to find
similar users and items, to recommend “frequently
bought together” (cross sell) at front end.
Users
Users can be segmented on various parameters like traffic source,
demo graphics, logged- in status, buying /goal intention etc.
Traffic+ demographics: User who visit site via
search engine from Canada.
Triggers
It’s the coordination between other components which organizes and
run the show. The decision point of when to show, what logic to show
and to whom to show etc.
Showing personalized trending cricket news feed in
home page to user who has affinity towards sports
> cricket.
User
Logic
Triggers
Inventory
Personalization

8. Users
8 As users can be classified or
segmented on various basis like traffic
source, demo graphics, new/return etc. For
ease of understanding and working, let’s put,
user into strangeness and buying intention
bucket.
Technically, at the edge, personalization (on the
basis of real time/ progressive) can be surfaced to users
whose browsing history is available. Irrespective of any
segmentation (demo graphics, new/existing, Not logged-in
etc... And this is made possible through “cookies”.
Classifying user on the basis of strangeness (known
or unknown) to the site/personalization engine.
Users
Known Unknown
System/Site Intention
Visitor Shopper Customer

9. Intention-User
9
Visitor Shopper Customer/Buyer
Who they are
A visitor is the one who visit your site
and may or may not have an idea of
converting through your site, at the
moment. As similar to one who checks
out the shops and merchandizes in a
mall.
A visitor turns into potential shopper if he
shows interest (custom triggered event) to buy
or initiate the goal (of the site). As similar one
who enters shop and picks (custom event)
dress.
A shopper turns into customer by
entering into the conversion funnel
or completes the site goal (purchase).
What they do
(Custom Event)
Visit to site
By triggering any defined custom event- like
product views, filling forms,performing search
etc. can be attributed as shopper.
Progressing into Conversion Funnel
or activates the site goal(order/sign-
up etc)
Example
User Searching for “samsung phones”
and visit site as natural traffic.
Triggering events like visit to specific pages or
product views or sales funnel etc.
Performing cart addition or entering
checkout steps or Form Submission
etc.

10. 2.Classifying
Personalization
Calssifying on the basis of mode, logics etc.
10

11. The one of Tree type
11
Personalization
Mode Recommendation Method
On-Site Off-site
Instant Real time/Progressive Predictive
User Known User Unknown + Known Known (processed)
Level
Element
Product
Page
Experience
Page
Product
Element
Experience
Page
Omni- channel
Data
Generated &
collected
from User
Generated
from User
Processed Data
-Touch Points
-Emails
-App Notification
-3rd party space
Multi to 11 to 1
Data Generated Collected + Generated
Over the industry,
personlization is being talked or
infered differntly in varying
concepts and terms. I took a
method which equates to ceratin
usage process.

12. On-Site Personalization
12
Instant
-Instant are those types were
personalization is available instantly as
user lands on site. Happens only when the
user is “known”. Combination of collected
and generated data of user is used for
personalizing.
Ex-Recommended for you widget
Real Time/Progressive
- Progressive personalization works well
with New/Unknown Users. Where users
are initially identified by explicit mentions
(devices, demographics etc.) and
personalization happens gradually
through browsing patterns.
Ex- Recently Viewed Items Widgets
Predictive
-Predictive personalization involves
observing implicit behavior and the types
of activity a customer engages in past and
using those observations to determine the
likelihood of future explicit behavior.
2.Known user
Real Time Progressive
1.Unknown User
User
Genrated DataBrowsing
Collected Data
Observation +
Processing
Predective Personalization
Ex- “we thought you might be interested”
Showing travel offers for upcoming Christmas,
to a user who usually travel during Christmas.

13. Recommendation Method
13 1 to 1
Mechanism
Involves processing of one’s own on-site
behavior patterns and other data to
optimize Personalization. The scope of
personalization limits to that user.
With concept of “social proofs’, it Involves
processing similar behaviors and the types of
activities engaged by other users and using those
insights to Personalize with current user.
Multi to 1 (M to 1)
Example (widget) Inspired by your browsing People who viewed this also viewed
1 to 1
M to 1
Known User Unknown User
-Instant
ex-recommended for you
-Predective
ex-Frequently bought
together
-Real time/Progressive (collected data)
ex-People also viewed
-Real/Progressive (generated data)
ex-inspired by your browsing
Mappping the segments
1 to 1 M to 1

14. 3.Levels of
Personalization
Inventories and penetration
14

15. Levels of Personalization
15
Level Explanation Example
Element Level
Any web page elements like images, text, banners, html can be
personalized.
Keeping
Product/item Level
Here Products can be defined as combination of elements, which
defines the key object of site. As by combing elements they
provide core experience to user.
It can be the combination of image and text to
represent a product to buy (ecommerce) or a
article (in content site) or a profile synopsis in
matrimony site.
Page Level
Page personalization Combines element + product. Combination
of these(element & product) can align and turn, almost a whole
page into a personalized experience.
Amazon’s home page, facebook feed, my yahoo
etc.
Experience Level
It’s the overall UX impression the impacts user. Experience level,
will attributes from elements to page level.
As small as personalizing “Preferred payment
mode” or an entire page to reactance/magnetic
etc.
Level/scope of personaliztaion
Content
Page
Experience
Element
Product
Keeps Evolving

16. Deep dive into Experiences
16
Reactive/Responsive UX
In this experience almost entire
site will align to the “user” based
on his/her browsing history and
other sourced data. It may happen
through any combination- page,
elements, product etc.
Example:
www.amazon.in where almost all
the home page element are tuned
to user’s browsing history and
predictive interests. This is made
possible through various widgets
and elements like “Recommended
for you”, “You recently viewed”
and other category specific
suggestion
Captivate or Magnetic UX
This is a commonly used User Experience
design. The approach is to provide
attractive (magnetic) or likely experience
that goes well with most of users. This
approach shrinks the personalization and
give hands to generic template approach
to all type of users. Simply put, they can be
defined as the user experience which is
partly driven by business.
Example:
www.newegg.com Here the web page
elements are tuned to user-business
specific. Similar to amazon, they provide
user experience through web elements like
“trending now”, “best sellers”, “featured
products”, etc. which are common for all
users.
Immersive UX
Is a kind of avant-garde which focus
on specific concept(s) or core
value(s) of the site or organization.
This is extensively innovation driven,
focusing primarily on user
experience and constantly carrying
out experiments with risk involved.
This approach also streams in native
Ad-on Features to enhance the
complete suite of user experience.
Example:
www.filpkart.com provide intuitive
user experience through mobile
device, which is easy and on-the-go
for users. They also built extreme
native Ad-On features like “ping"
which engages socialized buying
experience.
For more info click here

17. 4.Connecting the
components
Walk through the process
17

18. User Journey
18
1 Known Unknown
Level of
personalization
Product + Page+
element + UX
--
Widget/Items
to show
Recommended for you,
profiles you might like
Best Sellers,
Trending
News etc.
Target 1 to 1 and/or M to 1 M to 1
Experience Reactance Magnetic
3 Known Unknown
Level of
personalization
Product + Page+ element + UX
Widget/Items
to show
More items to consider, frequently
bought, more people to connect (linkedIn)
Target 1 to 1 and/or M to 1
2 Known Unknown
Level of
personalization
Product + Page+ element + UX
Widget/Items to
show
You might like, similar items, people
who viewed this also viewed
Recommendation
method
1 to 1 and/or M to 1
Visit to Site as visitor
Triggering Custom Event
like page views, search,
filling form etc
Triggering Custom Event
like cart addition, sign-
up etc.
Dynamically optimize personalization

19. Walk Through
19
User
Strangeness Known
On-Site –P Instant
Page Home page
Level of
personalization
Product/Page/element/UX
Logic (say) Recommended for you-recommend
Data Used Collected + Generated
Experience Reactive/immersion
Custom
event
Visit to category page + product views
Triggers
Page Home page
LOP
Product + Page+
element + UX
Logic
Inspired By Your
browsing
Add to cart,
checkout process
order confirmation
Page Home page
LOP Product + Page+ element
Logic
Cross sell- Also
bought/recommended for you
Visitor
Shopper
Customer
Strangeness Unknown
On-Site –P Progressive
Page Home page
Level of
personalization
Non for 1st time visit of the session
Logic -
Data Used Generated
Experience Magnetic
Triggers
Page Home page
LOP
Product + Page+
element
Logic
Inspired By Your
browsing Add to cart,
checkout process
order confirmation
Visit to category page + product viwew
Page Home page
LOP Product + Page+ element
Logic
Cross sell- Also
Bought/recommended for you
Custom
event
Via Search Engine- logged-in user Via Search Engine Non-logged-in user

20. Hosting-Over view
20
% of personalization
Decide the type of
experience to be hosted
through site (reactance,
magnetic etc)
Methods & Kick start
Start with real time & instant,
such that all differnet user
types are covered. And
gradually build predective.
Elements to page
Based on site’s key metric
(purchase, sign-up etc)
choose the inventories to
personalize.
Set-up
Define rules, triggers action and
M to 1 and 1 to 1 functionalities
through 3rd party or in-house
capabilities and dynamically
host the inventories and logics
to personalization.
Optimize
Monitor and optimize the
performance of items by
constantly tuning the front end
& back-end logics, screen real
estate placement, triggers etc.
Measure
Measure the performance by
contribution share, page
level performance, or
engagement metrics (CTR,
impression), usability etc.
Personalization
Site and
components

21. Personalization Under
Customization
Driving Personalization via customization
21

22. Personalization under Customization
22 Customization
Is an explicit mention of interest or control over the segment.
“you’re what you say” simply it is the concept of self-profiling.
Like preferred mode of payment, delivery address, interested
category/section, gender etc.
Ex- Amazon user admin panel is an example. where you can
customize their preferences (what you like what you don’t etc).
Personalization
Is an implicit mention of interest. So “you are what you click
and/or what you buy” etc. Basically the prediction insight
from your behavior observations. It is the auto/system
profiling.
User
Age, Preferred
brand/category,
payment method
etc.
Customization
Personalization
With more
weightage to user
preference
Input from User
User
Preference: sports and science
Customization
Website feed
tunes to sports
Assume: Within sports if user spends more with “tennis”
then feeds get more refined to tennis updates.
Personalization
under Customization
Over View:
Example:

23. Big Data World Thank You
-Parkavi Vasan (aka) Divakar