The Rise of Personalisation
Wikipedia defines personalisation as
“tailoring a service or a product to accommodate
specific individuals, sometimes tied to groups or segments
of individuals. “
It goes on to explain that
“a wide variety of organisations use personalisation
to improve customer satisfaction,
digital sales conversion,
marketing results, branding, and
improved website metrics as well as for
As technologies have matured over recent years,
personalisation has become a truly powerful marketing tool.
Affordable content management systems offering strong
personalisation capabilities have moved the ability to
provide users with a personal experience away from the
exclusive purview of large corporations, making it available
to marketers big and small alike.
More and more organisations have begun looking to improve
their customers’ experience by prioritising
personalisation, accompanied by the motto “Making our
experience as personal and relevant as possible”.
To the casual observer, personalisation may seem like magic,
mysteriously divining a user’s intention to deliver
them exactly what they’re looking for. Although at
first appearing incomprehensible and intimidating, the
secret to tailoring a user’s experience is somewhat
As Sherlock Holmes said, “You know my method. It is
founded upon the observation of trifles”. Much like
the famed detective, good personalisation employs these
‘trifles’ of data – dropped by all users
– to deliver surprising insights and unique
In this article, we cover some of the common strategies for
collecting and utilising user data so you can walk away
feeling empowered to explore personalisation as a viable
strategy to elevate your customers’ digital
‘Divining’ the User
Understanding an online user is not that different from
understanding a real world customer. A retail assistant in a
store has, broadly speaking, two ways of approaching a
customer who has just walked into their store.
If it is a new customer: Are they alone, with their
partner, a family with children? In each situation their
needs may be different, and so the interaction would
If it is a regular customer: The retail assistant would do
well to remember their last interaction, the
customer’s preferences, the products viewed etc.
In the case of the new customer, surface-level information
(or data) is used to try and improve the customer’s
experience. This ambient data is gathered from general
interactions with the user, without any explicit personal
data being exchanged. Personalisation using this approach is
called ‘Implicit”. Some of the
implicit information we can gather on a user in the online
IP address – and by inference – geographical
- Language settings in their browser
- Device type (mobile, desktop, tablet PC)
- Device details, e.g. model of mobile phone
- Campaign tagging details
- GPS location (permission needed)
- Webpages visited in the current session
- Webpages visited in the past session (via cookies)
- Browser type
In the case of a returning customer, the retail assistant
can draw upon remembered personal information that the
customer explicitly shared in pa previous interaction. This
type of personalisation is termed
‘Explicit’. When delivering
your digital experience, you can tap into data in your
customer relationship management (CRM) systems to extract
such information. Frequently, the following data is
Information related to the customer’s identity;
name, gender etc.
Contact information, including email, phone numbers,
social media accounts, mailing addresses, etc.
- Past purchases
Past queries and interactions with your assets, including
mobile applications, websites, call centres, etc.
Past use of profiling tools, e.g. product recommender,
wealth planner etc.
An experienced retail assistant will use a combination of
both approaches to tailor the interaction specifically for
the customer. A good tailored experience does the same. This
‘Hybrid’ approach combines both
implicit and explicit data to deliver a wholly personalised
At this stage you are probably wondering how the data above
translates into a personal and relevant experience for the
user. How do we go from the data to the magic? In this
section we will look at some examples of doing this.
Hopefully this will give you an idea of how the magic of
Before we jump into examples, let’s cover the key
considerations for constructing personalised journeys.
- Understand your users’ needs and objectives.
This must be the starting point. No personalisation will
succeed if we are not making it easier for users to
achieve their objectives. Avoid the temptation to start
with the data.
- Identify suitable data attributes.
Identify the data that enables you to differentiate the
various user groups and their needs.
- Design the experience.
Armed with the data, ensure each personalised experience
is more relevant to the target user than the generic
Example 1: Personalising News and Events on A University
User insight: The university website needs to serve many
different individuals, from prospective students, to alumni,
to industry partners. The default presentation of news and
events on this site was ordered by latest date, and as such
crowded out the content for niche users. Our goal was to
present every user group with news and events curated for
Data Point: Categorisation into different Personas based on
the user’s navigation history.
Solution: The CMS was set up to support various persona
types; prospective students, alumni, associate teaching
staff, industry partners etc. Pages in the website were then
tagged to specific personas. When a user visited the pages,
their persona would be implicitly inferred from the tags on
the pages they browsed.
The user would then only be shown news and events for their
specific persona, ensuring the content was relevant.
Example 2: Finding Bank ATMs and Branches on
User insight: When users accessed the bank’s site via
mobile phone, they most frequently viewed the page listing
locations of ATMs and branches.
Data Point: GPS location on mobile device.
Solution: We personalised the mobile homepage by having it
show the nearest branch and ATM to the user’s current
location, with easy access to the ATM / Branch locator.
Within the locator, listings were presented in ascending
distance from the user’s current (or specified)
Example 3: Displaying Relevant IDD Rates and
User insight: Our Telco client had a substantial migrant
worker user base, mostly from Indonesia and Myanmar. For
these users, the IDD promotions and rates were most
important since they use their mobile phones to frequently
Data Point: Language settings on browser.
Solution: We personalised the IDD rates and promotions on
key pages to show only the calling rates for the
user’s home country. For example, if the browser
language was set to ‘Bahasa Indonesia’, then
only IDD rates and promotions for Indonesia would be shown.
Example 4: Guiding Users Towards Nearby Outlets
User insight: Many users would visit the client’s
website to find the location and contact details for retail
stores, distributor outlets etc.
Data Point: Country / city inferred from user’s IP
Solution: We personalised the ‘Outlet’ widget on
the website to show the retail store in the city the user
was accessing the site from.
Hopefully this short article has helped to give you an idea
of how personalisation can be applied to your website or