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 advertising.”
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 more ordinary.
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 experiences.
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
- If it is a regular customer: The retail assistant would do well to remember
their last interaction, the customer’s preferences, the products viewed
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 environment are:
- IP address – and by inference – geographical location
- 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 available:
- 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 personalisation
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 experience.
Example 1: Personalising News and Events on A University Homepage
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 them.
Data Point: Categorisation into different Personas based on the user’s
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
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 Mobile
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) location.
Example 3: Displaying Relevant IDD Rates and Promotions
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 address.
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 mobile app.