A stand-up comedian has this arduous task of presenting rib-tickling jokes to the audience but it involves proper strategy as well. He would talk about funny instances from the school life if the audience is packed with students. Or, he would talk about the patient-doctor relationship for an audience full of doctors. Business enterprises apply similar web personalisation strategy to tailor the content on the website for their audience.
Segmenting your visitors helps you identify who they are and frame web personalisation strategy accordingly.
To personalise the web experience, audience segmentation is one of the key prerequisites to be adhered to. Segmenting your visitors helps you identify who they are and frame web personalisation strategy accordingly. Drupal has amazing capabilities to enable personalisation on your website.
The Assortment of Audience Segmentation
What is the segmentation and how do you do it? The process of splitting your audience into distinguishable groups based on specific criteria, contexts and/or conditions comes under segmentation. With real-time personalisation, segments of the audience are based on criteria which can either be detected automatically or derived from previously compiled user data.
There are several different categories of criteria on which audience segmentation can be done. Broadly speaking, all these different criteria come under two groups
When the information is implied or assumed, it is referred to as implicit data. This gives you an idea of a user’s intentions or needs but is not plainly conveyed by the user. This data allows you to test a hypothesis, recommend content, or to inform a content experiment like A/B test.
When you derive the interests of a person on the basis of the pages they have visited, such information would come under implicit data.
This kind of data is clear and specific and leaves no room for any kind of doubt. Explicit data can be comprised of visitor attributes detected automatically or the data which a user chooses to provide like their personal information and preferences.
When you tailor your content on the basis of the user’s age, gender, location or the kind of device being used, it comes under explicit data.
Rule-based Personalisation vs Predictive Personalisation
Personalisation done on the basis of explicit data
Personalisation done on the basis of implicit data
When the explicit data is used to personalise web experience, it is referred to as rule-based personalisation. Content is personalised when the specific rules and conditions are met.
Predictive personalisation leverages implicit data to tailor the content to the audience. It helps in customizing offers and communications precisely by predicting customer behaviour, needs, and wants.
Predictive personalisation selects the most relevant content for the audience based on the best performing content variation like a landing page that has led to the most amount of conversions.
Both implicit and explicit data can be used together to an effect to optimise the user experience. Types of Segmentation Criteria used to personalise content on the basis of implicit and explicit data includes:
The qualities or attributes of a specific group of people is what demographics refers to. Demographic criteria for the web personalisation is explicit as the data provided is mostly personal like information given by the visitor through sign-up, form fill or an account registration.
Demographic criteria constitutes:
Where can it be seen?
Online stores recommend clothes on the basis of gender.
Travel companies target promotional campaigns with Indian tour packages for senior citizens.
Geographic criteria is a type of demographic data which can be used to meet the needs of customers in a particular region.
Geographic criteria comprise of:
General region like State/Province
Local time or weather
Where can it be seen?
A news television channel can automatically show news coverage relevant to the local region of the user.
An online retailer can dynamically determine the local weather patterns of the user and show personalised product recommendations. For instance, a sale on sun protection creams for online visitors on sunny days and sale on raincoats for users in rain-hit locations.
The patterns shown in the behaviour of the audience can prove to be a determining user interest. Visitor behaviour mostly includes criteria detected automatically and implicit data delineating the current or past history of browsing sessions.
Behavioural patterns include:
Content topics visited by the user the most
Specific content visited by the user the most
The click path or the order in which the visitor is viewing the content
New visitors vs. returning visitors
Past site downloads
Recent conversions or purchases
Where can it be seen?
A healthcare site can display listicle showing recommended blogs about a specific disease on the basis of other articles visited by the user.
A digital agency can show topical marketing messages on the website on the basis of white papers and ebooks downloaded by the user previously.
Session and other visitor metadata
Personalisation can also be done on the basis of explicit attributes of the browsing session. An Econsultancy report stated that O2, a leading digital communications company, used the data based on the mobile device usage and location to make their ‘tariff refresh’ ad more relevant and tailor the messaging to their consumers. The betterment of 128% was observed through personalised ads in terms of click-through-rate (CTR).
Session attributes consist of:
Browser or Device type
Source or referral type
Authenticated users vs. Anonymous users
Where can it be seen?
A mobile application company can automatically detect the kind of smartphone user is using and deliver personalised promotional campaigns for applications that are compatible with the user’s device.
The homepage of the website of a SaaS-based company can display relevant messaging depending on whether the user has arrived from a direct link, a search engine ad, a banner ad, an organic search engine result, or a partner/affiliate site.
Previously gathered data constitutes user profile criteria. It can include account details from a CMS like Drupal, customer record in a CRM like Salesforce, or a personal information from a social media platform like Twitter.
User profile criteria include:
Customer type or account history
Where can it be seen?
A newspaper website can show a personalised list of news articles based on topics that the subscriber has indicated he is interested in.
A customer at a basic level of service can be presented with a promotional offer to upgrade to premium version.
Promotional messages for a customer can be displayed to renew their membership based on account history data that shows that his or her membership is nearing expiry date.
Segment vs Persona
Grouping of customers and potential customers on the basis of distinct needs
Fictitious characters created to simulate a real customer
What it does
Dictates brand’s messaging, content strategy, and product targeting
Provides insights into the psychological and emotional wants of customers
Used to initially attract a customer towards your brand
Used to keep a customer around once they are interested
Market segmentation and buyer persona may seem similar as they both help in grouping together current and potential customers. But they provide separate use cases for the businesses. Both the tools come handy in depicting how a business should market the product to its customers. And once they have caught customer’s attention, they can also strategise how best to target them to meet their needs and wants.
So we have already seen what segmentation is. Then what are buyer personas? They are fictitious characters created by a retailer to simulate a real customer. Personas are made on profiles that would include foundational information gathered from research done with real people. These profiles directly represent customer groups that share similar values, behaviours and goals.
Personas add the emotional and behavioural component to the customer profiles thereby adding that extra layer of warm fuzzies.
In addition to these basic profiles, personas are used to give names, faces, personalities, and families to delineate accurately what that person would want and need in real life. Thus, personas add the emotional and behavioural component to their customer profiles thereby adding that extra layer of warm fuzzies. Once done, it helps in determining the end goal for a particular customer to target them appropriately.
Leveraging the best of Drupal for Web Personalisation
Drupal provides an amazing platform to personalise the content on your website and enhance user engagement.
Drupal module, Acquia Lift Connector allows an integration with Acquia Lift service to give true insights on what customers want and do not want which helps in serving personalised content. This helps digital marketers to get control over automation, testing and measurement of marketing activities.
This module helps in the unification of content and the insight gathered from various sources about the customers for delivering in-context and personalised experiences across multiple channels.
Features like drag-and-drop user interface for targeting messages, A/B testing, unifying customer profile, syndicating content, behavioural targeting and combining anonymous and known online visitor profiles make it a highly valuable tool to empower digital firms in delivering the most cohesive and personalised experience.
Web personalisation is a useful strategy that can determine an organisation’s engagement ratio with its audience. To meet the needs and wants of its audience, segmentation must be done to understand your customers and potential customers. Audience segmentation is an integral prerequisite of web personalisation which every digital firm must adhere to.
Leveraging the flexibility that Drupal offers in personalising the site, it can prove to be a remarkable platform for businesses. We excel at Drupal services with Drupal Development as our numero uno service and can guide you in building a business website with personalised content.