Personalisation

What it is and why it matters

Personalisation uses data and analytics to tailor customer experiences to the individual. Using shopping history, demographic data and pattern recognition data, an individual’s experience can be modified to fit their unique preferences. Offering options that best fit their needs helps the customer to find what they want quickly, giving them more personalised experiences, ideally leading to happier customers and more sales.

History of Personalisation

While personalisation may be thoroughly modern and you might think it’s driven solely by technology, that’s far from true. Personalisation has been around since the first shop owners.

For example, in the 1800s a man might walk into a cobbler and ask for a pair of shoes. The cobbler could look at his customer card to see what size the man wears, how much he usually spends, how much time he spends on his feet – and then make a new pair of shoes based on his previous customer data. Especially in smaller towns and villages, early retailers were likely to recognise their customer and be able to create just what the customer needed. This level of personalisation became scarce after the Industrial Revolution when mass production largely replaced handmade items. As the early stages of the internet eventually came around, personalisation was still not much of a concern and most marketing teams would cater to each customer the same way.

However, the customer experience shifted when web-based companies, such as Amazon, appeared. Web personalisation first took off with Amazon due to its “customers who bought this item also purchased …” feature. And the age of the recommendation engine was born. This enabled grouping of customer segments based on merchandise preferences to be shown to other buyers in the same segment. Today, segmentation is not considered the purest form of personalisation, but it allowed for early personalised experiences and began the growth of the concept tremendously.

Personalisation is key in telecommunications. And analytics is the natural solution.

Learn how telecommunications company Telenor Norway uses real-time data and machine learning to personalise customer offers, enhance business decisions, improve customer service and continuously adapt to customers’ needs.

Personalization in today’s world

Personalization is a keystone for building great customer experiences. Learn more with these resources.

Create meaningful, profitable customer interactions

Understanding customer needs to deliver the products and services they desire is not a new concept. But smart technologies, personalization tools, AI capabilities and ever-increasing customer expectations are all new considerations when crafting superior customer experiences. Learn how to personalize interactions and customer journeys, including what role AI plays when building a customer-centric strategy.

Getting personal with GenAI

Marketers lead the way in adopting GenAI, but they’re barely scratching the surface of its full potential. But there’s good news: 92% are seeing positive ROI when using it for personalization. Dive into the details from a recent survey of 300 global marketing leaders as they discuss their plans for using GenAI.

Deliver exceptional customer experiences 

Personalization is the cornerstone of every successful customer journey. In this blog post, three organizations share how they’re using technology to personally customize offers and communications.

Take control of ad personalization

Organizations have lots of customer data, but they still struggle to deliver relevant and timely messages to their customers. However, delivering those messages becomes much easier – and more profitable – when they’re in control of their ad delivery.

Balancing personalization and privacy

Technological advances, including AI and machine learning, can collect more customer data than ever. While personalization is important for delivering hybrid digital-physical experiences, there’s another element that’s equally important: privacy.

Whether it’s a security breach or government use of personal information, consumers are increasingly wary about how their personal information is being used. 

Marketers must find that delicate balance between tailoring content to improve customer engagement and ensuring privacy to build consumer trust and loyalty.

Balancing Personalisation and Privacy

As technology advances and starts to collect more customer data, people have become increasingly wary of how it affects their privacy. Security breaches, government use of personal information and marketing communications that are a little too personal are making people more on edge about their personal information being shared. This makes it difficult for marketers to know the balance between how much personalisation is going to make someone’s privacy feel violated. As technology expands, it becomes vital for companies to be able to show two things: that they understand the customer and can protect their personal information.

Who’s using personalization?

Banking

Financial institutions are in an ideal position to deliver personalized offers and marketing campaigns because they have so much rich data on customer transactions and spending behavior. As customers increasingly demand digital experiences, personalization is a key component for enhancing the customer experience.

Insurance

Personalizing email and promotions can be overwhelming for insurers with vast amounts of historical customer data. Predictive analytics helps insurance companies personally customize offers to target precise customer needs, helping reduce churn and strengthen engagement.

Public sector

Never have governments and public health been asked to do so much, so fast and with mounting pressures – rising citizen service expectations, fiscal constraints and workforce fatigue. However, digital transformation and personalization are improving service delivery speed, helping the public sector operate more effectively and become more productive. 

Retail

Retailers are making the move to ramp up digital engagement efforts as customer engagement models must consider both physical and digital experiences. Creating custom, targeted experiences using data, analytics and AI leads to increased customer satisfaction and the potential for greater ROI on marketing campaign costs.

Personalized communications and superior customer service

Jyske Bank, Denmark's second-largest financial institution, is proactively improving its customer experience with relevant, timely communications tailored to individual customers' needs. Watch this one-minute video that highlights how Jyske Bank is boosting customer loyalty.

CNM Helps Nonprofits

Nonprofits were one of the many organisations significantly affected by COVID-19. However, personalisation offerings allowed them to keep up with demand and further their efforts during the crisis. Their use of analytics allowed them to build back safer and more healthy communities. Watch this video to take a closer look into how nonprofits fought back during COVID.

How Personalisation Works

Personalisation is mainly accomplished today by using algorithms and machine learning. Algorithmic complexity varies from basic to advanced, but they all offer a degree of differentiation. Basic algorithms might present new products or bestsellers to a buyer. More advanced algorithms for personalisation will be able to identify specific things about a customer and recommend similar items. For example, Netflix uses an algorithm that looks at the shows you watch in real time, and then recommends shows to you based on your viewing data. Decision trees are created to direct you to different paths to find more products related to your known interests.

In many ways, personalisation is the modern equivalent of excellent customer service. Customers expect it and may even become annoyed when the sites they visit do not include personalisation features. When looking at car insurance for a new driver, for example, an insurer who knows the ages of your children and what types of cars you drive can personalise an offer more quickly.

There are multiple approaches to personalization. Here are five ways it's commonly used.

Contextualization

Contextualization focuses on gathering behavioral data (such as past purchases, page views or clicks) to deliver personalized offers or recommendations. For example, a person visits an airline website to check prices on flights to Las Vegas. Later, the airline sends an email reminding them to book the flight or look at other flights.

Hyperpersonalization

Hyperpersonalization uses real-time data, advanced analytics and machine learning to process vast amounts of customer data. Because it uses real-time data, this technique takes personalization to a new level. As a result, offers can be adapted in real time as a customer navigates through a company’s website – delivering an enhanced customer experience.

Real-time interactions throughout the entire customer journey

Personalization offers benefits throughout all phases of the customer journey. For example, it can also be used in retention activities, such as customer support. Real-time decision-making capabilities deliver personalized experiences instantly, such as next-best-action recommendations that call center agents can use while interacting with customers.

Customer loyalty programs

Customer loyalty programs are a great way to increase customer engagement and satisfaction, plus build a positive perception of a brand. Personalization is a fundamental component when implementing loyalty programs – including techniques such as real-time decisioning, predictive analytics, customer data integration and customer journey mapping – that deliver targeted and relevant incentives and rewards.

Ad personalization

Personalized advertising allows brands to deliver targeted ads based on individual preferences and behaviors. Ad personalization is accomplished using advanced analytics, AI and real-time decisioning. Marketing and advertising data are integrated from various sources to build detailed customer profiles to ensure that timely and relevant ads are delivered across multiple channels, including websites, mobile apps and social media. Examples of well-known advertising platforms include Google Ads and Facebook Ads.

Next steps

SAS® Customer Intelligence 360 delivers purpose-built, intelligent marketing for today's modern enterprises. SAS moves brands from data to insight to action with rich functionality for adaptive planning, journey activation and real-time decisioning.