Foreword
When it comes to personalisation—tailoring a product, service, or experience to specific customer segments—many organisations across industries are already investing in this area, and reaping the rewards. When executed effectively, strategic personalisation initiatives, from personalised product offerings and recommendations to dynamic pricing and personalised webpages, can drive significant revenue impact. They also tap into the power of customer- centricity, helping foster greater customer loyalty and retention. Such tactics add value for both the brand and the customer by delivering the most relevant offers and experiences to the right customer segments.
In fact, according to an international, cross-industry executive survey by Harvard Business Review Analytic Services, nine in 10 respondents say customers expect organisations to know their interests and anticipate their needs. Correspondingly, eight in 10 survey respondents say personalisation is important to their organisation’s strategy—and more than half indicate their personalisation tactics are already an important driver of revenue and profits. Even more striking is that findings indicate 81% of respondents say personalisation will be an important driver in 2021, highlighting the important role business leaders expect it to play in the future.
This report explores best practices for personalisation strategy and execution to help online stores and eCommerce platforms pinpoint where to best allocate their resources, and where they may be leaving money on the table.
What is Personalisation?
In today’s increasingly competitive marketplace, delivering contextual consumer experiences is no longer ‘nice to have’ as expected, but is an expectation. Immerse yourself in how personalisation drives communication and builds relationships.
Personalisation for online stores is the process of delivering personalised experiences by dynamically displaying unique content, product recommendations and offers based on past activity, browsing behavior, purchase history, demographics, and other personal data.
Personalisation is increasingly important for merchants who are not only trying to attract customers, but also to increase buyback purchases, boost sales and stimulate conversation. It comes in many forms – from personalised product recommendations on a webshop’s home page or product details page, to abandoned-card marketing emails, to on-board questionnaires that provide consumers with a personalised showroom of items, among many other claims.
What means Personalisation today
Remember seeing your name in an email subject line as if it were a breakthrough in digital marketing? Today, personalisation that offers customers unique experiences that keep them engaged requires a much stronger and more strategic approach, which is essential to be competitive in a crowded market and is getting more and more complex.
Consumers today strive for brands that feel like listening to them, understanding them and paying attention to their specific needs and demands. That’s where personalisation comes in. It is a way of contextualising the messages, offers and journeys they deliver, based on the unique characteristics of each visitor.
Think of it as a growth from marketing communication to digital conversations, with data as a starting point. By collecting, analysing and effectively engaging information about demographics, interests, and user behavior, you can create campaigns, content, and experiences that respond to audiences, you are hearing.
Why is Personalisation important?
Your customers expect it!
The importance of personalisation is easier to understand when you consider your own experience as a consumer. If you are on an online store, are you happy to receive personalised recommendations and offers? What about content that is relevant to you, or related to a product or service that you have recently purchased? Like most buyers, you might want your expectations to be an essential part of your online experience.
The digital age has raised consumer expectations for relevant, contextual and accessible experiences to unique heights. Clearly, consumers have become accustomed to getting what they want, and they strive for the brands that place them at the heart of their tailor made marketing efforts.
Meeting these expectations falls directly on the shoulders of marketers, who need intelligent personalisation tactics if they hope to keep consumers engaged and come back for more.
91% of consumers are more likely to shop with brands who recognize, remember, and provide them with relevant offers and recommendations. Accenture survey, 2018
If you ever prodded to buy something (think Candy 2-for-1 at the cashier), you know that not necessarily every decision to buy is rational – very much of our emotions are driving those decisions, too.
Our emotions are personal to us. And that personal connection is something leading brands discover through contextual marketing to create relevance, encourage loyalty, and ultimately drive their bottom line.
Buyers often buy from brands familiar with them and their patterns, and nothing is more important than feeling them once they’ve made a purchase. If you’re going to do that (which you need to do), you need an effective way to accelerate user data to deliver content and experiences across all channels that feel current, in-context and personalised.
Try to Keep it useful, don't creep
Consumer expectations are important. People know what they want, and they expect to get it when they want it and where they are. To meet these requirements, brands need to create highly personalised communications, offers and experiences, but at the same time in a not too aggressive way.
There are ways to show your audience that you have heard their needs and understand exactly what they are looking for without crossing the line. For example, data may show that a particular customer has a preference for Retro sunglasses.
You can then accelerate that vision in a way they can appreciate by personalising your content and suggesting a pair of flip flops or natural organic makeup.
When you get into a client’s personal space, more isn’t always better. Listen carefully to what your customers are saying and then use the right tactics to make their personal experiences fit and unique.
48% of consumers have left a company’s website and made a purchase elsewhere. The only reason: the experience was poorly curated.
Accenture survey, 2018
Where does The journey begin?
To begin the journey to advanced personalisation, online resources must be able to log data through their eCommerce platform and personalise experiences based on:
- Context: Type of device, Time of day, Weather, Time and Place, Reference source
- Behaviour: Recently visited products and categories, Items from Abandoned Cards
- History: Previous purchase, Member of the loyalty program, Previous email interactions
- Demography and Psychography: Age, Sex, Budget, Emotions, And more…
Aside from these original data points, there are thousands more that could be considered, but one could never take care of them all. Using machine learning, a personalisation platform can consider these different data points as a context to determine what really works best for the customer in real time.
Personalising is more than knowing user’s shopping history!
e-Commerce Personalisation goal metrics
To measure success, a company must first define the objective dimensions for its personalisation efforts. Online stores often use personalisation to optimise for revenue, conversion rate, bounce rate or engagement; but you can also choose to develop your own statistics or choose from a number of other options, including:
- Add-to-cart rate
- Income per session
- Average order value
- Total time on website
- Cart Abandonment Rate
- Average number of page views
- And more…
Personalisation for Multi-device consumers
Customers are increasingly using more than one device to communicate with brands. Online retailers who track their customers across multiple devices can get valuable information about who their most valuable messages are, how often these messages interact with their brand, and how the experiences are present. Statistics show a significant increase in product display, rate, and average order value with personalisation for multiple devices versus one device:
- Product view rate is 88% v. 58%
- Purchase rate is 55% v. 6%
- AOV is $130 v. $115
As a result, customers who reap all the benefits of a more cohesive, personalised experience, can deliver more value to the seller as a direct result of recognition during their visit.
e-Commerce and Omnichannel personalisation
Until now, personalisation has been limited to online channels. Digital approaches are still valuable, but in the eyes of the customer they have one relationship with you – not one for each channel.
That relationship must be consistent across all interactions, whether online, offline, in-store, in email, or on mobile. To create an experience that makes the customer truly recognisable, you need your personalisation platform and strategy in all of these places.
The benefits of omnichannel personalisation include:
- Ability to customise products, content, and copy on any consumer or messaging channel
- Connecting customers’ online behavior to in-store by notifying local stores via their client app when a specific user browsed particular products online
- Linking customers’ online behavior to personalise the in-app experience and trigger relevant push notifications leveraging geofencing
- Enabling a POS feedback loop that ensures that online product recommendations and email ads can be personalised to reflect in-store purchases
how to get ready for The future of personalisation
Personalisation will be a key driver of marketing success within five years. These are the opportunities that companies must develop to stay ahead.
The interesting promise of personalisation is here. Advances in technology, data, and analytics enable marketers to create much more personalised and ‘human’ experiences across times, channels and levels of purchase.
While these opportunities are exciting, most marketers are not equipped to deliver. A recent McKinsey survey by senior marketing managers found that only 15 percent of CMOs think their business is on track with personalisation.
The leaders of personalisation who use modern methods were found to aim for a 5 to 15 percent increase in future revenue and a 10 to 30 percent increase in marketing for efficiency consumption – mainly by using product recommendations and driving communication across individual channels.
Building businesses to win requires the three main trends in personalisation and building the skills and capabilities needed to respond to them.
To make it more personal Three major shifts
We now see three major shifts in personalisation:
- The sympathy scale
Empathy – the ability to connect with each other and understand the feelings of another – is the foundation of strong relationships. By understanding social problems and changing yourself, people build trust. That is simply not easy to do digitally or at scale.
Machine learning changes that, or at least becomes much better at reading and dealing with emotions and moods. More advanced algorithms allow programs to interpret new types of data (visual, audio) and extrapolate emotions much more efficiently than before.
- Amazon has patented new features that its Echo device can detect when someone is sick, such as nosebleeds that indicate a stuffy nose. It then offers an appropriate suggestion, such as a recipe for a soup or cough syrups, some of which can be purchased from the machine for home delivery. Other companies also play a role.
- Kabbex uses machine learning to develop emotional recognition algorithms to sort and map facial expressions such as anger, contempt, insult, fear, and joy. These advances can help marketers communicate with customers in a way that is tied to specific emotions and can provide specific, curated ads for products, for example, that match that mood.
- Physical spaces are ‘digitized’
Less than 10 percent of companies surveyed are currently using personalisation systematically for more than digital channels. That offers a huge opportunity. One area where can have a significant impact is visiting stores.
The research data indicates that face-to-face “offline” experiences are the next horizon for personalisation. About 44 percent of CMOs say frontline workers rely on feedback from advanced analytics to deliver a personalised offering; 40 percent say personal shoppers are using AI tools to improve service; and 37 percent say facial recognition, location recognition and biometric sensors are more widely used.
- Brands will use ecosystems to personalize journeys end-to-end
The customer experience is with different suppliers. For example, a mall, a store and branded products all add to a buyer’s shopping experience. But each one sees and affects only a part of the overall buying experience. Linking these points is a great opportunity in the next stage of personalisation as partner ecosystems enable marketers to provide more stable and consistent experiences to users at all levels of the system. As AI gets better at predicting user needs, personalisation programs can move from one system to another. While the share of global sales through the ecosystems still hovers below 10 percent, it is expected to grow to nearly 30 percent by 2025. Consumer goods, home mechanics systems, automobiles, and a wide variety of digital devices should all be part of a seamless experience for the user.
How to turn The future into reality
Personalisation is seen as a major marketing potential, but we believe it should be a major driver of how online stores enter the market. This is where successful brands should now focus on:
Investing in Basic Consumer Data and Analytics: personalisation is impossible unless marketers have a way to consistently understand the needs of valuable customers. Leading marketers are therefore developing systems that can combine and analyze structured and unstructured data, algorithms that identify consumer behavioral patterns and bias, and analytical capabilities to capture that information. in easy-to-use editing dashboards.
The creation of a centralized customer-data platform (CDP) to bring together paid and proprietary data across different channels is critical. Unlike traditional CRM solutions, CDPs offer machine learning automation that can retrieve internal and external data, connect one customer across multiple devices, cookies and ad networks, and enable real-time campaign execution through connection points and channels. The bests are easy to use too.
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