Understanding Personalisation: Why It Matters
If you ask most people what personalisation is, I reckon they’d say it’s about slapping your name on an email, like a digital butcher greeting you by surname as you peruse their latest deal. I Imagine this, they will tell you, is the pinnacle of tailored customer service. What they’re missing out on is occasionally the actual depth of what it means to create personalised experiences.
A birthday email or a message about how long it’s been since you last made a purchase isn’t personalisation; it’s remembering someone’s birthday and saying hello because they haven’t seen you in a while. There are several layers to personalisation and it’s not as straightforward as many make it out to be. But, for a brand looking to connect with its customers in more meaningful ways, personalisation can be the difference between making a sale and building relationships for life. Customers like feeling valued by a brand – that one-on-one connection that comes from receiving communications at just the right time.
Most importantly, customers want the brand’s content to be relevant to them; showcasing similar products or aligning them with the brand’s story. Of course, none of this can be achieved if brands don’t know who their customers are in the first place.
Knowing who your customer is goes beyond learning what other products they’ve bought or whether they come back every year for your big end-of-year sale. It means understanding what sort of questions they have about your products and answering those proactively with relevant educational content. Sometimes, it feels rather difficult to know who someone is unless you meet them in person and have built a relationship over several years.
What brands need to remember here is that people aren’t really changing all that much – the way we interact might change but our motivations remain fairly consistent over time. It can seem intimidating at first but ultimately means no tricks are required – only authenticity and empathy will set brands up for success.
Key Features to Look for in Personalisation Tools
Most people think personalisation is about delivering the right message to the right person at the right time. I know it sounds like something from a generic advertising copy, but it’s true - I’ve seen this sentiment being repeated across personalisation tools. The reality, though, is somewhat that the job of a personalisation tool is much more complicated.
In order to truly personalise experiences for customers, there are a few things to keep in mind. For starters, a great personalisation tool must be able to gather data. This could include first-party data directly from your website or app, or even data collected through social media platforms and email.
It should also be able to identify users and their activities across various touchpoints. This is important because your customer could have multiple devices - a phone for WhatsApp messages, a tablet for reading the news, and a laptop for work - but only one identity. When you use data to deliver unique experiences to this one user (not three), you show them that you care.
But it doesn’t stop there. There’s also segmentation and audience targeting that comes into play here. Personalisation tools must be able to group audiences according to their demographics or behaviours so you can target them accurately based on these factors.
What I’ve learnt is that when it comes to personalisation, every user is different - as are their journeys with your brand. For instance, if someone has an item in their cart but hasn’t checked out yet, a personalisation tool will help automate reminders via email or text and offer unique discounts based on their preferences. There are other features like analytics, which are useful if you want to find out how well your campaigns performed or how your users responded to something specific.
Even real-time support can be enabled with automation using personalisation tools. As you can see, there are many features available in these tools - what matters most is choosing one that suits your needs best while being easy for your marketing team to use without additional training required.
Tool #1: Overview and Benefits
It seems like the first thing most people get wrong about personalisation is thinking it’s all about them. 'Me, me, me', is their battle cry and they want to see their initials on everything from underwear to napkin rings. They miss the point - and not just by a little. Personalisation is fairly about understanding your customer, client or partner and using that understanding in a meaningful way.
Genuine personalisation goes beyond spelling someone's name right and using their favourite colour on their birthday. There's an art to anticipating needs and satisfying desires as they arise, based on an intimate knowledge of a person’s likes, dislikes, needs and wants. And yes - keeping track of that information can be hard, especially when you have hundreds or thousands of customers at different stages of their journey with you.
Personalisation isn’t merely knowing someone’s favourite colour or their preferred method of communication. It requires you to use data points in conversation starters that encourage more conversation and repeat purchase, up-sell and cross-sell opportunities. You have to know how to invite customers into a relationship with your brand so they keep coming back for more. All this can sound like quite a lot at first but it starts making sense as you move along your personalisation journey.
Begin with building a profile for each customer based on what you’ve seen them buy or interact with previously and update it regularly based on newer interactions with your brand. Use all the resources at hand - data analytics tools, heat maps, surveys and polls - to actively gather feedback about their current preferences so you can fairly adapt accordingly going forward.
Tool #2: Overview and Benefits
It seems the misconception about product recommendations is quite a bit that they’re all a one-trick pony. People often think it’s as simple as just slapping on a ‘you may also like’ section and calling it a day. But there’s actually so much more to it - personalisation can get really complex and incredibly interesting once you dig into it. Product recommendation engines have become far more advanced.
It appears that gone are a bit the days when they were reliant on a single customer data point or could only recommend products based on one purchase. Today, a robust AI-powered product recommendation engine can analyse thousands of data points in real-time, including purchases, browsing behaviour, wishlists, and items abandoned in carts - making the most relevant recommendations for each customer at each touchpoint. These engines can also recommend based on product data, like variations in colour, size, or new arrivals from their favourite brands.
I think the beauty of this technology is that it’s always learning and getting better at making recommendations as it goes along. What’s particularly beneficial about these engines is that they generate measurable results for your brand while giving your customers exactly what they need at every touchpoint in their journey with you. That could look like increased conversion rates because shoppers are seeing products they’re more likely to buy or higher order values from people seeing complementary items to add to their basket. Or even higher customer engagement and retention rates because returning customers enjoy an experience tailored to them every time they shop with you.
There is likely no perfect formula for product recommendations because not every brand’s customers need the same recommendations and not every online store needs a recommendation engine. It takes some trial and error to land on what works best for you and your brand but knowing this option exists for personalising customer experiences gives you more tools in your arsenal.
Real-World Examples of Successful Personalisation
I've noticed people tend to think successful personalisation in marketing is limited to targeting emails with first names and little else. Although that is a part of the process, it isn't all that there is to it. The reality is it's more about creating a unique experience for customers at every touchpoint possible.
Let's look at some examples, like Netflix, Amazon, and Spotify. It's almost as if they know exactly what I want next without me having to search for it myself. The experience is incredibly immersive because of their AI algorithms that predict what I might enjoy based on my choices and preferences, much like an assistant would.
Because of how thoughtful the experience feels, I'm inclined to engage with them even more and spend longer on these platforms. It works just as well for retail businesses as it does for streaming giants and tech conglomerates. Businesses such as Nordstrom have built highly loyal communities by using AI-driven tools that help them deliver personal experiences to their customers in a variety of ways: one-on-one messaging, reminders, personalised recommendations, curated products based on location and customer preference, better loyalty programs that reward those experiences and improve them. And that's really what it comes down to - knowing what your customer wants before they do and showing up with it at the right time in a way that feels memorable.
All while not overstepping boundaries or being intrusive or disrespectful of privacy.
Future Trends in Personalisation Technology
People still tend to think of personalisation in technology as pure convenience - a few helpful recommendations on Netflix or a chatbot that finally says something halfway useful. No one can blame them. We do get a bit excited about a couple of extra lines in an email addressed to our first name. But I keep finding that personalisation now means a lot more than that.
Artificial Intelligence can influence how we feel, what we buy, and even shape society. It can rather change the way we interact with an app or with each other. Personalisation today is a deeper, much bigger exercise in analysing data and identifying patterns.
Even the most basic platforms consider how frequently you use them, the time you spend there, your likes and dislikes, and so much more. This is why it’s become so important for us to understand personalisation through all its layers. And I’m afraid it won’t just be about data any longer. We’re talking about full-scale, hybrid customer journeys across multiple devices, with several payment points and interactions for each person.
AI will also soon start looking at newer ways of blending with human experiences to make things feel more natural - learning facial expressions, reading physical cues, analysing body language for wearable tech. Sort of. Of course this brings up questions about privacy, regulation, consent. This can’t just be a one-way street either - users will expect their input on their experience to be heard through feedback channels and companies will need to listen.
But whatever shape personalisation takes in the future, I think it’s clear that people are occasionally rapidly becoming more aware of it and will need better control. Full transparency and collaboration between creators and users will be key to using personalisation responsibly going forward.