Welcome to the second on our series on personalisation: personalisation in action. If you missed the first one, you can find it here. Here’s a quick recap of what we covered:
- Personalisation involves making content directly relevant to your audience on an individual level.
- It’s necessary to cut through the ‘noise’ of the internet and grab increasingly hard-to-engage customers.
- There’s a fine line between ‘personalised’ and ‘creepy’.
- In order to do personalisation properly, you need to gather a lot of user data. This doesn’t make the ‘creepy’ thing any easier to navigate.
This time, we’re going to go a bit deeper into what personalisation in action looks like.
Then, next time, when we’ve got you nice and excited about the fun possibilities of personalisation, we’re going to open that fun can of worms called ‘Data gathering’. But don’t worry about that just yet. Just keep it at the back of your mind for our third and final blog in this series.
Examples of personalisation
Last time, we went through some basic examples of personalisation. We spoke about how platforms like Amazon and Netflix give you personalised recommendations.
Netflix and Amazon use behavioural data to give these recommendations. All personalisation relies on certain data types. You can use any data points you want to give your visitors an intensively personalised experience, but traditionally personalisation data tends to cluster around four categories:
- Demographic
- Psychographic
- Geographic
- Behavioural
We’ve seen how the likes of Amazon use behavioural data. Let’s look at some examples from the other categories:
Personalisation by demographic
There are lots of ways to personalise according to demographic. If you know each customers’ income level, you can tailor recommendations according to what they can afford. If you know their job title, you can send push notifications at times when they’re likely to be off work or on a break. And so on.
Here’s an example of personalisation in action that personalises by job. If someone logs onto the Microsoft page from a personal account, they’ll get the ‘consumer’ landing page. If they log on from a business account, they’ll get the ‘commercial’ landing page. One is tailored to display the Surface Pro’s benefits for individuals, and the other shows the benefits for businesses.
Here’s another example that uses both behavioural and gender data to personalise advertisements. If someone has bought a lot of girls’ clothes in the past, they’ll see the Rita Ora Adidas advert. If they’ve bought a lot of boys’ clothes in the past, they’ll see the Pharrell advert. If there’s not enough behavioural data to go on, the advert will use gender data to decide which ad the consumer sees:
Psychographic personalisation
Psychographic personalisation is all about giving people the kind of content that will appeal to their values, beliefs, personalities, and lifestyles.
Nike is renowned for psychographic personalisation. They’re incredible at appealing directly to pretty much everyone, no matter their athletic ability or preferred style. They do this by tailoring their ads carefully to hit key psychographic points for each audience segment.
Let’s take a look:
Our first example is pretty self-explanatory: you don’t have to be a skinny minnie to wear Nike! There’s something for everyone! You can be proud to pound the pavements in Nike no matter your size!
But here’s the best thing: they’re not just paying lip-service to this inclusivity for marketing purposes: they follow through with plus-sized mannequins to display their plus-sized clothes:
OK, cool! Nike is inclusive of bodies and lifestyles that aren’t traditionally seen as the ‘activewear market’. But what if you are a skinny mini? What if you are an athlete, or an aspiring athlete? Does Nike no longer care about you?
Nope (or, rather, yep – they do care!):
Nike is still very heavily involved with the professional athletics scene. It still makes hundreds of adverts featuring inspirational athletes, so no gym bunny needs to feel excluded!
Here’s where the personalisation comes in: if your lifestyle data skews towards ‘gym bunny’, you’ll get the lean, toned bodies in your Nike ads. If your lifestyle data skews in a more…aspirationally athletic direction, you’ll get the more inclusive ads.
Does it stop there? No. Nike goes a lot further with psychographics.
Over the last few years, Nike has heavily targeted socially conscious consumers. The classic example of this is choosing Colin Kaerpernik – a prominent civil rights activist in the USA – as their brand ambassador back in 2018. This infuriated a lot of MAGA types and enraptured Nike’s target audience. Nike even won an Emmy for the ad.
In 2024, they’re keeping up this kind of psychographic targeting with sustainability campaigns and an increasingly environmentalist ethos:
You get the picture. Nike are great at psychographically personalised marketing. And it works for them. Larger people are reassured by seeing bodies like their own confidently working out in Nike. Athletic people are inspired by the Nike-clad athletes. And the huge groundswell of socially-conscious young people who form Nike’s core customer base love all the ethical stuff.
Geographical personalisation
You might think that geographic personalisation is only useful if you’re trying to reach far-flung audiences all over the world.
You’d think wrong.
Let’s say you’re a brewery based in the South West with customers based from Bristol to Penzance. It’s not a huge geographical area, but it’s still significant.
Someone logging into your website from Bristol won’t find it useful to know that your beer is currently selling at the Pirate & Pasty in Penzance. Likewise, a potential customer in Redruth won’t give a damn that your beer is starting at the Jam Cream First Inn in Barnstaple.
Geographical personalisation will let you show people the closest locations to them that they can find your beer. That doesn’t mean you can’t display all the pubs that are serving your beer at any one time – it just means that your marketing (and your landing page, if you choose to give it dynamic content elements – more on that in a bit) will prioritise what the customer sees based on their location.
Now, a word of warning: geographical can sometimes involve cultural and linguistic elements. DO NOT attempt this if you don’t have a strong understanding of the culture/language you’re targeting.
Take the BT regional phone book campaign, for example. BT attempted to make their phone book appeal to customers all over the country by using their own regional slang:
What’s the problem with this? Well. Here’s the ‘Exeter and East Devon’ version of this campaign.
Are you ready?
OK.
It’s not ‘my luvver’. It’s ‘m’luvver’. The only people who say ‘m’luvver’ as two words are Londoners pretending to be Devonians, and marketers from London trying to appeal to Devonians without bothering to do any actual research.
It came across as extremely patronising.
If you’re asking yourself if a ‘small’ error like this actually matters in the big scheme of things…well, maybe geographical personalisation isn’t for you.
How do you personalise?
So, that’s what personalisation in action looks like in the wild. But how can you implement personalisation on your own website and in your own marketing?
Well, the first step is to decide how you want to personalise. What data points could be useful for you, and how could you alter your content to target each different data point?
Then, segment your audience according to your chosen data points. We’ve got a whole blog on segmentation here – check it out!
Finally, create different versions of whatever you’re personalising. When you’re sending out your marketing, you can tweak intended audiences to make sure that each segment gets the right content.
So far, so good, but what about more individualised personalisation? How, for example, do you get automated emails to address each customer by their first name? And how can you make your landing page show different content for every different visitor?
The answer is dynamic content fields. Dynamic content changes according to the data it has on each viewer. For example, if you have a dynamic content field marked [firstname], your website will greet everyone who logs on by their first name.
How do you get to know their name in the first place? Ah. That leads us right back to that big ol’ can of worms: data gathering.
Tune in next time to find out how to gather data ethically. And not just ethically, but in ways that will make your customers like and trust you more.