The long and short of successful personalisation on social
There’s a big difference between being relevant to people and personalising your communication.
Personalisation is the industry’s attempt to bring together two effectiveness drivers — conversion (short term) and demand generation (long term).
The big challenge is you can end up doing neither.
When it comes to driving conversion, relevance works really well. It enables a brand to ensure the audience receives the right offer and right product, at the right time and in the right place. Essentially, it is all about signposting.
Too fragmentation, too niche
On the opposite side of the spectrum is demand generation — building scale and getting in front of new customers. The goal here is more about ensuring that a brand becomes ‘distinctive’ in specific spaces and a specific sector.
What personalisation driven by digital and technology tries to do is to bring both of these things together in a single initiative and execution. The logic: a brand can access large media scale to reach thousands (or millions) of people, but still be relevant.
However, the risk with personalisation is that you create too much fragmentation in your audiences and too many niche audiences, which means that you don’t get the scale with any one audience.
You can run out of things to say that are meaningful to that many people. You’ve got to remember that a lot of brands don’t have hugely nuanced messages that can effectively speak to a hundred different audiences.
Added to this, you can lose a lot of the cultural salience that some brands really rely on. If you’re in fashion, or you’re in the automotive sector for example, it is the broader cultural currency that essentially influences people to buy into the brand, so what broader groups of society or communities think of your brand is important.
Build motivations
Another challenge with the personalisation of marketing is that it can miss ‘people in a broader context’.
For example, on a music streaming service, it doesn’t always get the fact that my favorite type of music depends on what I’m doing or what mood I’m in at the time, which is why I choose a focus playlist or exercise playlist. It misses that kind of human mood that is based on context; it doesn’t quite hit the mark very well.
What you can do — which is a little bit more around the people and strategy, rather than a focus on technology and delivery — is to try and build or incorporate motivations into the way you build your audiences.
You absolutely must have an audience that can access and buy your brand. However, it can be beneficial to try and pick out key motivations of what drives that audience, and what are they trying to achieve. Then you get to a model that you can scale, because you’re not filtering an audience down to necessarily just an age (unless it’s crucial that age is important) or a demographic (again unless it’s crucial and you’re there for a demographic).
What you get is a big audience, but you know that they are all after a certain thing and they’re all motivated by the same kind of things. You might have different segments of that, but that means that the comms that you put out, the work that you put out, is going to be relevant without being narrow in reach.
Why Netflix understands what matters most
Essentially, you can still be big and target people, and you can still use technology to deploy that activation. It’s much more of a strategic exercise of understanding people before you get into ‘what can we target?’ and ‘how can we target?’ And it allows you to be relevant in quite a broad way.
An example of this is the Netflix model. It’s not that bothered about whether I’m a man, I’m a woman, 50-plus, or I’m 20. What it cares about is that I really like binge-watching comedies or other genres — it uses this to build out recommendations from my motivations.
This is also where personalisation tech can be deployed to unlock motivations, needs, and behaviors. If the data is good enough, it tends to unearth insights into peoples’ interactions and behaviors which is a lot more powerful than what they say they think of a brand.
For example, if you are able to predict people’s behaviours and engagement patterns — which is where social comes into the equation — then delivering the next best experience can be pretty powerful. And where’s the evidence for this? It’s the social platforms themselves that are amazing at serving up the type of content that keeps you on their platform for ages.
That is a form of personalisation essentially done very, very well.
However, your data has got to be good. Your algorithms must be good. That’s the kind of pressure test, I guess, of personalising advertising.
These are the risks you must balance
We tend to see the types of work that use motivations to plan and personalisation tech to enrich the insight perform much better. This is particularly true in social, where you have to earn people’s attention and engagement and bring them to you.
It is not necessarily like other commercial spaces where you can buy access to that audience and broadcast to them, Instead, you are really competing with all sorts of different types of content, etc. And really must get that balance of ‘how can you be really relevant towards someone’s motivation?’ and ‘how do you scale this?’.
There’s a big difference between being relevant to people — which is understanding them and their needs — and personalising your communication, which is trying to second guess almost what their needs are to some degree.
The risk is that personalisation takes it too far and you run the risk of offsetting short-term efficiency with longer-term effectiveness — so demand generation and conversion need to work together.
It’s all about the collaboration between the short- and long-term.
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