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The mystery of digital personalisation

(Image credit: Image source: Shutterstock/Jirsak)

How can retailers and brands implement a truly personal experience for consumers? For some a named greeting on a landing page fits the bill. For others ensuring each customer receives customised recommendations based on previous product purchases suits. What is true of any form of personalisation is that businesses are always trying to leverage known data to provide a specific experience for customers. In doing so, businesses can improve various different sales and engagement KPIs, such as acquisitions and conversion rates, customer loyalty and repeat purchases.    

Let’s consider a recent study conducted by Boston Consulting Group that looks at the personalisation practices of over 50 popular brands. The results are astounding: the report estimates that companies excelling in personalisation today already experience a 6-10 per cent increase in revenue as a result. What’s more compelling is that the research goes on to suggest that over the next five years, across retail, financial services, and healthcare, “personalisation will push a revenue shift of some $800 billion (over £600 billion) to the 15 per cent of companies that get it right.” In short, personalisation is not about growing the pie. It is about cutting yourself a larger slice.   

As ever, the devil is in the detail when it comes to achieving great personalisation in practice - something that many brands and retailers will find daunting. But what else is holding businesses back from embracing personalisation and the benefit it carries? Let’s take the mystery out of personalisation...      

Removing the mystery  

In our multi-channel, multi-device digital age, ideally every interaction with a customer, consumer or client would be certain. Not only would businesses have perfect knowledge about a consumer – where they live, what they have purchased in the past, what images are most compelling to them, etc. – they would know exactly what action is going to convert them into a buyer. Sadly, despite improvements in data architecture, this is still not the case.   

Take a new visitor to a website as an example. From one click you can already tell where they came from, what page they visited and determine whether they have purchased something from the site before in the past. This still leaves a lot of uncertainty. So, you learn from this when a second new visitor arrives. And the third and then the fourth. Each time you’re tweaking the landing page using learnings from previous new visitors. By the 1000th person you know a lot more and you can make bolder conclusions about what you’ve learned. However, few businesses want to wait for all 1000 new interactions to occur before they act on each piece of insight that is gained.      

Making good decisions in the face of uncertainty is the foundation for differentiating your brand – because certainty is rarely guaranteed. The good news is that the right personalisation architecture can handle your constantly changing world without needing to drain uncertainty out of our interactions.    

Moving beyond segmentation 

Most retailers start by looking at ways to improve optimisation, where brands are looking for ways to create an uniform experience (that is, an experience that’s the same for everyone). To improve conversion, you try one or more alternatives. You see how well the experience works for that same universe of everyone, and pick the one that performs best. The problem with this approach is that it assumes everybody looks exactly like the average person in that universe. When you create an improvement on the collective experience, it means that in order to make it better for some people you had to make it worse for others. Quickly you hit a point of diminishing returns.    

The natural thing to do from there is to say, “If I’m hurting Peter to improve Paul’s experience, then I should think about working on these different parts of the population separately.” This is called segmentation. This might start with just one or two, but could quickly move to tens or hundreds of segments. You end up doing the exact same thing over again, improving the average. You say, “Here’s the midpoint of each of these populations. This becomes my universe.”  This offers an improvement over the model of treating everyone the same, but it too has limitations. Each segment you work on is as resource intensive as what you were doing for the whole audience. In fact, it’s more than that, because you have to discover the segments and prioritise them and build infrastructures for giving different things to different people. Your potential benefit is only the incremental improvement to the average for each of these segments. 

That’s where segmentation struggles. The work scales linearly. If you have three segments, you’re doing 3x the work, but you can’t get 3x the return because you are working with smaller and smaller groups of individuals.    

You can’t be all things to all people  

Many approach personalisation with a flawed segmentation framework, interpreting it as creating a “segment of one.” Imagine you are offering ice cream to a stadium of fans. In the flawed "segment of one" model, you’d have to create a customised flavour of ice cream for each person. One person would have vanilla, the next chocolate chip, a third strawberry. This is clearly not scalable when we consider personalising experiences across every website interaction, mobile inquiry or email communication.     

Believe it or not, true 1-to-1 personalisation is something different. 1-to-1 personalisation is about individual decisions, not about building unique, one-off experiences. Instead of trying to create a new flavour of ice cream for every person you meet, you need to decide which of all the available options you have on hand to offer a specific person. In our ice cream analogy that might mean having a dozen flavours to choose from and knowing which is going to appeal most to each person in the audience. The magic comes from building a flexible model that allows us to make a completely unique decision for everyone, even when what we know about them varies greatly.      

This is a significant mind shift from thinking of personalisation as a segment of one. And it’s absolutely imperative we break the old thinking if we want to operationalise personalisation at scale.    

The power of personalisation   

Personalisation is not a mystery. Nor is it complicated or complex. While many retailers have successfully implemented segment based personalisation, which has brought about significant business improvements, Individual personalisation, driven by machine learning is clearly the way forward. Brands such as Club Monaco and Jack Wills have already moved towards this form of personalisation and have seen dramatic improvements to business KPI’s.      

By seeing your customers as individuals – not segments – businesses can interact with them individually and, in turn, gain the benefits of true personalisation.    

Simon Farthing, Director Global Strategy and Insights, Monetate 

Image Credit: Jirsak / Shutterstock

Simon Farthing
Simon Farthing is the Director of Global Strategy and Insights at Monetate, Inc.