Personalisation, what's the hold up?

The ‘year of personalization’ has been on the cards for a while now. 

A quick Google search, and you’ll find plenty of articles touting 201X as the year that personalization will take off. Midway through 2017, we’re still waiting for it to really take hold.

So, what’s holding personalization back from becoming the norm? Why isn’t every website already perfectly tailored to my individual needs?

There are two main reasons we have yet to see personalization live up to the great expectations.

The first reason is the expectation itself. The dream of personalization as it’s sold – a website responsive to the user’s habits – will likely remain just that for all but a handful of organizations that meet very challenging criteria.

The rest of us have more realistic and practical expectations for personalization where it must prove its worth against many other activities competing for resources.

The second reason is that implementing personalization is a difficult process, and one where it makes sense to start small and build up. No doubt the majority of organizations are starting to explore personalization, but the reason we feel it has yet to take off is because they are still in the early stages. Personalisation is hard. It’s not something that can be undertaken lightly and from a conversion optimization perspective, is only possible if you have already reached the higher levels of experimentation maturity.

Before even thinking about technical capabilities, tools or technology, you should evaluate personalization in three areas: suitability, profitability and maturity.

Certain types of operating model are better suited to personalization and offer more opportunity and potential. If you maintain an ongoing relationship with your customers and see a high frequency of engagement e.g. if you get a lot of repeat transactions as an e-commerce site, then personalization is likely to be more suitable. In general, the greater the frequency of your customers’ visits, the more relevant any previous data about that customer is likely to be, and the experience you create for that customer can be more relevant as a consequence.

On the other hand, for websites that focus on a single engagement, where repeated engagement is unlikely or infrequent, personalization is likely to be far less effective. Those organizations are likely to have limited data about the user and, consequently, it will be more difficult to create highly relevant experiences. Depending on what model your organization operates, you might decide that your website is more or less suited to personalization.

Implementing and maintaining personalization comes with considerable costs. You should only invest in personalization if you can demonstrate that the benefits will outweigh the costs involved. The underlying hypothesis of personalization is that delivering a more relevant experience to a user will increase the likelihood of them converting. As with all hypotheses, this should be tested and validated. Experimentation and testing will allow you to prove the value of personalization for your business, so that is where you should start.

Personalisation requires a deep understanding of user behavior. More so than in A/B testing, we need to understand not just why users aren’t converting, but also how segments of users vary in their motivation, ability and trigger. If your organization is still at the lower levels of experimentation and conversion optimization maturity, then it will be difficult to implement personalization experimentation in a way that is effective and manageable. A good way to think of it is as a higher level of experimentation maturity that you should explore once you have exhausted the gains that could be had from general experimentation and conversion rate optimization.

It doesn’t have to be the 1-to-1 highly granular customisation that people tend to think it is. There are many different ways to approach personalization and the approach that is best for your business will depend on a number of factors.

In order to start your discussions about personalization, here are a few different types that you may want to explore:

• Behaviour-based personalization – This is a great place to start as it has a low barrier to entry. Generally, this type of personalization is based on the user’s behavior on the site during their current session. Altering the content that you show the user when they return to the homepage based on what type of pages they have visited in this session, (or multiple sessions using cookies), for example.
• Context-based personalization – This is where the user’s experience is personalized based on the context of their visit to the site. A basic example of this is personalising landing pages based on the user’s PPC search term, the email they clicked through, or the display ad they’ve clicked. This is more commonly known as segmentation, but really this is just another type of personalization. This can be a good step towards defining the important audiences/segments that would then feature in more advanced personalization.
• Attribute-based personalization – This is what most people think of when they think about personalization: using prior knowledge or attributes about a user to personalize their experience. This type generally requires more advanced technology to connect sources of data about a user together in a way that creates what’s known as a Dynamic Customer Profile for each user. This profile will contain all the possible attributes around which an experience can be personalized to that specific user.
• User-led personalization – Not all personalization has to be invisible to the user. In fact, it could be argued that personalization is more effective when the user can see it happening and is aware that the site is being customised to them. Netflix users know that movie recommendations are based on what they’ve already watched, just as Amazon’s product recommendations are based on what you’ve previously shown an interest in purchasing. This feels more compelling than if you were just shown recommended products without reason.
• Personalisation via predictive modelling – This is the realm of AI and machine learning, where models can be used to assign a user to the best guess ‘lookalike’ audience based on their first few actions on the site. For example, users that visit the ‘Sale’ section of a site within the first three clicks could be assumed to fit in a ‘bargain hunter’ audience. Then any previous learnings about how to effectively convert bargain hunters could be applied to personalize the experience for this user.

I expect we will see a lot more case studies emerging of personalization proving successful as more organizations start seeing the rewards of their investment in this area. If nothing else, I’d expect 2018 to be the year that organizations individually make their decision whether to invest or not invest in personalization in a serious way.

Personalisation isn’t going to be suitable for everyone. The dream of 1-to-1 personalization that runs itself might remain a dream for the majority, but taking the first steps towards investigating its potential is an exercise that every organization should undertake. As preparation, plotting your current position on our experimentation maturity model will help you to plan the steps you need to take to be ready when the time comes.