Building brand loyalty, increasing conversions or cross- and up-selling are just a few of the reasons why personalisation is a top priority for successful state-of-the-art digital customer experiences. There are many types of personalisation and some are surprisingly simple to make use of—continue reading to learn more.
Let’s start by having a look at the types of personalisation you may want to consider for implementation in your website, web application or online shop.
Content management solutions come under many labels—CMS, WEM, CEM/CXM or DXP are just a few of the acronyms that have been in use over the past years. A common denominator across all leading platforms nowadays is the inclusion of at least some type of rule-based personalisation and the differences are mostly in out of the box functionality, ease-of-use and flexibility. And to make that clear as well–the lack of at least some built-in and easily accessible kind of personalisation should be among your exclusion criteria when selecting a new platform.
The most basic of data that can be used to personalise your user experience is probably environment data. That is, any general (and often also anonymous) information you can gather from a user and their environment.
Acting based on a user’s date and timezone for sure is one of the simplest rules to implement. But who doesn’t appreciate a simple ‘good morning’ or offers automatically triggered on a particular weekday or bank holiday.
The IP address allows you to easily map users with their physical location and in succession also the pre-selection of a matching site/locale or special functionality. Imagine an offer for a special delivery promotion that differs by location—and don’t forget that what is appreciated by one user (free delivery) can be frustrating for another (delivery actually isn’t free in your region).
One of the more ingenious rule-based personalisation options I have seen is weather-based. When you are able to map the user with a more specific location you can also gather weather data for the region and react accordingly. It isn’t hard to understand why special bad weather promotions work—your own imagination is the limit here.
It is sometimes desirable that the customer experience varies based on how the user accessed it. Put it in simple terms, your website can behave differently when accessed through a specific domain name (with different branding and presentation depending on which one is used). The same goes for accessing similar contents through different URLs which can trigger changes in content, presentation and behaviour. In that sense a product category may contain a personal style guide feature—or not—based on two different URLs for the same page—without the need to maintain multiple pages.
Behavioural triggers are a more refined and a slightly harder to implement type of personalisation. They are usually still anonymous and based on relatively generic rules.
In case you have external links–be it from other web assets you own or from Google ads and similar kinds of external campaigns–you can use that information to show different information or even segment the user. Imagine that a user comes from a special campaign advertising a particular service or product category. As a visitor you would expect to see the campaign or related content promoted on the website you are visiting–in the simplest of cases with a special banner on the homepage of the website you are visiting.
Once you add login protection to at least some features of your online asset there will be some difference in user experience—from adapted navigation options to replacing entire blocks of functionality.
You may want to treat a returning visitor (or customer in case you have that information) differently from a new visitor. In the simplest of examples you can show a ‘welcome back’ message or you can try to continue or extend an already started customer/buyer journey. Or in reverse you way want to present information targeted towards new users such as a beginner’s guide or an introduction to the advertised products or services.
I'm assuming you are familiar with the concept of retargeting—the same approach can be used on your own website. In case a visitor has spent a certain amount of time browsing a particular website area or product category it is probably safe to assume a genuine interest. So why not encourage them to close the deal (or get in contact) by showing special offers or a similar call to action related to that category when they browse back to the homepage or category landing page. These kinds of personalised calls to action are proven to substantially increase conversions. While all of the above may seem relatively simple to implement, personalisation that is easy to maintain and really pays off depends heavily on careful prior planning on a business level. I highly recommend you to first define who you are targeting, why and what you plan to achieve in the long run, before you start working on any kind of personalisation or you even think of moving on to more complex types of personalisation. Besides that it pays off to speak to your technical team to understand what environment and customer data may already bet at your disposal for immediate use.
In certain scenarios the definition of personalisation rules may become a tedious task—that can be based on the large size of your website or online shop, or the dynamic nature of ongoing changes to the content and structure. The same goes for the use of complex personas to work with your personalisation approach. Once you reach a certain number of rules and categories (possible combinations that could be defined as one particular persona) it simply becomes unbearable to manage by hand. In both cases you will benefit greatly from predictive personalisation that is based on artificial intelligence. Here are two examples of what you can achieve:
In smaller websites or shops related and recommended products will be shown based on mostly manually defined rules—based on categories and similar properties, product groups and other metadata as well as manual links procured by your editorial team. That comes with the obvious issue of scaling such an approach and never quite achieves what a personalised user experience can do. AI-based recommendation engines will find the best matching content based on additional and foremost often also dynamic user-specific parameters—with the goal to positively influence conversions. Think about the expectations of a prospect buyer with regards to quality and price. In one case your online shop will benefit greatly from featuring high quality expensive product recommendations, in the opposite scenario this may negatively affect sales. From this simple example alone you start to grasp the potential of recommendation engines.
It is a common and proven method to plan digital customer experience based on personas. We use personas as well during the concept and design phase of our client engagements. In larger projects however you may face a number of problems with this approach. Your customers may be a lot more complex than you can handle with a reasonable number of personas—and it is also likely you forget about a particular combination of behaviours and properties that would define yet another persona to target. AI-based personalisation engines can help you solve this problem. Imagine how convenient it would be if the definition of personas was based on actual user behaviour and the data collected from all users. You end up with a much more tailored user experience for each and every user. And besides that you gain valuable insight on your users (beyond simple statistics) that may not only give you information about the popularity of your content but about which combinations of content are popular and work. It is not uncommon that this approach leads to the re-definition of the default personas to target—as personas still remain a useful planning tool that is easier to grasp than completely dynamically composed target groups.
Personalisation is becoming a standard in many websites and digital commerce solutions in particular. Luckily nowadays there are plenty of means to provide your visitors or buyers with a personalised user experience—some of which are actually a surprisingly low effort to implement compared to what your users and your business gains. The definition of personalisation strategies however requires both a good understanding of your business (to decide where personalisation actually makes sense and may positively influence conversions) but also the right tools and technologies (and the ability to make effective use of those).
Here are a few basic steps to guide your personalisation project:
Be prepared—define your personas based on demographic, behaviour or context, and know what is possible.
Personalise with a purpose—understand what you are trying to achieve and then define how you are going to implement that strategy.
Know what you can achieve—meaning only do what you can also maintain and keep alive in the long run.
Measure, learn, refine—be prepared to continuously adjust your personalisation strategy based on real user data.
And here are a few thoughts on the factors that go into this process overall. As already mentioned, understanding your personas and customer segments is a key ingredient for successful personalisation strategies. Then, another major factor will be the amount of content you are dealing with. Do you have the editorial capacity for all the content that needs to be created and also the A/B/n testing that you should start doing (if you aren't already). And lastly, you need to understand what level of automation you can achieve (e.g. in direction of transactional emails).