The Whys, Whats, and Hows of Website Personalization

by Rebecca Viser

Anyone who has had either the fortune or misfortune of talking to me about technology and digital strategy quickly discovers my obsession with website personalization. It is a powerful tool that many large content-producing sites have not taken advantage of, and one that has huge potential for creating more engaging experiences for users.

Benefits of personalization on a content site

For mission-driven organizations, improving those metrics can be the end goal. For membership or subscription-focused sites, engagement metrics are key indicators that you are providing real value to visitors. With non-subscribers, this creates more incentive to pay, particularly for sites with a paywall, and with subscribers, this leads to higher loyalty levels and lower churn rates.

So what is personalization?

There are two primary types of personalization: implicit and explicit. Implicit is driven by what website managers know or can guess about visitors based on tracking cookies or information from IP-addresses. This information makes it possible to change people’s experiences on a website in a variety of ways. For example, a visitor who has an IP-address in India could be presented with features highlighting Indian-focused content on a U.S.-based site. Alternatively, a cookied visitor could be shown features based on what they have engaged with previously, with modules highlighting sports content to a visitor who has already read several pieces on the NFL and WNBA or removing already-read articles.

Explicit personalization changes the experience for a user based on data they have willingly provided, usually through an account. In this case, a logged-in visitor may see features change based on topic preferences or newsletter subscriptions that they have set within an account management system.

What to think about before implementing personalization?

Technological implementation

Regardless of your tech stack, there are likely several paths forward for you. But when you’re dealing with large amounts of content, you need to think carefully about whether you want to build out automated personalization, using taxonomy and other behavioral-based rules, or increase staff workloads to manage more manual personalization.

Automated personalization has the benefit of requiring less staff time on an ongoing basis, and depending on the algorithms you create to drive the personalization, can ensure that you are always featuring new or popular content. Manual personalization is simpler to implement and provides greater control over what is featured, but is difficult to scale, and means personalized modules grow out-dated if not updated regularly.

For automated personalization to work, you’ll need to plan out and implement the data structures needed to support the rules you want, ensure that any needed data is available in user cookies, and build out ways for modules around your site to ingest that data and dynamically update page content based on it. The more automated the personalization, the higher the technical lift is to support it moving forward. Any time you add or remove types of taxonomies, content, or modules, you’ll need to decide how those new items will integrate with the personalization algorithm. You’ll not only need to update the algorithm, but the actual development of new content types or modules using the algorithm may be more complicated. You’ll also need to expand testing beyond the functionality you’re adding to include testing the algorithm to make sure it is working correctly.

Website curation staffing

Tracking success

Analyzing pathing information, paired with metrics like pageviews per session and time-on-site, can help you determine whether your variation is successful For example, analytics can indicate whether you should continue to personalize your homepage based on geo-IP, or instead focus on providing subscribers to topic-based newsletters more content on the same topic. While these are crucial questions to answer, answering them easily may require modifying your analytics implementation or existing reports.


Originally published at on December 15, 2020.

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