Website Personalization: How to Keep Your Visitors Coming Back for More

Published: September 22, 2017 Updated: September 12, 2018 Author Category Personalization

The growing need for customized products and services is what gets the onsite personalization ball rolling. It’s not only about meeting customers’ needs at every touchpoint. It’s also about presenting the right content to the right visitors. Such approach requires a deep understanding of visitors’ needs and expectations on a more granular level. Today’s technology, with its tracking tools and web analytics software, allows you to gain such insights. You then use them accordingly to transform information into personalized experiences in real-time. That’s the way dynamic website personalization works. It supports marketers’ efforts to observe users’ preferences and guide visitors through the abundance of offers. Ultimately it leads them to take an anticipated action: to convert.

As we’ve already discussed in our posts, the idea of personalization is not a revolutionary discovery. One-size-fits-all static websites are becoming obsolete, but not because marketers are coming up with fancy concepts to experiment with. It’s rather because dynamic websites provide users with the service they want and look for.

According to Marketo, 78.6 percent of their survey respondents claimed they would only consider a brand’s offer if it matched the way they had interacted with the brand earlier.

That sets the bar high for onsite personalization. The only way to reach it is to invest time and effort into delivering responsive sites that dynamically modify messages, offerings, banners, and callouts.

Behind the concept of dynamic personalization lies a website that changes on the fly, delivering content that perfectly fits within the framework of the user’s session, generating individual experiences at the site. The process takes into consideration a broad context of visitors’ tendencies and actions across diverse digital channels.

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A small tweak that makes a difference

If we break onsite personalization into pieces, the core of dynamic content is simply HTML content on your website, landing page, form, or search box. Its significance lies in the fact that it changes depending on the visitor’s preferences and behaviors. You set the criteria, and when users match them, you can present a variation of content relevant to them. In this way you may display a “Welcome back” message to a returning visitor, or give a discount on tickets to an event in the visitor’s city. So if you pair your product or service with dynamic content, you boost the whole personalization process and provide a site that suits the visitor’s unique needs.

The driving force of dynamic website personalization

Technology serves marketers to deliver customized content benefiting site visitors so they continue their customer journey without being sidetracked or annoyed by irrelevant messages. As dynamic personalization applies various techniques likes profiling, segmentation and user modeling, the visitor gets precisely tailored experiences aligned with their interests.

The methods used in dynamic personalization are collaborative filtering and machine learning. They are mostly based on aggregated data and algorithms. These are practices extensively employed by Netflix and Amazon in their product recommendations, something you’re certainly familiar with.

In order to make website personalization work seamlessly, you need to acquire data that provides you with the user profile, then with the context of the user’s interaction with your site, and finally tells you about their stage of the buying cycle. The wider the range of information, the more precisely and accurately tailored your content is. So when creating your algorithms, you should take into account:

  • Demography: Age, race, gender, language, etc.
  • Context: Situation in which the visitor views your content
  • Customer Journey: Previously bought products, product categories, average transaction value
  • Psychographic: Habits, likes, interests, preferences, etc.
  • Geo-location: Where the visitor lives and engages with the content
  • Engagement: Past and current visitor’s interactions with your content across all channels
  • Device: Computer, mobile, or tablet

Once you get a grasp on the algorithms, it’s time to bring them to bear. Let’s have a closer look at the adroit practices of Amazon and Netflix. These two giants have mastered the use of recommendation engines. These systems analyze available data to create suggestions for content a user might find interesting. The recommended offers result from algorithms created from available data, both current and historic. Among the array of data, the engines discover patterns which allow you to provide content that resonates with the user’s unique preferences. The recommendations might take form of “Similar Jobs postings”, “Suggested Videos”, “People who bought this bought also this” offers, etc.

What’s more, with the developments in technology, these systems are becoming more and more advanced and flexible in regards to business application. By implementing the recommendation systems, you can analyze whether your suggestions are fine-tuned to your site’s visitors, or if they influence their behavior. What’s crucial to your company is the fact that by acquiring an understanding of how appealing visitors find a particular product or service, you can set things up to meet your business objectives.

Why does your website need dynamic product recommendation?

When visitors come to your site, you want to make them feel as if the offers were designed especially for them. One way to achieve this is through dynamic product recommendation. Applied effectively, it supports engagement while increasing conversions and revenues. This strategy allows you to look for the right products to recommend by taking into account the visitor’s onsite and offsite interactions. But what does it take for efficient recommendations to make it?

There are two approaches. One we’ve already mentioned is collaborative filtering, focused on a product. You can, however, implement content-based filtering, which concentrates on the visitor. The latter is favored for its precision as it hones in on the individual user’s interests and affinities. It relies on similar products or content the same user has interacted with previously. The method employs affinity-based algorithms based on specific products and items that were searched, viewed, bought, or simply shared.

As your visitors and the stages of their user journeys differ, your approach to recommendations should be flexible. For example, you can suggest products that are:

  • similar
  • purchased together
  • most popular
  • most favorite in a category
  • recently viewed

Technology comes handy for these recommendation methods as it offers different ways to put your data in use and meet your business objectives. Product recommendation strategies vary, so you need an engine that allows you to set a broad strategy and to conduct multiple tests so you can make the most of your recommendations.

Why does dynamic website personalization make the grade?

Dynamic personalization offers an efficient way to keep up with constantly changing trends across the web. Most notably, it allows you to automatically create and optimize different variations of ads, banners, buttons, and messages. That’s how it exceeds rule-based personalization. The time you save can be devoted to designing content that matches the criteria you set.

With increases and fluctuation in traffic, alongside changes in visitors’ behaviors, adjusting the content accordingly becomes a formidable task. One of the core strengths of dynamic personalization is its capacity to handle the velocity, load, complexity, and range of data. What’s more, algorithms learn about your visitors and predict their propensities so you can design content that resonates with actual user behavior. All these factors translate into pinpoint accuracy throughout the entire process.

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Final thoughts

Dynamic website personalization has become an inseparable part of digital marketing and we want to shed light how it became as important as it is now. Given the complexity of the strategy, we’ve covered only the most pressing issues. There’s still more to come, but we’re here if you have any questions.

Author:

Karolina Matuszewska, Content Marketer

Content Marketer at Piwik PRO. Specializing in issues of on-site and off-site personalization. Transforming technical jargon into engaging and informative articles dedicated for digital marketers and web analytics specialists. LinkedIn Profile

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