content personalization

Content personalization is a strategy that tailors webpages and other forms of content to individual users' characteristics or preferences. Visitor data is used to provide relevant content that increases both user satisfaction and the probability of lead conversion.

Frequently used for customer service or e-commerce sales, personalization is sometimes referred to as one-to-one marketing, because the enterprise's webpage is tailored to specifically target each individual consumer. Personalization is a means of meeting the customer's needs more effectively and efficiently, making interactions faster and easier and, consequently, increasing customer satisfaction and the likelihood of repeat visits.

Content personalization, in some ways, harkens back to an earlier day, by making consumer relationships more closely tailored to the individual. When a customer purchases a book from Amazon, for example, the next time he or she visits, Amazon’s homepage will -- like a friendly and helpful sales clerk -- greet the customer by name and offer products in stock that they think the customer might like, such as additional books by the same author, or books purchased by other people who also bought the book that the customer purchased. Many portal sites, such as Yahoo, allow site visitors to customize the page with selected news categories, local weather reports and other features.

In addition to the use of cookies, the technologies behind personalization include:

  • Collaborative filtering, in which a filter is applied to information from different sites to select relevant data that may apply to the specific e-commerce experience of a customer or specific group of customers.
  • User profiling, using data collected from a number of different sites, which can result in the creation of a personalized webpage before the user has been formally converted.
  • Data analysis tools used to predict likely future interactions.

Content personalization methods

Overall, there are three primary methods of content personalization:

  1. Segmentation creates broad target audiences based on demographic and/or behavioral variables. Audience segment groups can be targeted based on age, geography, gender, job title, type of device being used or past brand interactions. Though it can increase the relevance of targeted content for specific users, segmentation does not provide a high degree of personalization.
  2. Persona-based content personalization is similar to segmentation but creates more comprehensive user personas based on more specific behaviors and attributes.
  3. Buyer journey-based personalization maps out where users are in the sales funnel and provides the appropriate content.
Diagram of personalization engine adoption increase
The use of personalization engines has been up by 28% since 2016.

Content personalization and privacy concerns

Because content personalization depends on the gathering and use of personal user information, privacy issues are a major concern. The Personalization Consortium is an international advocacy group organized to promote and guide the development of responsible one-to-one marketing practices. Founding members include PricewaterhouseCoopers (PwC), American Airlines and DoubleClick.

The consortium has established ethical information and privacy management objectives; these include, for example, the suggestion that enterprises should inform users about the information being gathered and the purposes for which it is sought. According to a March 2000 Personalization Consortium survey of over 4,500 web users, 73% of respondents found it helpful to have websites retain their personal information, while only 15% refused to supply personal information online. Sixty-three percent of respondents disliked having to reenter information that they had already supplied.

The importance of customer data

Content personalization strategies rely on information about potential customers to provide individual experiences. Therefore, any attainable customer data is helpful for maximizing the relevance of personalized content.

Customer data collected to provide a personalized experience may include, but is not limited to:

  • Age range
  • Geographic location
  • Job title, industry
  • Search queries
  • Browsing data
  • Time and frequency of visits
  • Device type (mobile, desktop, Android, Mac, Windows)
  • Referring URL
  • Session behavior such as clicks and page views

Examples of content personalization

Spotify, Netflix and Amazon are well-known examples of platforms that use content personalization for their user experiences:

  • Spotify makes song, artist and album recommendations based on the user's past listening history, engagement behavior patterns, and from what other similar user personas also listen to.
  • Netflix works similarly to Spotify's recommendation engine. According to the Netflix website, their recommendation engine relies on viewing history, user interactions with the service, title information (such as genre, release year, cast, etc.), duration of user sessions, time of day watching and device type.
  • Amazon ranks search results and generates additional product recommendations from page views, purchase history and other behavioral data.

Content personalization tools and platforms

Content personalization software tools are data-driven. They work by collecting, aggregating and identifying trends about consumer data. These tools may fall under the categories of customer data platforms (CDPs) or personalization engines.

Examples of content personalization software tools on the market include:

  • BroadVision
  • HubSpot
  • Evergage
  • Adobe Target
  • Optimizely
  • Omniconvert
  • Marketo
This was last updated in August 2020

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