The Growing Ubiquity of Personalization

We see varying degrees of personalization on a regular basis and it is essential for making products relevant to users.

Dickey Singh on March 4, 2017

Demand and Expectation

Customers expect and demand exhilarating experiences every interaction. Since no two customers are the same, personalizing content, channel, user interfaces, experiences, and messages goes a long way in progressing customer relationships. Showing highly relevant content to individual users increases engagement and conversion every time customers interact with your web or mobile app.

Personalization is ubiquitous

We see varying degrees of Personalization on a regular basis.

Almost 90% of customers expect personalized experiences and close to 98% of large organizations are personalizing content in one way or the other but in varying levels.

Products and services personalize experiences and interactions to create highly relevant experiences with users to provide better engagement, experience, retention and ultimately growth.

Personalization vs. Customization and Configuration

Configuring a car is not personalization, but it gives clear insights to the marketers what an individual or groups of individuals are selecting.

Serving content based on explicitly stated preferences is using explicit feedback to drive personalization. Apple Music, LinkedIn Pulse has long used explicit feedback to jump start building personalized content for new users.

Personalization is valuable with Customization and Configuration

Personalization is not analogous to customization and configuration, but personalization along with customization is useful in providing relevant experiences to users. Customization and configuration are explicit feedback. However, implicit feedback plays an even more important role in making a product or service personalized for users.


Explicit Feedback

Examples of explicit feedback are giving a 👍🏼 or 👎🏼 rating to a song, or choosing a particular layout and font size in your favorite editor.

Implicit Feedback

Examples of implicit feedback are clicking a call-to-action button, tracking browsing activity, scrolling past a feed faster or slower than average, spending 50% more time on a news feed item than average, liking a product, using a product at night between 8 and 9 pm, etc.

Personalization is one-on-one marketing at massive scale

Personalization is one-on-one marketing at a massive scale. Some are subtle, useful and welcome and others are outright creepy and untrustworthy. Relevant personalizations are a win-win for both marketers and users. Irrelevant personalizations do more harm than no personalization at all.

Shift from Customization to Personalization

Personalization has become such an integral part of designing a digital system in large part because it forges a connection with the user. The main goal of personalization is to deliver content and functionality that matches specific user needs or interests, with no effort from the users. The app profiles the user and adjusts the interface according to that profile.

The Shift from Customization to Personalization is driven by fact that customization imposes higher interaction cost.

Various types of Personalization

1. Message Personalization

Email marketing for acquiring new users, as expected, is the most commonly used personalized option. Typical criteria like first name and last name, recipient’s geographic location, demographics, campaign source, etc., is used.

Some marketers use atypical criteria for personalization with much wider success. For instance, what does an email address ending with — as opposed to — tell you about the user? What does an email address ending with tell you about the user?

Personalizing email content for transactional emails for existing users is not as widely used highly efficient. Personalization works wonders when you know about your users. In addition to using geographic location and demographics, user profile data, past sessions usage history can also be used in personalizing message content.

A personalized end-of-the-month fitness report complete with goals, text, and graphics is an extreme personalization only relevant to the person it was created for.

Similar to email, SMS, MMS, push notifications, local notifications and in-app notifications are widely personalized.

2. Search Personalization in Product

Google has been personalizing the search results for a decade.

Personalizing search content in a web or mobile app based on user profiles returns content that is relevant to users on the first page.

For instance, when a user who owns a 2009 Porsche 911 Carrera GTS searches for engine oil on an app, he or she could be shown synthetic oils approved by Porsche on the first page.

Such personalized experiences save users time and are appreciated.

3. Pricing Personalization

Personalizing pricing based on geography, past purchase history, browsing activity, search results, prior returns, demographics, income-level, type of device used, weather, time or the year, current market demands is a common tactic used effectively by many vendors.

  • Pricing aggressively before and after Christmas by geolocation is also common.
  • Pricing based on organizational demographics is common in B2B environments.
  • Large digital retailers change prices 3–5 times a day based on some criteria.
  • Dynamic pricing based on supply and demand

Outside of E-commerce, pricing personalization examples include:

  • Surge pricing based on supply and demand is common in ride-hailing apps.
  • In-App Purchases’ pricing can also be personalized by creating multiple IAP items and selectively displaying items for purchase

4. User Interface Personalization

UI Personalization is not so common but highly effective approach to serving different users.

For instance, an expense management web or mobile app could have two interfaces. A user who enters expenses rarely would use a wizard-like interface to enter one expense at a time. A salesperson who enters expenses every week would prefer to add the expenses in a tabular interface.

“You have not used the website for a while. Here is an easy way to enter your expenses. If you’d rather use our expert UI to enter many expenses at once, click on expert mode.”

5. In-Session Personalization

Personalizing content based on real-time activity. For example, depending on how you interact with pins on Pinterest, the web or mobile app can show personalized pins when you scroll down on a page. This technique is used both for paged content as well as infinite-scroll content.

6. Sort, Browse and Navigation Personalization

The order of items shown when users browse or navigate through items on an e-commerce site or app, for smart sort selections like relevance, popularity or featured, is personalized to provide results congruent with user’s brand affinities and profile and preferences. This technique is also known as Personalized E-commerce Category Sorting or Personalized Category Browsing. This is a very effective technique used by retailers with a large number of SKU items.

Navigation personalization is also common in digital surveys. Based on answers to previous questions and what you know about the user, questions or multiple choice answers are skipped or changed. Navigation Personalization provides a much better experience as surveys are perceived to be shorter and personal.

7. Meaningful Interaction Personalization

The age-old and simplest, addressing users with their first name — “Hi John, Would you have the usual latte?” — works great at a Starbucks, but may not impress a mobile app user or add value if you are reaching the user directly on their mobile device via push notification or SMS.

Although addressing a user with a name is a simple form of personalization, I am focused on more meaningful one in this blog. Amazon, for example, makes the communications messages useful.

“Your package with Philips Sonicare and three more items will be delivered tomorrow by 8 PM.”

8. Personalizing best time to reach and channel

Interacting with users at the time they would be most responsive based on past behavioral data, dramatically increases responsiveness. A user may respond to texts in mornings, and another user may respond to in-app promotions on weekends. Personalizing communications channel based on reachability and responsiveness are also useful. For example, mail channel for some users, push notifications for others users, and SMS for yet another group of users.

9. Content Personalization

  • Responsive Content — Serving content, differently to web visitors and mobile web users. Formatting for small screens, not relying on hover tooltips, finger-friendly buttons, etc. are typical examples.
  • Landing Pages — Showing different landing pages to users based on search keywords and what you know about a user, e.g. newness (is it a new user or if returning how long ago did they come before), location, device, etc.
  • Personalization based on purchase history — Personalizing content based on purchase history is a known way to market related accessories to users. Offering Nikon lenses to a user who has previously bought a Nikon Camera body makes sense.
  • Personalization based on user traits — Serving content based on user traits like demographics, device technology (Technographics), usage and behavior, psychographics (lifestyle, attitudes), etc.
  • Personalization based on Sensors & Artificial Intelligence — Changing the app behavior depending on context derived from geolocation, time, and motion sensors.
    “Here is a mix we created just for you, for your morning cardio at 24-hour fitness.”
    The app uses phone motion sensors, time, geolocation, a database of geo-fences of gyms, app genres to determine a songs list. Note, some users may find this creepy, ask for permissions with a valid explanation and have a fallback when the user does not provide a special permission.
  • Proximity Sensors — Changing the app behavior depending on proximity to external sensors, like an iBeacon
    “Seems like you at Sushi-o-sushi, would you like to search for promotions.”
  • Dock status— Changing the behavior of an app when the device is connected to a car or a home stereo dock
    “This is the first time you have connected your phone. Download BMW Apps from the app store.”
  • WiFi Connection — Changing the app behavior when you connect to the home wifi?
    “The kitchen lights have been turned on.”
  • Geo-Fences — Changing the behavior of an e-commerce app when in-store versus at home. An app should be able to detect the environment where it’s being accessed and offer users appropriate in-store or online context-aware experiences automatically.
  • Past Searches — Displaying relevant points-of-interest on a map based on past searches learning and predictions. If Mark frequently searches for sushi restaurants, the map could show sushi restaurants near Mark when he opens the app during lunch time. Similarly, Mary could be shown a jogging path and Mike the time it would take him to pick up his kids from school.

Top Personalization Techniques

Here is a summary of a few of the techniques used to personalize.

Behavioral targeting of individuals

Personalization techniques include extracting tags from content a user consumes and serving new content that contains the same tags. Extracting tags could be discovered explicitly (asking users) or implicitly discovered. Songs, Stories, Product types, Blogs use this method.
E.g. Tumblr uses this method

Recommender Systems

Recommender Systems aims to improve customer experience through personalized recommendations based on prior implicit and explicit feedback. Users are first classified into groups and then the personalization is based on the group they belong to.
E.g. Amazon uses this method for “people who bought this also bought…”

Collaborative filtering

Collaborative filtering is predicting whether a user would like a product based on products liked by similar people. Collaborative filtering, however, does not work well with too much (scale) and too little data (sparseness). The sparseness and scalability issues have been solved by the alternating-least-squares with weighted-λ-regularization (ALS-WR) algorithm Large-scale Parallel collaborative filtering for the Netflix Prize. Collaborative filtering can go wrong and produce creepy results.
E.g. Netflix uses CineMatch and a variation of Collaborative Filtering.
Pinterest uses a combination of behavioral targeting and collaborative filtering to serve new pins in real-time based on user actions within the same session.


After classifying users into groups based on segmentation techniques for example as outlined in my earlier post, curated content is shown to users.

Algorithmic curation

When curation is accomplished by an algorithm using traditional supervised machine learning.

In-session Personalization

Personalizing content when a user scrolls down a web page or moves to another page is becoming a popular way to keep providing value to users. I’ll blog about this in the future.



In conclusion, Personalization is essential for making a service or product relevant to individual users. It is known to increase conversion, engagement, and retention — the three critical ingredients of growth. It is never a good idea to over-personalize. You have to create a balance between security, privacy, and personalization. Avoid invading customer privacy by personalizing on sensitive topics like pregnancy. Personalization should always help the user and marketers should only collect information they need and be transparent about the information collected.