Dec 7, 2021
Dec 7, 2021
You’re here because you’re probably wondering:
We’ll answer all your questions and more. Stick to our advice and this is the only guide you’ll ever need! 😉
Customers expect brands they love to deliver personalized experiences across touchpoints. And, what type of message they receive plays an increasingly crucial role in building long-lasting relationships. 77% of marketers said that real-time personalization to individual customers is essential to them. As a result, customers quickly judge and take prompt action based on the personalized experiences they receive.
In the past, brick-and-mortar store owners had to remember their frequent customers’ names, choices, purchase preferences, and lifestyles of their most loyal customers, leveraging all this information to provide a delightful and memorable experience.
Lucky for you, having a good memory is not something you have to worry about. The world moved on from brick-and-mortar stores to app stores. And there’s one magic source to help you boost your mobile app engagement — data!
Today, technology enables businesses to collect customer data like demographic data, anniversary dates, and purchase history to deliver personalized customer experiences. Mobile app brands use unified data to address customers by their first name and recommend products based on their gender, location, and past purchase behavior.
We’ve entered into an advanced mobile marketing era where customers are more aware of how brands communicate and have the power to choose which apps communicate with them. Customers today expect personalized and targeted marketing from their favorite brands. Sending the same push notifications or same discount offers to everyone doesn’t work anymore. And it doesn’t really help in increasing mobile app engagement, either.
That’s why mobile app marketers consistently try to restructure their tech stack to deliver best-in-class and individualized experiences across channels. When evaluating different marketing tools and technologies, they focus on data and analytics capabilities, personalization technologies, and customer data profile management capabilities.
Evolution of Data-driven Marketing
What is personalization anyway?
Individualization: Redefining personalization to deliver 1:1 experiences
What’s the difference between individualization and personalization?
How does individualization work in mobile marketing?
How to create Individualized mobile app user experiences?
Rethinking mobile app engagement with individualization
Marketing has come a long way. With its evolution, marketers have become more creative, data-driven, and more answerable for results than ever before.
Globally, marketers track their lead generation activities and understand how much pipeline they need to generate for sales to hit their numbers. But from there, things can get fuzzy, with various teams across sales and marketing using different tools and methods to generate the ideal formula for accurate numbers.
When marketing technologies were first introduced, many tools focused narrowly on a single marketing activity—such as individual social media channels or on-page website analytics—and produced data in numerous standalone dashboards.
However, data-driven marketers are more likely to choose marketing technologies that can easily integrate with other platforms to make it seamless to get a consolidated view of the customer journey and connect with the bigger picture.
The concept of the floating sales funnel indicates that every customer goes through the same buying process. But today’s data-driven marketer knows that in the age of omnichannel marketing, the only constant is your customer’s expectation of consistency on every channel. For business, this means bridging the gap in understanding between marketing channels to gain a complete picture of an individual’s buying cycle.
Personalization is a marketing technique that uses customer data to deliver messages to a targeted audience segment at the same time. Personalized marketing typically uses general customer data such as user logins, visit history, most visited category, and past purchases to split users into target groups. Instead of sending random broadcast messages to the entire user base, personalization sends highly contextual messages at the right time.
Customers have long-expected brick-and-mortar businesses to cater to their needs. Today, most companies can analyze online and offline data, so basic personalization is no longer a differentiator—it’s what customers expect.
In the not too distant past, customers expected nothing more than seeing their first name in email updates. But today, every business has some level of personalization in place. But the bare minimum will not make your brand stand out or forge ahead of the competition. To survive, achieve your business goals and build lasting relationships, you’ll need to tap into advanced personalization methods that bring you closer to your customers’ wants and needs. And what happens when you give people just what they want and need? They engage with it. Up goes the number of active users and your mobile app engagement!
Individualization is a technique that automatically personalizes and optimizes the customer experience for each and every person. It requires greater data unification and analysis, multichannel deployment, and artificial intelligence to predict customer behavior and adjust to their real-time needs.
Let’s say a user visits your eCommerce app to buy a smartphone. Using individualization techniques, you can send the shopper a push notification with an offer, including their latest browsed products, related recommendations, top-selling phones, and more to boost mobile app engagement metrics and achieve higher conversions.
Take it a step further. When a user adds an out-of-stock phone to their wishlist, you can send them a push notification when they’re near a physical store carrying the product with geofencing.
Every time a customer visits your app and searches for a product, they share data about their current interests and needs. This information can tell you what they are looking at and provide data-driven engagement insights into why they are looking for a particular product. Armed with all this knowledge, you’ll need to create a valuable individualized customer experience that captivates users at every point of the journey.
However, Personalization and Individualization are often used interchangeably.
Personalization was initially defined as the process of delivering individualized experiences to each person. But in the period of time when the term was coined, few technologies could live up to the intended definition.
Marketers embraced the term and promoted a term that only partially captured the potential of customized experiences with segmentation and product recommendation algorithms.
Today, the marketing industry is in a golden age of innovation. New technologies make it possible to deliver experiences that closely resemble personalization’s original intent. With new tech came new terms such as 1-to-1 Personalization, Personalization 2.0, Individualized Personalization, or Individualization.
Individualization is an advanced form of personalization strategy.
Individualization does not replace segmentation-based marketing or personalization. It adds significant value to your overall personalization strategy. Brands that successfully deliver a seamless customer experience and personalization often use three different personalization strategies to achieve long-lasting customer experiences.
When used in the right combination in the right context, these three strategies can create opportunities and help you achieve your brand’s overall personalization goals.
In comparison to optimization and segmentation strategies, individualization goes one step further by offering a solution to two limitations:
Individualization represents a fundamentally different approach. This unprecedented level of relevance tailored to each user translates into higher revenue and increased customer loyalty. It’s not surprising that individualization has become what app-first businesses aspire to adopt.
Individualization is built on the layers of different kinds of personalization that your consumers receive and respond to. It considers all types of data that you know about the customer, such as user profile attributes, location, past actions, and more. Individualization changes significant parts such as content, visuals, and timing to deliver an engaging and individualized app user experience.
Individualization heavily relies on artificial intelligence (AI) powered technology to deliver a personalized experience to each customer based on all the available data. The customer data is continuously updated based on their current preferences, browsing patterns, and action-driven behavioral data. As the data is continually aggregated, AI makes it possible to improve each individual’s personalized experience consistently and at scale.
A personalization engine makes it easy to test and optimize, segment and target, and even create true 1-to-1 experiences. With all this in one personalization platform, mobile marketers have the flexibility to leverage proven strategies and practices to improve the customer experience not only on the mobile app but across all digital touchpoints.
To enable brands to create meaningful individualized experiences, a personalization platform should deliver on the following key promises:
Using a Customer Data Platform (CDP) as part of your app marketing and engagement efforts enables you to:
When armored with AI-powered predictive audiences, you can:
Imagine you are an eCommerce brand, and a customer has been browsing blue jeans on your mobile app. They find a pair they like and add it to their cart, but leave your app before they complete their purchase. This poses you an opportunity to send them an abandoned cart reminder message with a picture of the jeans they selected and a direct link to complete their purchase. Real-time interaction with customers helps you build stronger bonds with them and cultivates stronger brand loyalty. A larger percentage of users will more likely come back. User retention rates relate strongly to your loyal users – and a loyal user is an active user!
This is where a Mobile App Analytics platform helps you in delivering individualized experiences to a greater level. It also helps in creating individually targeted user experiences at scale. Using these analytics, you can create different segments based on user actions and behaviors. Targeted and individualized push messages delivered to these users’ segments can significantly uplift mobile app engagement rates.
Using analytics is a great way to get to know your new and existing users, including those who have fallen out of the marketing funnel, and how to win back your churned users. By analyzing the data retrieved from in-app user behavior and profile data, you can inform your marketing strategy to win users back with individualized messages and in-app experiences.
According to a study by Salesforce, customers who clicked on product recommendations are 4.5x more likely to add items to their shopping cart and 4.5x more likely to complete their purchase. Wouldn’t you say this is the ultimate goal when trying to increase mobile app engagement? This ability to orchestrate customer lifecycles with the right marketing technology stack to provide the most relevant product recommendations to the individual in real-time is invaluable.
For example, suppose a customer is looking for a given type of television set. In that case, you can send recommendations of products based on the size of the display, the technology browsed, and the best sellers in the category. To achieve this level of personalization, you would need to leverage an AI-driven recommendation platform that can help you in delivering an individualized app experience.
There has never been a bigger opportunity to build brand preference and increase mobile app engagement by delivering individualized experiences across channels.
But marketers have to recognize that personalization isn’t just a marketing tactic. It’s a strategy that focuses on the entire business-to-customer relationship and manifests not only on the mobile app but across touchpoints at every stage of the customer journey. However, the strategy becomes challenging when mobile marketers mistake true 1:1 personalization with traditional, segmentation-based personalization that fails to deliver the individually relevant experiences their audiences expect.
That’s why brands at the forefront of innovation are taking personalization to a whole new level by delivering hyper-personalized or, in order words, individualized experiences.
Experiences can only be as powerful as the data and tech underlying them. Therefore, brands raising the bar in customer experience delivery are leveraging artificial intelligence and big data to deliver real-time experiences that truly engage and convert.
Written by
Nicolas Algoedt
Passionate about new technologies and e-commerce, Nicolas has held various position at leading e-commerce and tech companies including Groupon, Microsoft and Bwin.