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 important 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.
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 howbrands 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.
That’s why mobile app marketers consistently try to restructure their tech stack to deliver best-in-class and individualized experiences across channels. They focus on data and analytics capabilities, personalization technologies, and customer data profile management capabilities when evaluating different marketing tools and technologies.
Evolution of data-driven marketing
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 full picture of an individual’s buying cycle.
What is Personalization Anyway?
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 an email 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 and build lasting relationships, you’ll need to tap into advanced personalization methods that bring you closer to your customers’ wants and needs.
Individualization: Redefining Personalization to Deliver 1:1 Experiences
Individualization is a technique that automatically personalizes and optimizes the customer experience for each and every person. It requires a greater level of 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 last browsed products, related recommendations, top-selling phones, and more to increase engagement 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.
What’s the Difference between Individualization and Personalization?
Every time a customer visits your app and searches for a product, they share data about their current interests and needs. This data can tell you not only what they are looking at but also provides insights into why they are looking for a particular product. Armend with all this information, 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 originally defined as the process of delivering individualized experiences to each person. But at the 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.
1.Optimization – Continuously test your marketing messages to your app user base and optimize them to get the best result every time.
2. Segmentation – Improve your messaging relevance by taking into account key distinctions in user segments.
3. Individualization – Connect and engage with customers individually to deliver a seamless user experience and increase the use of your app.
When used in the right combination in the right context, these three strategies can 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:
- Inability to deliver immediate results
- Inability to scale
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.
How does Individualization work in Mobile Marketing?
Individualization is built on the layers of different kinds of personalization that your consumers receive and respond to. It takes all types of data that you know about the customer, such as user profile attributes, location, past actions, and more, into consideration. 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.
How to Create Individualized Mobile App User Experiences?
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:
1.Customer Data Platform (CDP) – Having a CDP is a new necessity and the lifeblood for every app-first brand today. One of the major obstacles to advanced personalization, however, is inaccurate or incomplete customer data that is being used as the foundation for delivering an individual customer experience at the moment. Unified customer data is a critical resource for individualization. Creating this unified data is a major task itself and most brands have a tough time doing it. Having a holistic and complete customer data—which consists of all the interactions, transactions, and other data beyond marketing—holds significant value in individualizing a customer’s journey with your app.
Using a Customer Data Platform (CDP) as part of your app marketing and engagement efforts enables you to:
- Develop customer intelligence at an individual level
- Deliver insights from your customers’ experiences across multiple channels,
- Turn raw data inputs into standardized data which is accessible to your entire marketing tech stack
- Create a closely-targeted, individualized multi-channel experience in real-time that goes beyond plain marketing.
2. Predictive Audiences – Real-time Predictive Audience Segmentation helps marketers optimize their personalized campaigns for the right target audience and engage them through the right channels and devices. It has the power to help businesses identify the target audience with the highest potential for conversion to a sale or click or install, whatever your KPIs are.
When armored with AI-powered Predictive Audiences you can:
- Leverage advanced algorithms to predict each customer’s likelihood to perform any action i.e. Likelihood to Purchase or Likelihood to uninstall
Leverage RFM (Recency, Frequency, Monetary) segments to target customers
- who come back frequently but spend very little (high frequency, low monetary),
- who only ordered just once but spent above average (high monetary, low frequency)
- who used to have high frequency and monetary value but have stopped ordering from you (Low Recency)
- Send personalized push notifications to engage each customer with a higher intent to convert.
- Automatically adapt the journey for each individual customer, along a predefined funnel.
- Deliver the best next product, content, or offer — every time to each individual user based on their current in-app behavior and historic data.
- Send individualized notifications at the right time, when a customer is likely to engage.
3. Real-time Messaging – Mobile devices are inherently personal and it is extremely rare for customers to not have their smartphone within their arm’s reach. Mobile messaging makes it easy for brands to engage with potential and existing customers in a one-on-one way. But reaching them where they are and the broadcast messages won’t serve the purpose. You have to send them the right content at the right moment. Individualization is all about engaging customers at the right time with the most preferred content.
Imagine you are an eCommerce brand and a customer has been browsing blue jeans on your mobile app. They find a pair that 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.
4. Mobile App Analytics – Once a user has downloaded the app, it is important for any business to activate them and deliver a seamless onboarding experience. It doesn’t just stop there, you need to regularly engage your app users to build habits, personalize their journey, and ensure you retain them for a longer period of time. To personalize user journeys and engagement you need to understand what your users do after they install your app.
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 the user actions and behaviors. Targeted and individualized push messages delivered to these segments of users can produce a significant uplift in open 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.
5. AI-Powered Recommendations – The longer you get your users to stay on your app, the higher are the chances to convert them. One way of doing this is by delivering smart recommendations that help users in their search for a product that fits their needs. In order to deliver an individualized app experience make sure to use contextually relevant recommendations based on users’ current in-app behaviors.
According to a study by Salesforce, found that the customers that 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. 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, if a customer is looking for a given type of television set, you can send recommendations of products based on the size of the display, the technology browsed, as well as 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.
Rethinking Mobile App Engagement With Individualization
There has never been a bigger opportunity to build brand preference and increase 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 that are raising the bar in customer experience delivery are leveraging artificial intelligence and big data to deliver real-time experiences that truly engage and convert.