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How to create personalized user experiences for mobile applications?

A personalization engine makes it easy to test and optimize, segment and target, and even create real one-on-one experiences. With all of this in one personalization platform, mobile marketers have the flexibility to leverage proven strategies and practices to improve the customer experience not just on the mobile app, but across all touchpoints. digital.

To enable brands to create meaningful individualized experiences, a personalization platform must deliver on the following key promises:

1.Customer Data Platform (CDP) – Having a CDP is a new necessity and the cornerstone of every first application brand today. However, one of the biggest obstacles to advanced personalization is inaccurate or incomplete customer data which is used as the basis for delivering an individual customer experience at this time. Unified customer data is an essential resource for individualization. Creating this unified data is a major task in itself and most brands struggle to do it. Have a Holistic and comprehensive customer data, which includes all interactions, transactions, and other data beyond marketing, has significant value in personalizing a customer’s journey with your app.

Using a Customer Data Platform (CDP) as part of your marketing and app engagement efforts allows you to:

    • Develop customer intelligence at the individual level
    • Provide insight into your customers’ experiences across multiple channels,
    • Turn raw data input into standardized data accessible to your entire marketing technology stack
    • Create a personalized and targeted multi-channel experience in real time that goes beyond simple 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 greatest potential to convert into sales or clicking or installing, regardless of your KPIs.

When it has AI-powered predictive audiences, you can:

    • Take advantage of advanced algorithms to predict the likelihood of each customer to take an action, i.e. likelihood of purchase or likelihood of uninstall
    • Leverage RFM segments (Recency, Frequency, Currency) to target customers

      • who come back frequently but spend very little (high frequency, low monetary value),
      • who only ordered once but spent above average (high money, low frequency)
      • who had high frequency and dollar value, but stopped ordering from you (Low recency)
    • Send personalized push notifications to engage every customer with higher conversion intent.
    • Automatically tailor the journey for each individual customer, along a predefined funnel.
    • Deliver the next best product, content or offering – every time to each user based on their current behavior in the app and historical data.
    • Send personalized 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 that customers do not have their smartphones at hand. Mobile messaging makes it easy for brands to interact with potential and existing customers on an individual basis. But reaching them where they are and the messages disseminated will not serve the purpose. You need to send them the right content at the right time. Individualization is about engaging customers at the right time with the most preferred content.

Imagine that you are an e-commerce brand and a customer browsed jeans on your mobile app. They find a pair they like and add it to their cart, but exit your app before finalizing their purchase. This gives you the opportunity to send them an abandoned cart reminder message with a photo of the jeans they have selected and a direct link to complete their purchase. Real-time interaction with customers helps you build stronger relationships with them and cultivate greater brand loyalty.

4. Analysis of mobile applications – Once a user has downloaded the app, it is important for any business to activate it and provide a seamless onboarding experience. It doesn’t end there, you should regularly engage your app users to build habits, personalize their journey, and make sure you stick with them longer. To personalize user journeys and engagement, you need to understand what your users are doing after installing your app.

This is where a Mobile application analysis platform helps you bring personalized experiences to the next level. It also helps create 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 sent to these user segments can produce a significant increase in open rates.

Using analytics is a great way to get to know your new and existing users, including those who have exited the marketing funnel and how to win back your unsubscribed users. By analyzing data extracted from in-app user behavior and profile data, you can inform your marketing strategy to win back users with individualized messages and in-app experiences.

5. AI-based recommendations – The longer your users stay on your app, the higher the chances of converting them. One way to do this is to provide smart recommendations that help users find a product that meets their needs. In order to provide a personalized app experience, be sure to use contextually relevant recommendations based on current user behaviors in the app.

According to a salesforce study, found that customers who clicked on product recommendations are 4.5 times more likely to add items to their cart and 4.5 times more likely to complete their purchase. This ability to orchestrate customer lifecycles with the right stack of marketing technologies to deliver the most relevant product recommendations to the individual in real time is invaluable.

For example, if a customer is looking for a certain type of TV, you can send them product recommendations based on screen size, technology they are browsing, and top sellers in the category. To achieve this level of personalization, you need to take advantage of an AI-powered recommendation platform that can help you deliver a personalized app experience.

Rethinking mobile application engagement with individualization

There has never been a greater opportunity to build brand preference and increase engagement by delivering personalized experiences across all channels. But marketers need to recognize that personalization isn’t just a marketing tactic. It’s a strategy that focuses on the entire business-customer relationship and manifests itself not only on the mobile app, but through touchpoints at every stage of the customer journey. However, the strategy becomes difficult when mobile marketers confuse true 1: 1 personalization with traditional segmentation-based personalization that fails to deliver the relevant individual experiences that their audiences expect.

That’s why brands at the forefront of innovation take personalization to a whole new level by delivering hyper-personalized or, in order, individualized experiences. Experiences cannot be as powerful as the data and the technology behind them. Therefore, brands that are raising the bar for customer experience delivery are harnessing artificial intelligence and big data to deliver real-time experiences that truly engage and convert.



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