Segmentation Strategies for Personalized Push Notifications

In this blog, we’ll discuss:

• What is a push notification
• Effective ways to segment users
• Segmentation strategies for personalized mobile app push notifications
• Implementing these strategies across Android and iOS.

We’ll guide you through using mobile app push notifications to engage your audience, build loyalty, and keep your customers coming back.

Push Notifications: What They Are and Why They Matter

What is a push notification? You see that alert on your phone or tablet from your favorite app, notifying you of something important. App or mobile push notifications can be sent to your device whether you’re actively using the app or not. They’re like personal digital nudges designed to keep you engaged with the apps you love.

There are two types of push notifications:

• Mobile Push Notifications: Alerts sent to a mobile device’s home screen. These messages keep users in the loop, whether it’s about an abandoned shopping cart or a limited-time offer.
• App Push Notifications: Alerts are delivered directly through a specific app. For example, fitness apps might notify you about your weekly workout stats.

Benefits of Push Notifications:

• Increased Engagement: A new report from Leanplum analyzed over 1.5 billion messages and found that while only 1.5% of people open a generic mobile push notification, 5.9% open a personalized one. This shows that customized push notifications can significantly boost user engagement.
• Improved Retention: Mobile app push notifications help you stay top-of-mind with users. Through timely reminders and relevant offers, apps encourage customers to return and use their services.
• Precise Timing: The report also shows that notifications sent when users are prone to open an app have a 5.3% open rate. It’s all about catching them at the right moment.

Real Examples:

• Uber: Notifies users about nearby drivers and upcoming promotions, like discounts on airport rides or offers on scheduled trips. You have the option of opting out of these too. 

Image Credits: support.xtremepush.com

• Headspace: This meditation app sends gentle reminders at the best times to encourage you to meditate or practice breathing exercises based on your chosen schedule.

• Nike uses push notifications to inform you about new product drops, exclusive discounts, and challenges that align with your fitness goals.

When done right, an app push notification delivers relevant messages that keep users engaged and drive them back to your app, strengthening customer loyalty.

How to Segment Users for Tailored Push Alerts

Segmentation divides your audience based on shared characteristics, making it easier to deliver personalized mobile push notifications that resonate with each user. It’s crucial because people respond differently to generic and targeted messages. 

There are multiple ways companies can segment their users:

Advanced Segmentation Strategies for Personalized Push Notifications

• Behavioral Segmentation
  Behavioral segmentation is tailoring notifications based on what users do in an app, like the pages they visit or the products they buy. Brands quickly send about 73 million notifications, but only 0.9 percent are opened. However, eight percent of users get opened when they send around 69 million notifications based on user behavior.

Brand Example:
Netflix does a great job with this. It tracks what shows or genres each user enjoys and then sends notifications about new series or episodes that match those tastes. So, if someone often watches crime dramas, Netflix will let them know when a new mystery show is available. This personalized approach keeps people returning and makes the whole Netflix experience feel special.Behavioral segmentation helps you understand customers’ liking and engage them with relevant content. Your app can make users feel understood and valued by sending the proper notifications at the right time.

• Preference-Based Segmentation
  Preference-based segmentation involves customizing notifications based on a user’s interests, which are collected through their interactions and app settings. Businesses can send an app push notification that makes sense to each person by figuring out what people like.

Brand Example:
Spotify nails this. They look at the artists and genres you listen to most and then send notifications with music suggestions you’ll probably love. Whether it’s a curated playlist or a notification about a new album release, Spotify ensures these updates match what you enjoy, keeping you interested and exploring more songs in the app.

Preference-based segmentation helps businesses deliver content that clicks with their users’ interests. When people receive notifications that match their preferences, they’re more likely to open them and stick around for more, which builds better loyalty over time.

• Engagement-Based Segmentation- Engagement-based segmentation adjusts the notification strategy based on how users respond to past alerts. By tracking which users interact often and which don’t, businesses can tailor the frequency and type of notifications they send.

Brand Example:
eBay is smart with this approach. Users who regularly bid on auctions receive more notifications, while those who browse without bidding receive fewer alerts. Regular bidders might get updates about auctions they’re involved in or last-minute deals,

encouraging them to place a final offer. On the other hand, casual browsers receive fewer notifications to avoid overwhelming them.

This approach ensures that notifications align with user behavior, leading to better engagement.

• Location-Based Segmentation
  Location-based segmentation targets users based on where they are, sending alerts about nearby stores, events, or offers relevant to their area.

Brand Example:

Starbucks does a great job with this. Their app sends push notifications about store discounts or special drinks when you’re near one of their locations. For instance, if you’re walking past a Starbucks, you might receive a notification about a special offer inside. This location-based strategy drives foot traffic to the store and encourages people to stop in.

With location-based segmentation, businesses can send relevant notifications that are more likely to be opened, boosting customer engagement and satisfaction.

• Time-Based Segmentation
  Time-based segmentation involves scheduling notifications at the best times based on user activity patterns. Businesses can time their notifications to maximize visibility and engagement by understanding when users are usually active.

Brand Example:
Duolingo is good at this. They send educational push notifications at times when users tend to be more active on the app, helping maintain consistent user engagement. For instance, if a user usually practices Spanish lessons in the evening, Duolingo will send them a reminder around that time to keep them on track with their language goals. This timing keeps users motivated and coming back for more lessons.

Scheduling notifications when people are more likely to see them makes them more effective, improving user engagement.

• Psychographic Segmentation
  Psychographic segmentation uses psychological data like user values, attitudes, and lifestyles to tailor push notifications. This helps businesses connect with users on a deeper, more personal level.

Brand Example:

Patagonia does this well. They send push notifications about environmental initiatives or new sustainable products to users who value eco-friendly living. For instance, users interested in reducing their environmental impact might receive alerts about Patagonia’s newest line of sustainable outdoor gear or ways to support environmental causes. This strengthens brand loyalty by resonating with customers’ core values.

Using psychographic segmentation, businesses can send notifications that align with what users care about most, leading to stronger engagement and loyalty.

Tools and Technologies

To segment users effectively and deliver mobile app push notifications, companies often rely on specialized tools:

Customer Data Platforms (CDPs):

• Function: CDPs like Segment, mParticle, and Tealium act as a central hub, unifying customer data from various sources like website behavior, app interactions, CRM systems, and purchase history.
• Features for Segmentation:
  • Create detailed user profiles with demographics, interests, purchase behavior, and website/app activity.
  • Segment users based on complex criteria using a drag-and-drop interface or custom queries.
  • Integrate with marketing automation platforms and push notification platforms for seamless campaign execution.

Machine Learning (ML) & AI-powered Tools:

• Function: Platforms like OneSignal, Urban Airship (now Airship), and MoEngage integrate machine learning (ML) and artificial intelligence (AI) for user segmentation.
• Features for Segmentation:
  • Analyze vast amounts of user data to identify patterns and automatically segment users based on predicted behavior.
  • Recommend relevant segments and personalize notifications in real-time based on user preferences and actions.
  • A/B test different notification content and timing for optimal engagement.

RFM (Recency, Frequency, Monetary) Analysis Tools:

• Function: Platforms like Pushwoosh, MoEngage, and Braze offer built-in RFM analysis features.
• Features for Segmentation:
  • Segment users based on their purchase history – how recently they bought (Recency), how often they buy (Frequency), and how much they spend (Monetary value).
  • Target users with relevant offers and promotions based on their spending habits.
  • Identify valuable customer segments like high-value customers or at-risk customers for personalized engagement.

Behavioral Analytics & Customer Journey Mapping Tools:

• Function: Tools like Mixpanel, AppAnnie, and FullStory analyze user behavior and map customer journeys across your app or website.
• Features for Segmentation:
  • Identify user actions, feature usage, and drop-off points within your app.
  • Segment users based on specific in-app behavior, like abandoned carts, completed tutorials, or specific feature engagement.
  • Tailor push notifications to address user needs at different stages of their customer journey.

Contextual Targeting Platforms:

• Function: Platforms like Localytics, Leanplum, and Swrve offer built-in contextual targeting features.
• Features for Segmentation:
  • Utilize real-time data like location, time of day, weather, and device type to personalize push notifications.
  • Trigger location-based notifications for nearby promotions or send time-sensitive messages based on user activity patterns.
  • Create highly relevant and engaging notifications based on the user’s current context.

Predictive Analytics Tools:

• Function: This advanced approach utilizes AI and machine learning to predict future user behavior. Tools like AppsFlyer and Singular offer such features.
• Features for Segmentation:
  • Predict user churn, purchase intent, and product interest based on historical data and user behavior.
  • Segment users based on predicted behavior and send proactive push notifications to encourage desired actions.
  • Requires a robust data infrastructure and expertise in data science for optimal results.

Implementing Segmentation in Your Push Notification Strategy

1. Advanced Analytics Tools:
   Tools like Google Analytics, Mixpanel, and Adobe Analytics help identify patterns in the way users behave and their preferences, letting you segment users based on app usage, purchase history, and features they prefer. Netflix is a prime example, analyzing what viewers like to watch and sending push notifications with relevant show suggestions that keep users returning.
2. CRM Systems:
   Customer relationship management (CRM) platforms like Salesforce, HubSpot, and Zoho provide detailed customer profiles. They help you group users based on demographics, purchase history, and location so you can send personalized notifications. Automating push alerts at the right time is much easier if your CRM system is integrated with your push notification platform.
3. A/B Testing:
   Testing different approaches is critical. Domino’s Pizza uses A/B testing to tweak push notifications’ timing, content, and frequency. Experimenting with different variations allows them to fine-tune messages to promote special offers and encourage orders.
4. Behavior-Based Notifications:
   Behavior-based push notifications yield up to 800% higher open rates than generic blasts. Many brands overlook this method, but various tools analyze individual app usage patterns to send push notifications when users are most likely to open them. Triggering notifications based on user behaviors, like shopping cart abandonment, makes them feel more personal and relevant.
5. User Feedback:
   Feedback through surveys or ratings helps understand how users perceive your notifications. If people find them useful, you’re on the right track. Otherwise, use their feedback to refine your segmentation.

Android vs. iOS: Personalized Push Notification Engagement

Implementing Advanced Technologies

AI and machine learning are crucial for making push notifications more personalized. They analyze user behavior and past interactions to deliver relevant and timely messages.

AI uses predictive analytics to determine customers’ needs based on their previous behavior. For example, if a user often shops for skincare products, the AI can identify this pattern and send a push notification about a new moisturizer they may be interested in.

Machine learning takes personalization even further by learning how users interact with notifications. If a user ignores push notifications during work hours but tends to respond in the evening, machine learning adjusts the timing to suit their schedule better.

Using AI and machine learning to personalize push notifications allows marketers to have more meaningful customer conversations. These technologies provide insights that let businesses send the right messages at the right time, leading to better engagement and improved customer loyalty.

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Run Cutting-Edge Push Notification Campaigns

Brands like Airbnb and ASOS are great examples of delivering highly relevant push notifications by studying users’ behaviors and preferences. They know what their audience likes and send notifications that hit the mark. The results are clear: personalized push notifications can increase open rates by up to 800% compared to generic messages, showing just how powerful targeted messaging can be.

If you’re looking to take your push notification strategy to the next level, AdLift can help. Our approach will get your audience to open up and act on your messages. Our expertise will make your mobile push notifications timely, relevant, and impactful. Contact AdLift today!