App User Segmentation: A Step-by-Step Guide to Shopping Behavior Targeting

Imagine two customers using your app.

Both are 32. Both live in Austin, Texas. Both own the latest iPhone and landed on your homepage from an Instagram ad.

Apparently, both users may look the same; their source medium is the same Instagram ad, both are using an iPhone, and they are from the same location. Moreover, their age is the same. 

But here’s the difference: (Understanding these differences will give you the initial breakthrough to understand the basics of mobile app audience segmentation). So, you need to pay closer attention here. 

• One browsed five product pages, added two items to their cart, and bounced during checkout.
• The other clicked straight to your clearance tab, filtered by size, and left within 30 seconds.

Same demographics. Very different intent. And here is what the app user segmentation approach comes in. 

Earlier, this whole instance was very natural, and both users were considered similar. There was no segmentation, considering that both users’ behaviors were the same. There was nothing called a cohort analysis in mobile apps previously.

That’s the core problem with traditional segmentation, it treats people like static profiles instead of dynamic shoppers. 

But in 2025, that’s not enough. Today’s users expect smarter personalization, and the only way to deliver that is by paying attention to what the users do, not just who they are.

This is where behavioral segmentation comes in. Instead of grouping users by device type, zip code, or age bracket, you group them by how they behave inside your app – what they browse, when they buy, and how they engage. And all that is done through rigorous customer behavior tracking.

It’s what leading U.S. brands like Sephora, Target, and Nike already do. They don’t just market to “women in their 30s.” They use powerful user segmentation strategies for apps.

These guys segment users based on their actions, such as:

• Frequent shoppers
• Lapsed buyers
• Window browsers
• Big spenders, and more

Behavior is the new superpower – and if you’re building a mobile app for your Shopify, WooCommerce, or DTC brand, behavioral segmentation in apps is the playbook that’ll help you drive real, repeat revenue.

What is Behavioral Segmentation in Mobile Apps?

Behavioral segmentation in apps is the practice of grouping app users based on what they do, not who they are.

It’s a shift from static user data (like age or location) to dynamic, real-time behavior patterns. You’re looking at things like:

• What products a user interacts with
• How often do they return to the app
• How far they get in the checkout flow
• What time of day do they tend to engage
• Whether they respond to push notifications

Think of your app as a digital storefront. Mobile app audience segmentation is how you track the “aisles” people walk down and what they pick up along the way.

For example, a user who opens your app every Saturday and browses men’s running shoes might belong in your “high-intent weekend shopper” segment. A different user who opens your app once a month but always checks your sales tab could go into a “bargain hunter” segment..

And this kind of eCommerce app user segmentation doesn’t just power better marketing. It powers better product decisions, more personalized offers, and smarter retention flows.

Behavior doesn’t lie. It’s the cleanest, most predictive signal you’ll get in mobile commerce – and yet, most small to mid-sized brands still don’t use it.

Those who are still not using the power of app user segmentation are doing nothing but losing real money every day, every hour!

How to Segment Users Based on Shopping Behavior

Once you’ve identified key behavioral signals, the next step is to segment users based on shopping behavior, breaking users into groups based on patterns that influence how (and if) they shop again. Below are the seven essential behavioral segments every e-commerce app should use to build smarter retention and personalization strategies:

1. First-Time Users with High Browsing Intent

These users are new to your app, but they’re not passive. They visit multiple product pages, spend more than average session time, and may even initiate cart actions. So, you can segment these users based on shopping behavior.

Why they matter:
This group is primed to convert, they’re exploring actively. The right message at the right moment (like a limited-time offer or onboarding discount) can turn them into first-time buyers.

What to do:
Trigger welcome incentives like “Get 10% off your first order if you check out within the next hour,” or surface a “Frequently Bought Together” bundle to reduce friction.

2. Repeat Buyers with Predictable Cycles

Some customers exhibit regular buying patterns – maybe every 3 weeks, or around paydays, or seasonally. Even a detailed cohort analysis in mobile apps should be done for them as well.

Why they matter:
This group represents your most stable revenue. They don’t need persuasion, they need recognition – and optimization.

What to do:
Use their purchase timing to schedule re-engagement. For example, send a reminder when they’re nearing their average reorder cycle. Offer auto-ship or subscription nudges for convenience. All that can be done when you have a proper customer behavior tracking system in place. 

3. Cart Abandoners with Consistent Drop-Off Points

These users often add items to their cart but rarely complete the purchase. The dropout point is usually consistent, just before payment or right after entering address info.

Why they matter:
They’re halfway there. The intent is high, but friction or doubt is stopping them. So, a separate app user segmentation should be done for these guys. 

What to do:
Segment by abandonment stage and retarget with urgency-based nudges: “Still thinking it over? That item’s almost sold out,” or highlight alternative payment methods like Shop Pay or Afterpay if friction is financial. For proper segmentation of these users, you’ll need advanced user segmentation strategies for apps.

4. High-Value Buyers (Top 5% Spenders)

These are your whales. They may not purchase frequently, but when they do, they go big – buying bundles, premium SKUs, or full-price items.

Why they matter:
This small group often contributes a disproportionate share of revenue and LTV.

What to do:
Create exclusive access segments. Offer them early drops, personalized VIP pages, or loyalty tier badges. Make the app experience feel customized – like a premium concierge, not a general storefront.

5. Discount-Driven Users (Coupon Chasers)

These users always interact with your sales section, apply promo codes, and typically convert only when an incentive is present.

Why they matter:
They won’t deliver your highest AOV, but they’re predictable and easy to re-engage during promos.

What to do:
Set up flash sale or spin-to-win mechanics just for this group. You can also experiment with gamified referrals to turn their discount-seeking into virality.

6. Loyal Browsers Who Rarely Buy

They open your app frequently. They check out new arrivals, save products, even share them, but rarely convert.

Why they matter:
They’re invested. They like your brand. Something’s missing – urgency, trust, or price.

What to do:
Use social proof (“X users bought this today”), or surface UGC (real customer photos, reviews). You might also A/B test showing product bundles vs. single SKUs.

7. Dormant or Inactive Users

They haven’t opened your app or bought anything in 30+ days, maybe longer.

Why they matter:
They’re at risk of churn, but many were once loyal. The goal here is revival.

What to do:
Send a comeback flow with personalized win-back offers (“We miss you, here’s 15% off just for today”), or surprise them with free shipping if they return. Highlight what’s new since their last session – new SKUs, seasonal drops, or app features.

How to Collect the Right Data for Segmentation

You can’t segment what you don’t track. While many apps already collect data passively, most fall short of making that data actionable. If you’re building a serious retention strategy, data collection isn’t a checkbox – it’s a foundation.

Start with the essentials:

1. User behavior data:
   Track every in-app event – product views, add-to-carts, purchases, search terms, scroll depth, and exits. Tools like Firebase or Mixpanel make this customer behavior tracking easy without needing a full dev team.

2. Session-level data:
   Look at how long users spend in the app, where they drop off, and which screens they return to most often. These signals often reveal hidden friction or “hot spots” worth doubling down on.

3. Purchase history and frequency:
   When did they last buy? How often do they reorder? Which products do they favor? This is where app user segmentation becomes valuable, especially when paired with inventory or seasonal behavior.

4. Engagement data from push notifications:
   Which users open push notifications consistently? Which messages lead to sessions or conversions? This data helps refine which segments are most responsive and when.

Now, if you’re a Shopify store owner using a no-code app builder like Twinr or Tapcart, much of this data can be captured automatically – no engineering lift required. What matters is how you interpret it.

For instance, let’s say a user opens the app three days in a row but never adds anything to the cart. They’re interested, but not convinced. That’s a great time to trigger a trust-building push: “Want to see what others are buying? Our top-rated picks for you.”

When data tells a story, eCommerce app user segmentation becomes not just a tactic, but a real-time dialogue.

Tools & Platforms to Help You Segment (No Code Needed)

You don’t need an enterprise data stack to segment your users intelligently. Today’s no-code and low-code tools make it possible to build powerful behavioral segments without writing a single line of code.

Here are some of the best tools to segment users based on shopping behavior:

1. Firebase Analytics (by Google)
   Great for tracking event-level app behavior and funnel drop-offs. Its audience segmentation feature lets you define groups like “users who added to cart but didn’t purchase in the last 7 days.”

2. OneSignal or Pushwoosh
   These push platforms allow for dynamic mobile app audience segmentation based on user behavior, location, device type, and more. You can create real-time engagement campaigns personalized to your segments.

3. Shopify + Twinr
   If you use Shopify with a no-code builder like Twinr, you can access order data, user tags, and browsing behavior within a visual interface. Segments like “repeat buyers” or “first-timers who haven’t converted” can be created with logic-based rules.

4. Customer.io or Klaviyo (for deeper retention)
   For more advanced workflows (like targeting VIP buyers with early access offers), these platforms integrate with your app and backend to trigger behavior-based flows.

The real advantage here isn’t just accessibility – it’s speed. With these tools, you can launch, test, and refine segments within days, not months.

And the best part? These platforms scale with you. Whether you’re managing 500 users or 500,000, behavioral segmentation in apps doesn’t require a new team, just better tools and sharper focus.

Personalization Strategies Based on Each Segment

Once your segments are live, the real magic begins: tailoring the app experience in ways that feel timely, relevant, and personal. Below are ways to personalize for each segment discussed earlier:

• First-time users
  Greet them with a short onboarding flow that shows app benefits clearly. Highlight curated collectionsx or offer a “New Here?” starter kit to drive first conversion.

• Predictable repeat buyers
  Send reorder reminders timed to their past patterns. Use dynamic banners like “It’s been 3 weeks, ready to restock your favorites?”

• Cart abandoners
  Trigger win-back nudges based on where they dropped off. For example, if they exited on the payment screen, offer an alternate payment method or highlight security badges.

• High spenders
  Show them exclusivity. Private collections, VIP-only bundles, or early access to sales make them feel valued. Personal greetings like “Hey Sarah, your loyalty earns you early access” go a long way.

• Discount chasers
  Instead of just throwing generic coupons, offer gamified rewards: “Spin the wheel for your discount” or “Unlock your deal by completing your wishlist.”

• Loyal browsers
  They like to explore, so surface what’s trending, what’s back in stock, or what’s loved by others. Highlight products they’ve previously engaged with and add social proof.

• Dormant users
  Re-introduce them to what’s new. Use a “See what you missed” campaign or offer a welcome-back perk. Avoid guilt-tripping,zaz make it about discovery, not pressure.

Remember, personalization is not about showing everything, it’s about showing the right thing. And the best personalization? It doesn’t feel like marketing, it feels like the app knows you. It understands how app user segmentation is done.

Measuring the Impact of Segmentation on Retention

Mobile App Audience Segmentation is a long game. But that doesn’t mean it’s hard to measure.

Here’s how to know if your segmentation strategies are working:

• Retention rate (7-day, 30-day)
  Compare segmented users to the general cohort. Are “repeat buyers” coming back more often when re-engaged? Are “cart abandoners” converting more after targeted messages?

• Repeat purchase rate (RPR)
  Track how many users placed another order after being added to a segment-specific flow. This shows whether your efforts actually impact buying behavior.

• Time to next session/purchase
  If the average time between sessions shrinks for a segment, that’s a strong signal. It means your nudges are working.

• Revenue per segment
  High spenders should show increased AOV. Dormant users should contribute new revenue post-campaign. If not, it’s time to re-evaluate what you’re offering each group.

• Push open and conversion rates.
  Don’t just measure opens, track how many opens turn into sessions, then purchases. This shows how well your message matched intent.

Tip: Run A/B tests within segments. For example, test two messages for cart abandoners – one emotional, one urgency-driven. Over time, you’ll learn what truly resonates.

Common Pitfalls to Avoid When Segmenting App Users

Even with the best tools and strategy, it’s easy to overcomplicate eCommerce app user segmentation. Here are a few mistakes that hold brands back:

• Too many segments, too little focus
  You don’t need 30 segments. Start with 5–7 high-impact groups. More segments = more noise, not more clarity.

• Segmentation without action
  Creating segments is useless if they’re not tied to real campaigns. Every segment should have a purpose and a flow attached.

• Wrong timing
  Sending a discount after someone has already converted? Offering a bundle when they’re only browsing? Segmentation must consider timing and lifecycle.

• Using only demographic data
  Age and gender tell you nothing about why someone buys. Behavior is king when it comes to intent and retention.

• Stale segments
  User behavior changes. Someone might be a “dormant user” today, but after they re-engage, they belong in another group. Keep your segments dynamic, not static.

When you segment users based on shopping behavior, it isn’t about slicing users thinner and thinner. It’s about finding where behavior aligns with opportunity, and acting on it with speed and relevance.

Conclusion: Segmentation Isn’t a Tactic, It’s Your Growth Lever

Smart brands don’t guess what users want. They observe, segment, and respond. That’s what makes mobile app experiences feel personal, even if you’re working at scale.

The truth is, your users are already telling you how they want to be marketed to. Every tap, scroll, cart, and bounce is data. Behavioral segmentation in apps turns that data into strategy.

And when you build your app experience around segments – not just sessions – you stop talking at users… and start talking to them.

So don’t just build an app that converts. Build one that remembers.