TOP 20 FASHION APP USER ENGAGEMENT METRICS 2025

When I first started paying attention to fashion app user engagement metrics, I honestly didn’t think they would feel all that different from tracking my online shopping habits in general. But the deeper I went, the more I realized these numbers tell little stories about how we discover new looks, save pieces for later, and even decide when it’s finally time to buy those socks we’ve been eyeing for weeks. For me, it’s not just about cold stats—it’s about understanding what keeps me coming back to an app and what makes me close it in frustration. Sometimes the smallest details, like how quickly I find an outfit in a lookbook or whether push notifications feel helpful instead of spammy, completely change the experience. That’s why I believe these engagement metrics matter just as much for shoppers like me as they do for the brands running the apps.

Top 20 Fashion App User Engagement Metrics 2025 (Editor’s Choice)

 

 

Top 20 Fashion App User Engagement Metrics 2025

Fashion App User Engagement Metrics #1 – Daily Active Users (DAU)

Daily Active Users (DAU) reflects how many unique individuals open the fashion app each day. This metric is a quick way to understand whether the app is part of a user’s daily routine. High DAU numbers signal strong stickiness, meaning people consistently return. If DAU fluctuates significantly, it could indicate reliance on seasonal sales or drops. For fashion apps, DAU often peaks during new collection launches or exclusive limited-time offers.

Fashion App User Engagement Metrics #2 – Monthly Active Users (MAU)

Monthly Active Users (MAU) shows how many distinct users are active in the app within a 30-day period. It provides a bigger-picture view compared to DAU, helping track overall reach and growth. A healthy MAU indicates that users continue finding value over longer time spans. Combining MAU with DAU gives the DAU/MAU ratio, which measures depth of engagement. In fashion apps, strong MAU numbers align with seasonal shopping cycles like spring/summer and fall/winter launches.

Fashion App User Engagement Metrics #3 – Session Frequency

Session Frequency measures how often a user opens the app in a set timeframe. This metric shows whether people use the app occasionally or make it part of their daily shopping habit. Higher session frequency suggests strong user interest and anticipation for fresh content. For fashion apps, this often ties to how often new styles or editorial content are updated. A well-timed product drop can significantly boost frequency across the user base.

Fashion App User Engagement Metrics #4 – Session Length

Session Length captures the average duration of time a user spends per session. Longer sessions often suggest more browsing, product exploration, and inspiration-seeking. Shorter sessions may signal users coming in with a clear purpose, such as checking shipping status. For fashion apps, increasing session length often means stronger engagement with lookbooks, try-ons, or curated outfit feeds. Brands often aim to balance session length with high conversions to avoid passive browsing without purchases.

 

 

Fashion App User Engagement Metrics #5 – Retention Rate

Retention Rate tracks the percentage of users who return after downloading the app. This metric is crucial to see if initial interest translates into long-term loyalty. Strong retention shows the app successfully provides ongoing value through content, recommendations, and offers. For fashion apps, Day 7 and Day 30 retention reveal how much post-install engagement the app can maintain. A high retention rate usually signals a good mix of personalization, seasonal relevance, and trust.

Fashion App User Engagement Metrics #6 – Churn Rate

Churn Rate measures how many users stop using the app within a given timeframe. A rising churn rate indicates disengagement and highlights areas where the experience may need improvement. Fashion apps often see spikes in churn after major sales if users lose interest afterward. Tracking churn helps brands adjust loyalty programs, content cadence, or push notifications. A low churn rate means the app is consistently providing enough value to keep users engaged.

Fashion App User Engagement Metrics #7 – Average Order Value (AOV)

Average Order Value (AOV) calculates the average amount spent per purchase through the app. It reflects how much users are willing to invest each time they buy. Increasing AOV is often tied to upselling, bundling, or promoting premium fashion items. Fashion apps can leverage styling recommendations to encourage customers to add complementary pieces. A rising AOV is a good sign that the app experience is boosting not just engagement but revenue.

Fashion App User Engagement Metrics #8 – In-App Purchase Conversion Rate

In-App Purchase Conversion Rate measures how many users complete a purchase after browsing. It’s a key sign of how effective the app is at guiding users through the shopping funnel. High conversion rates often indicate smooth UX, relevant recommendations, and trust in the platform. In fashion apps, this is especially critical since style choices are emotional and need strong product presentation. A dip in conversion may point to checkout friction, unclear sizing, or shipping concerns.

Fashion App User Engagement Metrics #9 – Wishlist / Save-to-Cart Rate

Wishlist or Save-to-Cart Rate shows how often users bookmark items for later. It’s an intent-driven metric, highlighting future buying potential even if purchases don’t happen immediately. A strong save-to-cart rate often signals users are exploring and considering multiple options. For fashion apps, it also shows which collections or items have long-term appeal. Tracking these saves helps forecast demand and optimize re-engagement through reminders or discounts.

Fashion App User Engagement Metrics #10 – Push Notification Open Rate

Push Notification Open Rate measures how many users open the app after receiving a notification. It reveals how effective push messaging is in bringing users back. Low open rates may indicate over-messaging or irrelevant content. For fashion apps, well-timed pushes about limited stock, sales, or collection drops often yield high opens. This metric is critical in bridging passive users back into active engagement.

 

 

Fashion App User Engagement Metrics #11 – Click-Through Rate on Recommendations

Click-Through Rate (CTR) on Recommendations shows how many users interact with suggested products. A strong CTR means users trust and value the personalization engine. In fashion apps, this metric indicates how well algorithms align with evolving personal style preferences. A poor CTR may suggest recommendations are too generic or misaligned. Optimizing this metric can directly impact both user satisfaction and conversions.

Fashion App User Engagement Metrics #12 – Outfit / Lookbook Engagement

Outfit or Lookbook Engagement measures user interactions with curated fashion content. It highlights whether users are connecting with inspirational shopping experiences. High engagement shows content is not only visually appealing but also drives product exploration. For fashion apps, lookbooks often bridge storytelling with commerce, creating emotional connections. This metric also signals how well editorial content is fueling shopping journeys.

Fashion App User Engagement Metrics #13 – Social Sharing Rate

Social Sharing Rate reflects how often users share outfits, carts, or style ideas externally. This metric reveals the app’s viral potential and ability to extend reach. In fashion apps, shares to Instagram or TikTok amplify organic growth and visibility. Strong sharing rates show the app is successfully blending commerce with social identity. It’s also a sign that users are proud to showcase their style discoveries.

Fashion App User Engagement Metrics #14 – Review & Rating Participation

Review and Rating Participation measures how many users contribute product feedback. High participation rates indicate an engaged community willing to guide peers. Fashion apps rely heavily on this for credibility, especially with sizing, fit, and quality. User-generated content in reviews reduces hesitation for new shoppers. This metric builds long-term trust and strengthens the overall shopping ecosystem.

Fashion App User Engagement Metrics #15 – Virtual Try-On Usage Rate

Virtual Try-On Usage Rate captures how often users engage with AR features. High usage means customers are curious and comfortable with tech-based styling. In fashion apps, this often drives confidence in purchase decisions, especially for shoes, accessories, and cosmetics. A low rate may signal either tech limitations or lack of awareness. Increasing this metric can set fashion apps apart by blending innovation with practicality.

 

 

Fashion App User Engagement Metrics #16 – Abandoned Cart Rate

Abandoned Cart Rate tracks how many users add items but don’t complete purchases. This is a critical friction metric showing where the funnel breaks. In fashion apps, common reasons include unclear sizing, unexpected shipping costs, or price hesitation. Lowering this rate requires smoother checkout, flexible payments, or personalized reminders. Keeping abandoned carts in check directly increases conversion and revenue.

Fashion App User Engagement Metrics #17 – Referral Engagement

Referral Engagement reflects how many users join through invite-a-friend features. This metric highlights the strength of community-driven growth. Fashion apps with strong referral activity often gain trust faster since recommendations come from peers. A high rate here suggests users enjoy the experience enough to recommend it. It’s also one of the most cost-effective ways to scale user acquisition.

Fashion App User Engagement Metrics #18 – Personalization Engagement

Personalization Engagement measures interactions with tailored feeds, styles, or suggestions. It reflects how well the app adapts to individual preferences. High engagement indicates that users feel understood and valued. For fashion apps, personalization helps surface relevant outfits faster, cutting decision fatigue. This metric also improves conversion by aligning directly with personal style journeys.

Fashion App User Engagement Metrics #19 – Loyalty Feature Engagement

Loyalty Feature Engagement measures user activity with points, badges, or rewards programs. It’s a direct indicator of how well gamification drives retention. Fashion apps often tie these to seasonal collections or limited drops to enhance exclusivity. High participation keeps users coming back regularly to maximize rewards. This metric blends commerce with motivation, reinforcing long-term loyalty.

Fashion App User Engagement Metrics #20 – Customer Support / Chatbot Engagement

Customer Support or Chatbot Engagement shows how many users rely on in-app help. It reflects the importance of real-time assistance for smoother experiences. In fashion apps, this often covers sizing queries, delivery updates, or styling advice. High engagement suggests users trust the app to solve issues quickly. This metric supports loyalty by ensuring problems don’t block purchases.

 

 

Final Thoughts on Fashion App Engagement

Looking through all of these fashion app user engagement metrics has made me more aware of my own habits, and maybe even a little more forgiving when I catch myself endlessly scrolling through new arrivals. I’ve learned that things like retention rates and abandoned carts aren’t just abstract numbers—they represent real moments of decision-making that I’ve lived through myself. Sometimes I’ve left carts behind because the checkout felt too pushy, and other times I’ve stuck with an app because its loyalty rewards gave me just the right nudge. What I love most is seeing how these metrics mirror the real rhythms of our fashion lives, from impulse buys to carefully planned seasonal updates. At the end of the day, it feels like a reminder that behind every chart or percentage is someone like me, trying to make style choices that fit not just their closet, but their everyday life

SOURCES

https://sendbird.com/blog/app-retention-benchmarks-broken-down-by-industry 

https://www.businessofapps.com/data/ecommerce-app-benchmarks/ 

https://www.businessofapps.com/data/app-retention-rates/ 

https://www.businessofapps.com/data/app-engagement-rates/ 

https://www.promodo.com/blog/mobile-fashion-applications 

https://www.digitalfashionacademy.com/engagement-rate-product-discovery/ 

https://uxcam.com/blog/mobile-app-retention-benchmarks/ 

https://cordial.com/resources/why-brands-need-mobile-app-stats/ 

https://sproutsocial.com/insights/social-media-benchmarks-by-industry/