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Zakir Naik Lectures icon

How much does Zakir Naik Lectures earn?

Android app from MrKunity · Music & Audio

ML forecast ★ 5.0 · 311 Free

~191/mo

ML revenue forecast. Calibrated against 76225 apps in this category.

Confidence band
±15%
High — many comparable apps with verified data

At a glance

What the app looks like

Live screenshots from the Play Store, captured by our snapshot worker. Tap any image to enlarge.

Zakir Naik Lectures screenshot 1 Zakir Naik Lectures screenshot 2 Zakir Naik Lectures screenshot 3 Zakir Naik Lectures screenshot 4

Zakir Naik Lectures's revenue trajectory

Forecast revenue from snapshot history. Last 1 months.

Where Zakir Naik Lectures sits in Music & Audio

Revenue distribution of 76225 comparable apps. Zakir Naik Lectures highlighted.

Zakir Naik Lectures vs comparable apps

Revenue trajectory side-by-side. Bold = Zakir Naik Lectures, ghosted = peers.

App spec

Version
Varies with device
Launched
Jun 09, 2020
Price
Free
Monetization
Free

What Zakir Naik Lectures actually does (from store listing)

Zakir Naik is a famous Ulama from India, He Has a Full Name Zakir Abdul Karim Naik, born on October 18, 1965; (51 years old) is an Indian Muslim public speaker, and author of Islam and comparative religion. Professionally, he is a medical doctor, earning a Bachelor of Medicine and Surgery (MBBS) from Maharashtra, but since 1991 he has been a scholar involved in Islamic da'wah and comparative religion. He stated that the aim was to revive an important foundation of Islam that most Muslim teenage…
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Comparable Android apps

The five apps in Music & Audio with the closest revenue to Zakir Naik Lectures. Click any to see its detail page.

AppRevenueRatingRatings
Devi Mantra : Powerful Mantra icon Devi Mantra : Powerful Mantra 191 0
Q95.5 icon Q95.5 191 ★ 4.4 44
قرآن الكريم عبدالرزاق الدليمي icon قرآن الكريم عبدالرزاق الدليمي 191 0
Mahakali Mantra icon Mahakali Mantra 191 0
Şans FM icon Şans FM 191 0
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How we calculated this

Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag. The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR. Every number on this page comes from public APIs and bumetric's own snapshot history.

Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors. See also the live data on Zakir Naik Lectures's tracker page for current rating, reviews and snapshot timeline.

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