I. Client Background

1. Business Model

JunkFree is a mobile cleaning and optimization application that intelligently scans all videos, images, audio files, and documents on a user's phone, identifies and removes duplicate files and useless cache, frees up storage space, and improves device performance.

2. Core Markets

The core user base consists of Android device users in the United States (US) and Russia (RU). In the US, the focus is on white‑collar workers and students. In Russia, the focus is on lower‑tier markets and family users, with special attention to users of older devices (Android 6.0 and above).

3. Marketing Objectives

KPIs: App downloads (CPI), new user retention
Media: TikTok, Mintegral, Applovin
Regions: United States (all 50 states, with emphasis on California, Texas, Florida); Russia (Moscow, St. Petersburg, and surrounding second‑ and third‑tier cities)
Ad Placements: News feed, rewarded video, native landing pages

4.User Download & Activation Funnel

Download & Activation: Users click on an ad, are directed to a Mintegral native landing page, and click a prominent download button (in RU, a large red button) to go to the app store and complete the installation.

II. JunkFree Advertising & Marketing Strategy

Precision Audience Targeting: Device + Behavior + Interest Three‑Layer Model

Basic Targeting: Users aged 18–55 who use Android devices and care about phone storage space.
Countries/Regions:

United States (all 50 states, focusing on densely populated areas)
Russia (core cities and surrounding second‑/third‑tier cities; avoid remote areas with poor network connectivity)

Device Targeting:

US: Focus on Android devices priced between $ 100– $300; exclude high‑end flagships
RU: Focus on devices priced below $200 and over 2 years old (compatible with Android 6.0 and above)

Demographic Targeting:

Age: 18–55
US emphasis: White‑collar workers, students
RU emphasis: Lower‑tier market users, family users

Interest Tags: Select relevant categories such as "phone optimization", "digital accessories", "free tools", "cleaning & acceleration"
**Behavioral Targeting: **Prioritize users who have recently searched for "fix phone lag", "junk cleaner app", "not enough storage space"

Content & Creative Strategy (Core of Viral Success)

In Western and Russian markets, pure feature demonstrations struggle to drive download intent. We built a two‑region, differentiated viral content model around four pillars: "efficiency + privacy security + free utility + legacy device compatibility".

Content Localisation Adaptation

Language: English for US, Russian for RU (interface and ad copy).
Landing Pages: Use Mintegral native landing page templates.
- US: Highlight "No Privacy Risk", "1‑Click Clean". Clean and simple design.
- RU: Highlight "Поддержка Android 6.0+" (Compatible with Android 6.0+), "Бесплатно" (Free). Use a large red download button and minimise click‑through layers.
Cultural Adaptation: US emphasises personal efficiency and data security; RU emphasises practicality, free usage, and broad device compatibility.

Advertising Cadence

3.1 Pre‑Campaign Planning & Strategy

a. Produce region‑specific creatives (US: privacy‑safety demonstrations; RU: storage‑saving numbers + Russian UI).

b. Complete account integration with TikTok, Mintegral, and Applovin to ensure unified tracking of conversion events (download, activation, retention).

c. Confirm target markets (US, RU), media (TikTok, Mintegral, Applovin), and conversion goals (download/activation).

d. Define audience personas based on device price, usage age, and search behaviour.

3.2 In‑Campaign Execution & Dynamic Optimisation

Cold‑start period (7–14 days, small budget to test creatives):

Allocate $ 500– $1,000 daily budget per region, using a bid strategy slightly above platform average to quickly acquire traffic.
Test 3–5 different creatives (US: demonstration style; RU: numerical display style) and monitor CPI and retention data.
Kill rules: if an ad reaches 5,000 impressions with CTR < 1% or CPI > 2x target, shut it down.

Stable / Scaling period (2–6 months):

Filter out best‑performing creatives (US: privacy‑safety creatives; RU: storage‑saving display creatives).
Combine "smart bidding + manual control" to prioritise high‑retention user acquisition.
Dynamically adjust budgets based on ROI: when a region’s ROI exceeds 1.0 for three consecutive days, increase its budget share, up to a maximum of 50%.

3.3 Post‑Campaign Data Review & Insights

a. Review core KPIs: spend, CPI, day‑1 retention, ROI, CTR, conversion rate.

b. Multi‑dimensional deep dive: creatives, audience (age/occupation), region (state/city), placement, time of day, device model.

c. Extract insights and define next‑cycle actions – for example, if RU shows highest conversion during evening peak (Moscow time 19:00–22:00), increase budget for that time slot.

Account Optimisation Cadence

For new ads still within the learning period, modify bidding (including target CPI, audience‑specific bids, placement‑specific bids) and targeting no more than twice per day.
Flexibly adjust account optimisation frequency based on actual performance. In early stages, focus on turning off low‑performing creatives; in middle and late stages, continue shutting down wasteful campaigns, adjusting budgets, and optimising based on ad diagnostic status.
For well‑performing campaigns (high retention, positive ROI), promptly increase budgets and expand lookalike audiences; allocate budget preferentially to high‑ROI accounts and regions.
Continuously monitor campaign and account status, paying attention to cost increases caused by wasteful spend. In particular, some remote cities in RU may have poor network connectivity leading to conversion failures – shut down ineffective locations in a timely manner.

III. Case Summary

Backed by a clear product positioning and in-depth localization strategies, JunkFree achieved efficient growth in the U.S. and Russian markets. Leveraging precise audience targeting, differentiated creative content, phased campaign pacing, and refined account optimization, the project effectively controlled Cost Per Install (CPI), boosted new user retention, and successfully established a replicable global campaign model for tool-based apps—providing a mature methodological reference for similar products expanding overseas.