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How Digidarts Scaled Equal AI from 0 to 10 Million Installs in 9 Months

About the Campaign

Background

Equal AI is an AI-powered caller assistant that answers unknown calls on behalf of users, understands the caller's intent and connects only the conversations that truly need attention.

The challenge wasn't simply to drive installs. Equal AI was introducing a new user behaviour: letting AI answer unknown calls on your behalf. That meant a cheap install could easily become a low-quality user if expectations weren't set correctly.

Digidarts therefore built the acquisition strategy around one principle: Acquire for retention, not just installation.

Within 9 months, Equal AI scaled from 0 to 10 million Play Store installs while simultaneously improving CPI, onboarding and retention.

Objective

Key campaign objectives:

Scale Equal AI rapidly while maintaining user quality.
Improve acquisition efficiency without compromising retention.
Identify audiences most likely to understand and adopt the product.
Improve install-to-onboarding conversion.
Reduce Day-1 uninstall rates.
Build a repeatable creative engine capable of supporting rapid scale.
Grow daily active users alongside install volume.

Our Approach

Identified distinct ICPs across business professionals, parents, scam-conscious users, tech enthusiasts and finance audiences.

Instead of one generic proposition, communication was tailored to each audience's specific motivations.

Creative testing was structured across:
Persona × Problem × Hook × Creator × Language × Format

At peak scale, the team tested 50+ creatives every week, expanding winning concepts across different hooks, creators, languages and formats.

Moved beyond CPI as the primary measure of acquisition quality.

Post-install behaviour became the key signal, with strong cohorts defined by users who remained active for at least five days and used Equal AI to answer unknown calls more than twice a day.

On Google, irrelevant GDN placements generating accidental or low-intent installs were removed.

YouTube received greater investment because it consistently delivered users with approximately 20% better retention, despite being slightly more expensive.

On Meta, regions generating cheap but low-retention installs were restricted, while stronger retention markets received greater investment.

Cost determines efficiency. Retention determined scale.

For a new AI-led product, communication had to explain the product clearly before users downloaded it.

Advertising clearly communicated:

What Equal AI does
How it answers unknown calls
When it connects users
What users should expect
What users should not expect

Product demos, creator walkthroughs, tech-expert explainers, social proof and trust-led communication became core parts of acquisition.

This approach improved Day-1 uninstall by 20% and install-to-onboarding conversion by 15%.

Initial scale was concentrated across Tier-1 and metro audiences, where product acceptance was strongest.

Creators across AI & Tech, Lifestyle, Marketing and Finance helped introduce the product through different audience contexts.

Hindi, English and vernacular communication further improved product understanding and regional relevance.

The model was simple:
High-potential market → Relevant creator → Localised communication → Quality acquisition → Greater scale

Results & Impact

10M

Play Store installs delivered in 9 months

31.2X

Growth in monthly install volume vs. Month 1

49%

Improvement in Cost Per Install (CPI)

15%

Improvement in install-to-onboarding conversion

20%

Improvement in Day-1 uninstall rate

1M+

Daily Active Users (DAU) reached

25%+

Minimum month-on-month DAU growth

45%

DAU growth recorded in the latest measured month

Top 10

Trending app in Google Play Store Communication category

Bottom Line

Equal AI didn't reach 10 million installs by simply buying more scale.

It built an acquisition engine designed around user quality.

Creative testing found the right messages. Post-install signals identified the right users. Expectation-setting improved onboarding and retention. Audience and channel intelligence determined where to scale.

The result: 10M installs in 9 months, 49% better CPI and 1M+ daily active users, proving that acquisition can accelerate without sacrificing long-term product value.