Scaling FaithTech App Dharmayana from 0 to 3M+ installs to 1,000+ orders/day.

The product.

Dharmayana is a FaithTech app that gives users guidance through astrology-based services such as Kundali, Pooja, Prashna consultations and spiritual remedies, bundled into a single app experience. SurgeX has owned the user acquisition, creative engine, WhatsApp automation and viral distribution since the early days of the journey.

What we set out to do.

Five phases. Each one earned by what the last one taught us.

We didn't write the playbook upfront. Each phase was a response to what the previous phase exposed, both the wins and the cracks.

01

Build the install base with CPI campaigns

Oct 2024 to Jan 2025 · CPI ₹50 to ₹10

We started with CPI (Cost Per Install) campaigns to drive app installs and early traction. The focus was install growth, early-funnel engagement, and helping the platform get discovered.

What moved

• CPI: Started at ~₹50, closed the quarter at ₹10.
• Installs scaled rapidly with quality creative + tight audience iteration.
• Account hygiene + structure in place for the next phase.

What we learned

• Install volume did not directly translate into orders.
• The optimisation signal needed to shift downstream, closer to revenue.
• Set us up to move from CPI to CPO in Phase 3.

02

Scale CPI & build the creative framework

Feb 2025 to Jul 2025 · Scaled high-intent campaigns

With a working install engine, Phase 2 was about scaling the winners and formalising the creative framework: concept families, hook libraries, and a repeatable testing cadence that compounded performance.

• Scaled high-intent campaigns. Kept feeding budget into the cohorts that consistently held CPI.
• Conversion efficiency improved significantly as creative and audience signals matured.
• Built the testing infrastructure that Phase 4 would later lean on heavily.

03

Move down funnel: launch CPO campaigns

Aug 2025 to Sep 2025 · 80% CPO / 20% CPI · Orders to ~300/day

We made the strategic move to launch CPO (down-funnel optimised) campaigns. Budget rebalanced to 80% CPO / 20% CPI. Orders grew to ~300/day, but the move surfaced a new problem: average ticket size dropped.

Root causes

• Campaigns were optimising only for order volume, not order value.
• Low-intent users were entering the funnel.
• A free Prashna offering was attracting low-quality, low-LTV users.

Observations

• Orders increased.
• Revenue per order decreased.
• User quality declined, which set up the work for Phase 4.

05

Final growth push: 700 orders/day

Continuous creative testing + optimised CPO + returning-user focus

With creative testing on autopilot and campaigns tuned to the right signals, daily orders climbed steadily and crossed 700 orders/day on the last day of the quarter.

The honest read on profitability.   Through this push, blended ROAS moved with the campaign mix. We hit peak >1.3x ROAS in our best creative-product combinations and during specific weeks, but it was not constant. There were ups and downs as we shifted budget into CPO and rebalanced free vs paid offerings. Sustaining >1x blended ROAS across the full account is the active next chapter.

What actually moved the needle.

Six things did the heavy lifting. The first three are media & product fundamentals. The last three are where SurgeX's edge shows up: a relentless creative testing engine, WhatsApp automation as a profitability lever, and our proprietary Viral Hacks playbook ported in from other categories.

Where we started, where we landed.

Business impact

• 20x+ increase in daily orders from the initial baseline (0 to 50 › 1,000+/day at peak).
• ~375x growth in app installs (~8K › 3M+) on a bootstrapped budget.
• Established a scalable acquisition framework across CPI, CPO and WhatsApp activation.
• Built an always-on creative testing engine that compounds week over week.
• Ported in SurgeX's Viral Hacks playbook from other categories as a non-paid growth lever.

One source of truth: AppsFlyer.

All channel performance was reconciled in AppsFlyer, including installs, in-app events, cohorted revenue and ROAS. This is what let us cut spend confidently on channels that looked good in-platform but didn't show up in the cohort.

The view we ran the business on, every week.

Beyond ad platforms, we built internal Excel dashboards that stitched spend, installs, orders, CPI, CPO, uninstalls and ROAS by channel and campaign (Kundali, Pooja, Prashna, Services, Jyothisha, Dosha Parihara). This is what we walked the founder through every week.

What we'd bring on Day 1.

The arc below is what we'd execute against from week one, sequenced to compound: install engine first, down-funnel optimisation next, then profitability.