What does the Launch Pipeline actually do?

The Launch Pipeline takes an App Store URL as input and walks through 7 interactive stages: (1) app metadata extraction, (2) competitor identification, (3) keyword discovery and clustering, (4) initial bid suggestions, (5) campaign structure proposal (Brand + Category + Discovery), (6) budget allocation across ad groups, (7) launch readiness checklist. Each stage requires the developer's approval before moving forward — read-only model.

Why was the developer's CPI better than typical indie launches?

Three structural reasons: (1) Launch Pipeline pre-built the campaign with Brand isolation from day 1 (most indie launches lump Brand and Category together, inflating Discovery CPT through brand leakage), (2) Custom Product Page was assigned to the highest-intent ad group (lifting first-week CR), (3) Initial bid recommendations were calibrated to ad group floor + 30%, avoiding both under-bidding (no impressions) and over-bidding (wasted launch budget).

Is the Launch Pipeline available on all ASAPilot plans?

Yes — Launch Pipeline is available on the free tier (1 app, 10 AI queries/month), Starter, Growth, and Agency plans. The free tier is specifically designed to accommodate one-time launch usage. The developer in this case study used the free tier for the first 14 days, then upgraded to Starter ($39/month) for ongoing automations.

How an Indie Developer Launched a New App on Apple Search Ads at $50/Day With ASAPilot Launch Pipeline

Note: This case study describes a representative indie-launch workflow observed across multiple ASAPilot users. Developer identity, app name, and exact figures have been anonymized at the user’s request.

The developer

A solo indie developer based in the US, full-time on a self-funded project. Background: 6 years as a backend engineer at a SaaS company, no prior mobile marketing experience. The launching app was a productivity tool — note-taking and task management with offline- first sync.

The app launched on the App Store on May 1, 2026 after 18 months of development. The developer had committed $1,500 to the first 30 days of Apple Search Ads — $50/day average — and needed to make that budget work without overspending on experimentation.

The problem

Standard ASA setup advice was paralyzing for a first-time advertiser:

“Build Brand, Category, Discovery campaigns” — but with which keywords?
“Bid $1-3 CPT initially” — but at $1 you may get no impressions; at $3 you may overpay
“Use Search Match for exploration” — but on which ad groups?
“Assign a Custom Product Page” — but the developer had not built one yet

The developer estimated 2-3 weeks of trial-and-error would burn $300-500 in inefficient spend before the campaign settled into a sustainable shape. On a $1,500 monthly budget, that was 20-33% of the runway.

The implementation

The developer signed up for ASAPilot’s free tier on launch day, May 1, 2026, and started the Campaign Launch Pipeline at 2pm.

Stage 1: App metadata extraction (4 min)

Pasted the App Store URL. ASAPilot extracted:

App name and adam ID
Category and sub-category
Default product page screenshots and description
Current ratings and reviews count
Existing organic keyword rankings (where the app already showed up before paid)

Stage 2: Competitor identification (8 min)

ASAPilot identified 8 competitor apps based on:

Category overlap
Keyword ranking overlap (apps the new app already organically competed with)
Search Tab adjacency (apps frequently shown together)

The developer reviewed the list, confirmed 6 as direct competitors, marked 2 as “category-adjacent but different product.”

Stage 3: Keyword discovery + clustering (22 min)

Based on the app’s metadata, category, and competitor keyword profiles, ASAPilot proposed:

47 candidate keywords in 4 clusters:
- Brand (the app’s own name + variants): 3 keywords
- Category-core (note-taking, task manager, etc.): 12 keywords
- Category-adjacent (productivity, GTD, etc.): 18 keywords
- Long-tail (specific use cases): 14 keywords

The developer reviewed each cluster, removed 6 keywords as poor fit, added 4 from their own intuition. Final: 45 keywords.

Stage 4: Initial bid suggestions (5 min)

ASAPilot pulled current bid floor data per keyword + storefront (US for launch) and suggested:

Brand keywords: $0.75 (1.5× floor; Brand should always win)
Category-core: $1.50 (1.3× floor; competitive but worth winning)
Category-adjacent: $1.20 (1.2× floor; exploration mode)
Long-tail: $0.80 (1.5× floor; cheap enough to test)

Developer accepted all defaults.

Stage 5: Campaign structure proposal (10 min)

Proposed structure:

Productivity App — US Campaign
├── Brand ad group (Exact, $0.75 bid)
├── Category-core ad group (Exact, $1.50 bid)
├── Category-adjacent ad group (Exact, $1.20 bid)
├── Discovery ad group (Broad + Search Match, $0.80 bid)
└── Negatives: own brand name on Discovery ad group

The developer accepted the proposal as-is.

Stage 6: Budget allocation (8 min)

ASAPilot proposed a budget split based on expected conversion characteristics:

Brand: $5/day (cheap, high CR, capture all brand intent)
Category-core: $20/day (highest-volume acquisition driver)
Category-adjacent: $15/day (expansion bet)
Discovery: $10/day (exploration; capped tight)
Total: $50/day

Developer accepted.

Stage 7: Launch readiness checklist (10 min)

ASAPilot ran final pre-launch checks:

✅ All keywords have bids above their floor
✅ Brand isolation negative is in place
✅ No keyword appears in multiple ad groups
⚠️ No Custom Product Page assigned — recommendation: build one for Category-core within first 14 days
✅ Daily Cap matches monthly budget intent
✅ Audience refinements left default (no over-targeting)
⚠️ App rating is currently 4.2 (3 reviews) — recommendation: ask early users for reviews to lift TTR

The developer reviewed the checklist, acknowledged the two warnings as follow-up work, and launched the campaign at 3:47pm — 1 hour 47 minutes after starting the Pipeline.

The outcome (7-day measurement)

Metric	Week 1 actual	Typical indie launch baseline
Total spend	$342 (under-paced; expected)	$350
Total installs	81	25-45
Average CPI	$4.20	$8-15
Brand CPI	$0.95	$1.50-3 (with leakage)
Category-core CPI	$4.80	$9-14
Discovery CPI	$5.40	$10-18
Search Match share of spend	18%	35-50% (often unmonitored)

The first-week CPI of $4.20 was 65-75% below typical indie launch CPI of $8-15.

Why the CPI was better than typical

Three structural advantages:

1. Brand isolation from day 1

Most indie launches accidentally let brand traffic leak into Discovery — they bid the same keywords across ad groups or forget to add Brand-as-negative on Discovery. The Launch Pipeline’s structure prevented this; Brand campaign captured brand intent at $0.95 CPI while Discovery focused on actual exploration.

2. Bid calibration to floor + 30%

Bidding too low results in no impressions (frustrating for first-time advertisers, who often double bids panic-style). Bidding too high wastes early budget. The Pipeline’s floor + 30% calibration produced enough impressions to gather data without overpaying.

3. Tight budget caps per ad group

The Pipeline split the $50/day across ad groups with appropriate proportions. Without this guidance, many indie launches concentrate budget into Discovery (because it has the most matches), which produces noisy data and high CPI in the first week.

30-day trajectory

After week 1, the developer:

Week 2: Built Custom Product Page for Category-core (CR lifted from 32% to 41%)
Week 3: Promoted 4 high-converting Discovery search terms to Exact in dedicated ad groups
Week 3: Added 8 zero-conversion negatives from the Search Term Report
Week 4: Upgraded to ASAPilot Starter plan ($39/month) for daily summary + CPI alert automations
Week 4: Lifted Brand bid to $1.00 (impression share was below 90%)

End-of-month metrics:

Metric	Week 1	Week 4
Average CPI	$4.20	$3.10
Daily installs	11.5	19
Total spend	$342	$1,485 (cumulative)
Total installs	81	432

The $1,485 spent produced 432 installs at $3.44 blended CPI — well below the typical $2,500-3,500 spend that would have produced equivalent volume under untooled launch.

What worked

The structure was the unlock. A first-time indie advertiser following the Launch Pipeline’s structure outperformed not because of access to special data, but because the structure prevented common first-month mistakes (brand leakage, over-bidding, keyword duplication).

Brand isolation was the biggest single saving. Without Brand isolation, indie launches typically pay $5-10 CPI for traffic that should cost $1-2. On a $1,500 budget, this single structural choice is worth ~$200-400.

Read-only safety was reassuring. The developer reviewed and approved every Pipeline step. No automated changes happened without their explicit sign-off.

What was harder

47 candidate keywords took longer to review than expected. The developer initially felt overwhelmed by the keyword list. ASAPilot’s per-keyword rationale (“competitor X bids on this”) helped speed it up by stage 3.
Custom Product Page review (App Store) took 48-72 hours. The first-week metrics did not yet reflect the CPP impact; that came in week 2.
Trust took time to build. The developer wanted to “verify” each ASAPilot recommendation against external sources for the first few days. By day 5, the workflow was direct trust.

Recommended for

This pattern works best for:

First-time ASA advertisers launching their first app
Solo indie developers with limited time for trial-and-error
Small initial budgets ($30-$200/day) where waste reduction matters most
Apps in competitive but not winner-take-all categories (productivity, fitness, utilities, casual games)

The Free tier is sufficient for the Launch Pipeline; upgrading to Starter or Growth becomes worthwhile after the campaign is established and recurring automations matter.

See pricing or read the new app launch checklist for the structure used in the Pipeline.