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Start with public signals, add your real numbers when useful, and get a clear next move. Connected reports name the metric and the date we will return.

NocturaSleep & Focus · iOS App Report · May 2026

GROW MY APP

Public signal

Too few ratings exist to support a product diagnosis yet.

Lifetime ratings: 11
Average rating: 4.6
Recent releases: 3

What this means

The listing shows active product work, but eleven ratings are too thin to separate a real quality issue from noise. The honest first move is to create a readable trust signal before diagnosing retention or revenue.

One evidence-bound next movePublic data

Next moveGoal: Get more ratings before optimizing anything else
SignalThe app has a visible value moment, but almost no rating history.
What to doPrompt for a rating during onboarding or right after a user completes the app's core successful action.
Metric to improveNew ratingsAverage rating

Top insight

Revenue is growing, but weak retention will limit the sale multiple.

Paying customer outcome after 30 daysRevenue +9.4%

Still paying: 41%
Gone by day 30: 59%

Retention gapMore customers leave than stay.Revenue is rising, but the growth is still fragile.

Monthly recurring: $31.2k
Still paying · day 30: 41%
Refund rate: 8.2%

What this means

Monthly recurring revenue rose 9.4%, but 59% of new paying customers are gone by day 30 and refunds are high. Buyers pay more for predictable revenue. Improving retention and refunds before listing the app can support a stronger multiple.

Three initiatives to tackle nextRanked

Top initiativeGoal: Make first-month revenue more predictable
SignalMost customer loss happens before a paying user builds a repeat habit.
What to doGuide every new user to create one recurring task on day one, then bring them back with a useful day-two reminder.
Metric to improve7-day paying retention30-day paying retentionReview in 30 days
Fix refunds before buyers ask
An 8.2% refund rate invites price negotiation.
Next moveShow both plans and explain renewal before purchase.
WatchRefund rateTrial-to-paid
Make the growth provable
Buyers discount revenue they cannot attribute.
Next moveBuild a by-source view of 30-day revenue to hand over in diligence.
Watch30-day revenueCost per lasting customer

Top insight

Downloads are rising, but the seller cannot show what is driving them.

Seller's source reportTraffic not attributed

Search can include paid and unpaid downloadsNo ad-platform proof

Asking price: $780k
Owner profit · 12 mo.: $210k
Ad spend: Missing

What this means

Downloads increased consistently from April to June, but there is no traffic-source or ad-spend report showing why. That pattern may reflect paid marketing, so the growth should not be treated as organic yet. Request platform reports for the same dates and check public ad activity independently.

Three initiatives to tackle nextRanked

Top initiativeGoal: Verify what is driving download growth
SignalDownloads rose each month, but the seller provided no traffic-source or ad-platform records.
What to doRequest April-to-June acquisition and spend exports from every active platform, then check public ad libraries for current campaigns.
Metric to improveVerified downloads by sourceCost per paying customerRecheck before offer
Check if one plan hides the churn
Annual billing can mask cancellations for a year.
Next moveCompare trials, paid users, refunds, and 30-day revenue by plan.
WatchTrial-to-paidRefund rate30-day revenue
Do not pay for the seller's ideas
The asking price includes product ideas that have not shipped.
Next movePrice unproven improvements as upside, not revenue.
WatchPrice-supporting sales

How it works

Different signals go in. A clear read comes out.

We reconcile the business across the same dates, preserve what happened before, and surface the facts, gaps, and conflicts behind each recommendation, with an operator's eyes on the result.

01
Start with public data
We analyze the app's public footprint based on your app's App Store URL.
02
Connect your data, add context or run it in autopilot
Add revocable read-only sources, exports, history, and goals for a sharper read, or plug the read straight into your own agent or LLM.
03
Get facts and ranked next moves
AI interprets the evidence with explicit confidence and suggests the next moves. An operator hand-reviews every read before it lands in your inbox. When you accept a move and opt into follow-up, we record the date and come back with what moved.

How a read is built

Every signal, reconciled into one answer.

Your app signals

Public and market data
App Store Connect
RevenueCat or other
App context, analytics, history
Marketing data
More

Connect what changed with what moved.

Align evidence to the same dates
State facts and confidence
Connect changes with outcomes

Our analysis

01Plain-English insights
02Evidence-bound next moves
03The metric to watch

Operating memory

Build a record that can connect initiatives to results.

What changed

04 AprRelease 4.6Intent onboarding
18 AprSleep ResetCampaign launch
02 MayPaywall BPricing test

What we learned

InitiativeObserved resultWatch next

Intent onboardingActivation +8.7 ptsD7 retained trials

Sleep ResetMore traffic, lower fit30-day revenue

“7 nights free”Refunds +2.1 ptsPlan-level retention

How data is handled →

Questions, answered plainly

Before you share anything.

Is this another dashboard?

No. A dashboard leaves the interpretation to you. We state the facts in plain English and show only the next validation the available evidence can support. Thin evidence produces a smaller answer, not a longer disclaimer.

What do I get if I want to grow my app?

The whole business in one view, what is actually causing the plateau, and momentum from one initiative to the next. Only the findings that change the decision, and each recommendation paired with the signal that should confirm or challenge it.

What do I get if I am selling?

A profit and sale-readiness read that makes the business easier to trust and harder to discount: a credible buyer story backed by evidence, handover preparation, and support through the negotiation.

What do I get if I am buying?

Seller claims turned into a focused diligence process: a tailored red-flag list, a custom owner-question script, transfer preparation, and support pricing the risk before you inherit it.

How do AI and expert review work together?

AI works inside a harness built by experienced iOS app operators. It aligns evidence, states the facts, separates evidence from inference, and shows its confidence. Reports are prepared and reviewed with human involvement.

How is my data handled?

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