chat-first aso for mobile apps

A Personal ASO/ASA Agent in Your Chat

We deploy an OpenClaw-like agent for your team on a dedicated VPS, connect your MCP credentials, and move Apple Search Ads analytics and automation into a chat-first workflow.

No constant work across 5-7 dashboards. No manual exports. No context loss across teammates.

1 chat
for analytics, decisions, and execution
dedicated VPS
an isolated runtime per client
apollo-like app
managed through mobile chat
s01

What You Pay For

Dedicated Execution Runtime

Your personal agent is deployed on a separate VPS environment for your team. No shared runtime and no single account for all clients.

Value: privacy, control, and predictable performance.

Integration of Your MCP Credentials

We connect your tokens and access rights to the MCP servers and ad data sources that are actually needed for your operations.

Value: a production-ready setup from day one, not a platform "for later".

ChatOps for ASO and ASA

Instead of navigating multiple dashboards all day, you give a command in chat: the agent collects metrics, explains anomalies, and proposes the next best step.

Value: more decisions, less operational routine.

Campaign Automation

We set up workflows: daily digests, alert rules, KPI checks, recommendations, and repeatable actions based on your playbooks.

Value: steady optimization pace without 24/7 manual supervision.

s02

Why This Dramatically Simplifies Operations

Current State
With aso.network
Business Outcome
Reports are assembled manually across multiple dashboards
One chat request returns a full summary and priorities
Your team spends fewer hours on routine operations
Reaction to KPI drops is delayed
The agent monitors KPIs and sends automatic alerts
Issues are caught before budget leakage accelerates
Decisions are fragmented across chats and spreadsheets
Decision history and actions stay in one timeline
More transparency and less duplicated work
Hard to scale process across new geos and apps
Automation templates scale to the full app portfolio
Growth without proportional headcount growth
s03

How Day-to-Day Work Looks in Chat

Show where ASA CPI increased over the last 7 days and suggest the 3 highest-impact actions.
I found 2 campaigns with CPI growth above 18%. Main reason: expanded broad traffic in the US and UK. Suggested actions: 1) reduce broad ad group bid by 12%, 2) add negative keywords, 3) reallocate 20% of budget to exact ad groups with stronger ROAS.
Apply actions 1 and 2. Move action 3 to tomorrow's plan and send control metrics in the morning.
Done. Changes are applied in the runtime. Tomorrow at 09:00 I will send CPI, TTR, CR, and spend delta.
s04

How We Launch in a Short Cycle

01

Define the Runtime

We align goals, KPIs, security rules, and the list of connected data sources.

02

Deploy VPS and Agent

We set up the dedicated runtime and connect MCP servers using your credentials.

03

Configure Scenarios

We add automations and validate them on your real ASA campaigns.

04

Switch Team to Chat Mode

We deliver ready command templates to get analytics and trigger actions fast.

s05

Transparent Pricing Model

You are not paying for "UI access". You are paying for a working operating runtime: dedicated VPS + MCP integrations + automation + support for production workflows.

  • Scope depends on app count, geographies, and data sources.
  • The more routine work your team has today, the faster the chat-first model pays back.
  • Result focus: fewer manual operations, faster "signal -> decision -> action" loops.
s06

FAQ

Where are my credentials stored?

In your dedicated VPS runtime. Access is used only for approved integrations.

Can we operate without constantly logging into ad dashboards?

Yes. The core operational loop moves into chat, so dashboard use becomes occasional.

Who controls final campaign actions?

You define the policy: where actions are automated and where explicit chat approval is required.

If your team spends too much time in interfaces, it is time for chat-first ASO/ASA

In the demo, we show how your current process moves into an isolated chat runtime with clear unit economics and fast optimization loops.