AWMY — Marketing intelligence

We make marketing predictable.

Turn competitor content, customer signals, and market activity into decisions your team can actually use.

For performance teams · agencies · product companies

Early access
No.01 The right infrastructure never existed

You can find data. You can’t find meaning.

Teams have access to more marketing data than ever, yet critical decisions still depend on assumptions, isolated reports, and incomplete context.

01

Fragmented discovery

Insights appear in isolated channels — communities, competitor campaigns, customer reviews. Most teams never see the full picture.

02

Structural blind spots

Teams optimize within their own category and rarely observe adjacent markets where new patterns and expectations emerge first.

03

Research doesn’t scale

Manual research is expensive, inconsistent, and hard to repeat. Discoveries disappear into docs, chats, and individual expertise.

No.02 Who it’s for

Built for teams that run on marketing decisions.

01 Primary

Performance marketing teams

  • Heavy dependence on paid acquisition
  • Constant creative iteration
  • Need for faster market feedback loops
02 Secondary

Brand and full-service agencies

  • Cross-industry intelligence requirements
  • Continuous need for fresh insights
  • Pressure to justify strategic recommendations
03 Tertiary

Product companies

  • Strong internal product expertise
  • Limited cross-category visibility
  • Need to identify emerging opportunities earlier
No.03 The product

Every module answers a different strategic question.

Combined, they reveal opportunities invisible to traditional analytics tools.

Module 01 Live

Organic analysis

Customer intelligence from organic conversations.

Outputs
  • Pain maps, personas (ICPs), voice of customer
  • Buying signals, trend detection
  • Weekly digests, Airtable integration
Sources
Reddit Threads TikTok Quora YouTube
Researching organic conversationsNicheDating 50+
1,240Conversations
8Pains
3Personas
Persona 1 of 3 20 authors · 18 threads
Persona

Divorced 50+, dating again

Divorce after a long marriage. Kids grown and living apart. After a lonely holiday — decides something has to change.

MotivationCompanionship with dignity, not pity
AngleIdentity · the right to feel like a living person again
Pains · 4
Don’t want to look desperate Blue ocean
Don’t know who I am now Blue ocean
Afraid of my kids’ reaction Red ocean
It’s too late for me Red ocean
Reddit 4 TikTok 2 Quora 1
NewPain · blue ocean

Don’t know who I am now

“I don’t know who I am outside of being someone’s husband”

AngleIdentity · searching for a new self
1,100 upvotes · 14 authors
Module 02 Live

Competitor analysis

Structured analysis of competitor marketing activity.

Outputs
  • Ad creative tracking, structure & narrative breakdown
  • Scaling & shutdown tracking
  • Weekly digests, Airtable integration
Sources
Meta
Researching competitor adsNicheDating 50+
3,077Creatives
2Competitors
6Angles
Bumble
  • ▲Don’t want to look desperate3 ads · ~420K
    “Date on your terms, no apologies”
    Socialguarding their dignity
  • ▲Swipe fatigue1 ad · ~85K
    “Quality matches, not endless swipes”
    Emotionalcraves real connection, not volume
  • ▼Apps not for my age2 ads · ~50K
    “Dating after 50 made simple”
    Identitywants to feel it’s built for them
Hinge
  • ▲After losing a partner2 ads · ~110K
    “Honor the past. Open to the future”
    Identityneeds permission to move on
  • ▼It’s too late1 ad · ~30K
    “It’s never too late for love”
    Emotionalfears they’ve missed their window
Competitor gap

Rivals scale “desperate” & “after-loss”.

The Identity angle — “who am I now” — sits untouched.

Module 03 Soon

Customer voice

Deep analysis of existing customer feedback.

Outputs
  • Review & interview analysis, ICPs
  • Motivation mapping, churn signals
  • Messaging & product opportunities
Sources
App Store Trustpilot Interviews In-app surveys Quizzes
Researching customer feedbackNicheDating 50+
Feedback report 1,120 reviews · 3.4/5
Positive 38%Negative 62%
Top themesmentions
▼ Fake profiles & scams142
▼ Too complicated to start88
▲ Matches feel age-appropriate76
▼ Felt judged, out of place54
Signal by source
App Store 480 Play Market 390 In-app 250 Interviews 8
Interview▲ “actually met someone real on here, at 58”
Opportunities · 3

Trust-first — real, verified people

Answers the #1 complaint: fake profiles & scams.

More opportunities
Guided setup — fix “too complicated to start”
Age-positive, judgment-free tone
Module 04 Soon

Overlap analysis

Market opportunity detection across datasets.

Outputs
  • Demand vs supply, competitive gaps
  • Blue & red ocean detection
  • Strategic & tactical recommendations
Sources
Cross-module
Researching opportunitiesNicheDating 50+
Open lane last 7 days
Market opportunity

Own the slow-dating shift

Demand▲ +34% in 6d · 82/100 · emerging
Supply▼ 1 me-too ad · Bumble ~85K
Signal“slow dating is a thing and I’m here for it”▲ 4,200
The move Launch ASAP
PainSwipe fatigue → wants slow, real connection
Creativewarm · slow · real connection · beyond smalltalk
Synthesized from 01–03
No.04 How it works

Why not just use ChatGPT?

Large language models generate answers from available information. They do not build structured market intelligence systems by default.

One engine. Five layers.

The system combines data collection, normalization, market mapping, signal extraction, and analytical interpretation into a single research workflow.

01 Collect

Tens of thousands of creatives, licensed Reddit, reviews — data access closed to base models.

02 Methodology

Behavioral economics, cognitive psychology, game theory. A model has no method — we give it one.

03 Model ensemble

Claude · GPT · Gemini · DeepSeek + fine-tuned. We depend on none.

04 Verification

Hallucination detection at generation signal level — not just cross-checks.

05 Interpretation

The hidden drivers behind a decision — the real why surveys never reveal.

No.05 The team

The people behind the methodology.

Execution
Vitaliy
CEO

NLP Engineer, Tech Lead, 3x founder.

LinkedIn
Integration
Oles
COO / CPO

7 years engineering, 2x founder.

LinkedIn
Methodology
Iovana
CGO

17 years marketing & revenue systems, 4x founder.

LinkedIn
Architecture
Oleksandr
CTO

EPAM, Monobank, Superhuman (ex Grammarly).

LinkedIn