Local Market Typing Framework
A strategic model revealing where Axios can win — and how to innovate, differentiate and grow across 34+ markets
Local Market Typing Framework
A strategic model revealing where Axios can win — and how to innovate, differentiate and grow across 34+ markets
Create a common language for describing market dynamics or aligning teams on city-by-city strategy.
Axios Local expanded quickly into dozens of cities — each with different competitive landscapes, civic identities, audience densities, and revenue potential.
Leadership needed a unified strategic lens to answer foundational questions:
What type of market is each city?
Where does Axios have a natural advantage?
Where should we double down, adjust, or rethink our approach?
How do we tailor editorial, marketing and revenue strategy to local conditions?
I built Axios’ first Local Market Typing Framework: a multi-dimensional strategic model integrating more than 200 internal and external signals to categorize each city into distinct strategic “types.”
This system combines:
Local audience behaviors
Competitive media landscapes
Civic identity + economic drivers
Professional influencer density
Axios performance data
Advertising + revenue patterns
Market saturation + differentiation potential
The goal: give Axios a shared, strategic map of where and how to win.
Each city receives a data-backed “type,” paired with implications for editorial tone, product strategy, revenue narratives, and market-level decision-making.
📊 200+ signals synthesized into a single, repeatable strategy model
🗺️ 34 cities mapped into clear strategic types adopted by leadership
🎯 Provided the backbone for city-level strategy, from editorial priorities to positioning
📈 Informed resource allocation, advertiser framing, and expansion conversations
🤝 Enabled cross-functional teams to work from the same “market reality” for the first time
This framework became a central decision-support tool, helping Axios Local shift from intuition-driven planning to data-backed market strategy.
Accountable for:
Ensuring the framework aligned with editorial, revenue and growth goals
Driving cross-functional understanding and adoption across Local, Revenue and Editorial leadership
Maintaining clarity and rigor as the model scaled and informed broader planning
Delivering a model that supported long-term strategy, not just a one-time classification
Responsible for:
Designing the market-typing methodology and multi-signal scoring framework
Conducting competitive analysis and synthesizing 200+ market indicators
Creating individual city profiles, scoring sheets, opportunity maps and strategic implications
Translating complex data into a simple, intuitive model leadership could immediately use
Signal Identification & Data Mapping
Pulled data from LinkedIn, Census, local media ecosystems, Axios performance dashboards, ACV patterns, civic identity indicators and competitive landscapes.
Model Development
Built a weighted scoring system incorporating audience potential, competitive saturation, professional density, revenue readiness and differentiation signals.
City Typing & Profiles
Assigned each city a strategic type, with accompanying diagnostics: strengths, risks, opportunities, long-term potential.
Strategic Implications
Developed tailored recommendations for editorial tone, content mix, coverage depth, growth tactics and revenue positioning for each type.
Leadership Alignment
Ran reviews with Local, Growth, Product, Revenue and Editorial leadership to refine, validate and operationalize the model.
Deliverables I Created
Market Typing Framework + Scoring Model
34 City Profiles
Competitive Landscape Summaries
Strategic Recommendation Decks
Tools I Used
LinkedIn campaign manager
Looker BI
Sailthru
ChatGPT
Skills I Applied
Segmentation leadership
Vendor management + methodological direction
Mixed-methods research
Strategic modeling
Cross-functional alignment
Executive storytelling
Different cities demand different strategies. One-size-fits-all models hide more than they reveal.
Clarity accelerates planning. Once teams could see each city through the same lens, decisions moved faster.
This framework became an ecosystem tool. Editorial, revenue and growth teams now plan in lockstep, grounded in shared reality.